From order analysis, content creation, knowledge bases, to process handoffs: start with a real problem, learn a method, then use templates to produce your own results.
Don't try to learn all the tools first; complete one thing first.
Download the free learning pack, work through a fictional sample, then decide which capabilities are worth integrating into your business.
01 Choose a real problem
For example, organizing orders, analyzing reviews, creating voiceover content, or turning articles into searchable material. Each resource indicates who it's for, what input it requires, and what it delivers.
02 Ten-minute startup
After extracting, open SKILL.md and provide it along with support files like references/ and templates/ to your AI tool. First, ask it to run only the teaching sample within the pack, then verify against the expected output.
03 Evaluate value based on results
Keep sources, definitions, and review records. Producing a table or draft doesn't mean the system is deployed; connecting real accounts and publishing externally are separate steps.
Beyond the method packs, there are also original mini-tools you can use in your browser.
Voiceover Motion Workbench
Import local videos and subtitles, drag cards, customize backgrounds, and freely disable watermarks. Export the final video with original audio directly; use MP4 when the browser supports it, otherwise clearly output WebM. Assets stay on your device.
No account needed, load the sample to practice. Adjust subtitle position, color, and pace first, then export the short video to review; projects can be saved and continued later.
23 standalone method packs covering content, business data, development, and enterprise processes. Look at the input and output first, then download and practice; for continuous use, connect the method into a workbench.
New here? Start with a small exercise
Start with a specific task
Produce a result first, then expand the entire process.
Choose the exercise closest to you. Verify with the sample first, then decide whether to connect real business.
01
Create voiceover
Produce a short video first, practicing subtitle timing, frame position, and final output review.
Prepare first
Short video you have rights to and SRT subtitles
Practice output
Practice video with adjustable subtitles
Acceptance criteria
Check the opening and closing frames, audio, and subtitle alignment section by section
Select 2 - 3 items to compare and find the best fit.
No matching resources. Try fewer keywords or select “All resources.”
01Workflow
Content growth and video productionThis version has been reviewed.
Talking-head motion graphics workbench: turn subtitles into visuals
Free voiceover dynamic effects workbench: import videos and SRT locally, drag captions, customize card backgrounds, watermark can be turned off, and export MP4 or WebM output with original audio. Offline source code and Skill included, no asset upload required.
Suitability & requirements
Best for
Voiceover creators, enterprise content teams, video editors, and FDE learners
Talking-head motion graphics workbench: turn subtitles into visuals
Free voiceover dynamic effects workbench: import videos and SRT locally, drag captions, customize card backgrounds, watermark can be turned off, and export MP4 or WebM output with original audio. Offline source code and Skill included, no asset upload required.
Who it's for
Voiceover creators, enterprise content teams, video editors, and FDE learners
Reading & practice reference
20minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
In-browser local compositing; no dependency installation; supports final videos with original audio and transparent layer export
Version & license
1.5.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · Original browser tool with accompanying documentation. Verified input limits, local asset processing, no external dependencies, and export boundaries; no third-party project code or assets included. Before using your own materials, still confirm authorization and sensitivity levels.
Content growth and video productionThis version has been reviewed.
MiniMax H3 local video workflow: generate raw footage, edit subtitles, export final video
Learn to use local ComfyUI and MiniMax H3 to create voiceover raw footage, then drag captions, customize card backgrounds, and export the final video in the FORMWEFT workbench. Provides original Skill, de-identified workflow, prompts, and caption samples, no model weights included.
Suitability & requirements
Best for
Voiceover creators, enterprise content teams, and local AI video learners
Reading & practice reference
35 minutes
Version / License
1.0.0 · MIT (original tutorials and tools); models separately licensed
MiniMax H3 local video workflow: generate raw footage, edit subtitles, export final video
Learn to use local ComfyUI and MiniMax H3 to create voiceover raw footage, then drag captions, customize card backgrounds, and export the final video in the FORMWEFT workbench. Provides original Skill, de-identified workflow, prompts, and caption samples, no model weights included.
Who it's for
Voiceover creators, enterprise content teams, and local AI video learners
Reading & practice reference
35minutes; excludes installation, model generation, and business validation
Internet access
On-demand online
Local software / dependencies
Offline verification script in the package; generation requires separate ComfyUI, Python, GPU, and licensed models
Version & license
1.0.0 · MIT (original tutorials and tools); models are separately licensed
Public review record
This version has been reviewed. · 2026/09/05 · Based on one real local H3 generation and voiceover workbench export, this is an original teaching pack. Checked fixed file list, sanitized workflow, offline verification, and subtitle handover; contains no model weights, generated videos, or auto-installers. The sample SRT is an editing script pending audio calibration, not accurate transcription.
AI video and content productionThis version has been reviewed.
AI Short-Drama Production Design and Acceptance Skill
Original AI short-drama production design and acceptance Skill: outputs planning, characters, storyboards, task lists, and acceptance sheets by default; only after tools, data destinations, and authorizations are approved does actual generation begin.
Suitability & requirements
Best for
Content teams, brand teams, AI video producers, and FDE engineers
AI Short-Drama Production Design and Acceptance Skill
Original AI short-drama production design and acceptance Skill: outputs planning, characters, storyboards, task lists, and acceptance sheets by default; only after tools, data destinations, and authorizations are approved does actual generation begin.
Who it's for
Content teams, brand teams, AI video producers, and FDE engineers
Reading & practice reference
45minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; approved local or cloud Providers can be connected per project
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · FORMWEFT original documentation-type Skill, intended by default for production planning and acceptance design. Structural checks, offline static scans, and manual file-by-file reviews are complete. The download package contains no scripts, dependencies, model weights, keys, auto-uploads, or auto-publishing. MIT covers only original documentation and templates, not third-party tools, models, assets, or output.
AI video and content productionThis version has been reviewed.
AI talking-head and digital human production design Skill
Original AI voiceover and digital human production design Skill: covers licensing, spoken scripts, performance, lip sync, captions, and acceptance; by default does not call models, upload assets, or auto-publish.
Suitability & requirements
Best for
Marketing, training, product education, digital IP, and content operations teams
AI talking-head and digital human production design Skill
Original AI voiceover and digital human production design Skill: covers licensing, spoken scripts, performance, lip sync, captions, and acceptance; by default does not call models, upload assets, or auto-publish.
Who it's for
Marketing, training, product education, digital IP, and content operations teams
Reading & practice reference
35minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; approved TTS, digital human, or editing Providers may be connected per project
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · FORMWEFT original document-type Skill; by default intended only for production planning and acceptance design. Structure validation, offline static scan, and per-file manual review completed; the download package contains no scripts, dependencies, account keys, voice cloning, or auto-publishing. The MIT license covers only original documents and templates, not third-party tools, models, assets, or outputs.
Security, governance, and trusted deploymentThis version has been reviewed.
GitHub repo quick diligence Skill
Without cloning, installing, or running repository code, verify license, maintenance, supply chain, release integrity, and adoption risks to form a traceable GitHub repository due diligence evidence package.
Suitability & requirements
Best for
FDE, platform engineering, open-source governance, security, and technology procurement teams
Without cloning, installing, or running repository code, verify license, maintenance, supply chain, release integrity, and adoption risks to form a traceable GitHub repository due diligence evidence package.
Who it's for
FDE, platform engineering, open-source governance, security, and technology procurement teams
Reading & practice reference
30minutes; excludes installation, model generation, and business validation
Internet access
On-demand online
Local software / dependencies
None; if online verification is needed, the user must approve sites and scope
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · Written independently clean-room based on directory topics; no licensed Feishu original package copied or redistributed. The pinned ZIP has passed structural validation, offline static scanning, and per-file manual review; no scripts, dependencies, install hooks, mandatory network access, or automatic remote operations.
Enterprise AI and FDEThis version has been reviewed.
GitHub high-potential project radar Skill
Use a repeatable evidence framework to discover and compare high-potential GitHub projects, distinguishing popularity, maintenance quality, adoption fit, and supply chain risks without treating star counts as conclusions.
Suitability & requirements
Best for
FDE, R&D efficiency, technology strategy, innovation, and product research teams
Use a repeatable evidence framework to discover and compare high-potential GitHub projects, distinguishing popularity, maintenance quality, adoption fit, and supply chain risks without treating star counts as conclusions.
Who it's for
FDE, R&D efficiency, technology strategy, innovation, and product research teams
Reading & practice reference
30minutes; excludes installation, model generation, and business validation
Internet access
On-demand online
Local software / dependencies
None; if public web retrieval is needed, user must approve sites and scope
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · Written independently clean-room based on catalog themes; did not copy or redistribute unlicensed Feishu original package. Fixed ZIP has passed structural validation, offline static scanning, and file-by-file manual review; default read-only, no cloning, running, modifying remote, or auto-contacting authors.
E-commerce visuals and content productionThis version has been reviewed.
E-commerce image prompt reconstruction Skill
Break a reference image into composition, subject, lighting, materials, text safe area, and constraints to form reviewable, iterable e-commerce image prompts without directly copying brand assets.
Suitability & requirements
Best for
Business operations, marketing, e-commerce, content, data, and FDE teams
Break a reference image into composition, subject, lighting, materials, text safe area, and constraints to form reviewable, iterable e-commerce image prompts without directly copying brand assets.
Who it's for
Business operations, marketing, e-commerce, content, data, and FDE teams
Reading & practice reference
25minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; only processes reference materials explicitly provided and authorized by the user
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/04 · Rewritten independently based on the Feishu directory topic clean-room, without copying or redistributing the original package text. Conclusions apply only to the current fixed hash: the archive structure has been parsed, static rule result is eligible, with 6 files and no scripts, dependencies, or install hooks; online boundaries follow the statements in this resource, and files are output only to user-approved locations. Static review cannot replace runtime environment, input data, or later-version rechecks.
E-commerce visuals and content productionThis version has been reviewed.
E-commerce main image evidence-based diagnosis Skill
Diagnose e-commerce product images using five dimensions: information hierarchy, product recognition, selling points, platform constraints, and experimental hypotheses, and output actionable change orders rather than just aesthetic opinions.
Suitability & requirements
Best for
Business operations, marketing, e-commerce, content, data, and FDE teams
E-commerce main image evidence-based diagnosis Skill
Diagnose e-commerce product images using five dimensions: information hierarchy, product recognition, selling points, platform constraints, and experimental hypotheses, and output actionable change orders rather than just aesthetic opinions.
Who it's for
Business operations, marketing, e-commerce, content, data, and FDE teams
Reading & practice reference
30minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; use a browser or image viewer to open user-approved materials as needed.
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/04 · Rewritten independently based on the Feishu directory topic clean-room, without copying or redistributing the original package text. Conclusions apply only to the current fixed hash: the archive structure has been parsed, static rule result is eligible, with 6 files and no scripts, dependencies, or install hooks; online boundaries follow the statements in this resource, and files are output only to user-approved locations. Static review cannot replace runtime environment, input data, or later-version rechecks.
E-commerce operations and data analysisThis version has been reviewed.
E-commerce operations data analysis Skill
Establish a unified standard from orders, traffic, ads, products, and fulfillment data to identify profit and growth issues, forming a business analysis with evidence, responsible parties, and next steps.
Suitability & requirements
Best for
Business operations, marketing, e-commerce, content, data, and FDE teams
Establish a unified standard from orders, traffic, ads, products, and fulfillment data to identify profit and growth issues, forming a business analysis with evidence, responsible parties, and next steps.
Who it's for
Business operations, marketing, e-commerce, content, data, and FDE teams
Reading & practice reference
40minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; you may use company-approved spreadsheet tools to process local copies
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/04 · Rewritten independently based on the Feishu directory topic clean-room, without copying or redistributing the original package text. Conclusions apply only to the current fixed hash: the archive structure has been parsed, static rule result is eligible, with 6 files and no scripts, dependencies, or install hooks; online boundaries follow the statements in this resource, and files are output only to user-approved locations. Static review cannot replace runtime environment, input data, or later-version rechecks.
Automation and workflowsThis version has been reviewed.
n8n content pipeline blueprint Skill
First clarify the boundaries of input, approval, generation, quality inspection, publishing, and rollback, then configure the content production workflow into an auditable n8n blueprint, defaulting to not connecting any external accounts.
Suitability & requirements
Best for
Business operations, marketing, e-commerce, content, data, and FDE teams
First clarify the boundaries of input, approval, generation, quality inspection, publishing, and rollback, then configure the content production workflow into an auditable n8n blueprint, defaulting to not connecting any external accounts.
Who it's for
Business operations, marketing, e-commerce, content, data, and FDE teams
Reading & practice reference
35minutes; excludes installation, model generation, and business validation
Internet access
On-demand online
Local software / dependencies
None; optional n8n during implementation, must approve instance, domain, credentials, and permissions first
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/04 · Rewritten independently based on the Feishu directory topic clean-room, without copying or redistributing the original package text. Conclusions apply only to the current fixed hash: the archive structure has been parsed, static rule result is eligible, with 6 files and no scripts, dependencies, or install hooks; online boundaries follow the statements in this resource, and files are output only to user-approved locations. Static review cannot replace runtime environment, input data, or later-version rechecks.
E-commerce visuals and content productionThis version has been reviewed.
E-commerce visual production SOP Skill
Connect requirements, assets, layouts, generation, manual review, platform adaptation, and archiving into a transferable e-commerce visual production standard, reducing rework and version chaos.
Suitability & requirements
Best for
Business operations, marketing, e-commerce, content, data, and FDE teams
Connect requirements, assets, layouts, generation, manual review, platform adaptation, and archiving into a transferable e-commerce visual production standard, reducing rework and version chaos.
Who it's for
Business operations, marketing, e-commerce, content, data, and FDE teams
Reading & practice reference
35minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; may use the company's existing design and asset management tools
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/04 · Rewritten independently based on the Feishu directory topic clean-room, without copying or redistributing the original package text. Conclusions apply only to the current fixed hash: the archive structure has been parsed, static rule result is eligible, with 6 files and no scripts, dependencies, or install hooks; online boundaries follow the statements in this resource, and files are output only to user-approved locations. Static review cannot replace runtime environment, input data, or later-version rechecks.
E-commerce growth and experimentationThis version has been reviewed.
Viral main image evidence lab Skill
Use samples, variables, evidence, and experiment records to study high-performing images, distinguish correlation from causation, avoid copying competitor assets, and produce verifiable creative hypotheses.
Suitability & requirements
Best for
Business operations, marketing, e-commerce, content, data, and FDE teams
Use samples, variables, evidence, and experiment records to study high-performing images, distinguish correlation from causation, avoid copying competitor assets, and produce verifiable creative hypotheses.
Who it's for
Business operations, marketing, e-commerce, content, data, and FDE teams
Reading & practice reference
45minutes; excludes installation, model generation, and business validation
Internet access
On-demand online
Local software / dependencies
None; before studying external samples, must approve specific public domains and recording scope.
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/04 · Rewritten independently based on the Feishu directory topic clean-room, without copying or redistributing the original package text. Conclusions apply only to the current fixed hash: the archive structure has been parsed, static rule result is eligible, with 6 files and no scripts, dependencies, or install hooks; online boundaries follow the statements in this resource, and files are output only to user-approved locations. Static review cannot replace runtime environment, input data, or later-version rechecks.
Competitive intelligence and business strategyThis version has been reviewed.
Competitor evidence distillation map Skill
Organize public competitor information into a four-layer map of facts, inferences, unknowns, and actions, retaining sources and timestamps, so competitive intelligence truly serves product, marketing, and sales decisions.
Suitability & requirements
Best for
Business operations, marketing, e-commerce, content, data, and FDE teams
Organize public competitor information into a four-layer map of facts, inferences, unknowns, and actions, retaining sources and timestamps, so competitive intelligence truly serves product, marketing, and sales decisions.
Who it's for
Business operations, marketing, e-commerce, content, data, and FDE teams
Reading & practice reference
50minutes; excludes installation, model generation, and business validation
Internet access
On-demand online
Local software / dependencies
None; public research only after approved domains, terms, and scope.
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/04 · Rewritten independently based on the Feishu directory topic clean-room, without copying or redistributing the original package text. Conclusions apply only to the current fixed hash: the archive structure has been parsed, static rule result is eligible, with 6 files and no scripts, dependencies, or install hooks; online boundaries follow the statements in this resource, and files are output only to user-approved locations. Static review cannot replace runtime environment, input data, or later-version rechecks.
Content growth and video productionThis version has been reviewed.
Competitor teardown script toolkit Skill
Turn competitor research into an evidence chain, shot list, and review checklist for short videos or talking-head scripts, avoiding unverified comparisons, disparagement, and copyright material reuse.
Suitability & requirements
Best for
Business operations, marketing, e-commerce, content, data, and FDE teams
Turn competitor research into an evidence chain, shot list, and review checklist for short videos or talking-head scripts, avoiding unverified comparisons, disparagement, and copyright material reuse.
Who it's for
Business operations, marketing, e-commerce, content, data, and FDE teams
Reading & practice reference
45minutes; excludes installation, model generation, and business validation
Internet access
On-demand online
Local software / dependencies
None; specific domains must be approved before verifying public sources, and production tools are approved separately by the business.
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/04 · Rewritten independently based on the Feishu directory topic clean-room, without copying or redistributing the original package text. Conclusions apply only to the current fixed hash: the archive structure has been parsed, static rule result is eligible, with 6 files and no scripts, dependencies, or install hooks; online boundaries follow the statements in this resource, and files are output only to user-approved locations. Static review cannot replace runtime environment, input data, or later-version rechecks.
Automation and workflowsThis version has been reviewed.
Feishu data hub: reconcile first, then import
Organize order, product, and refund CSV files into clear field definitions, primary keys, currencies, and import previews, avoiding writing dirty data straight into online spreadsheets.
Suitability & requirements
Best for
E-commerce operations, finance, data leads, and project teams preparing to build Feishu multidimensional tables
Organize order, product, and refund CSV files into clear field definitions, primary keys, currencies, and import previews, avoiding writing dirty data straight into online spreadsheets.
Who it's for
E-commerce operations, finance, data leads, and project teams preparing to build Feishu multidimensional tables
Reading & practice reference
40minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; documents, templates, and samples
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · FORMWEFT independently authored Chinese methods, templates, and fictional samples; Feishu original package not redistributed. Current fixed version has completed file structure, static rules, and content review, no high-risk behavior found. Real data permissions and generated results still need user review.
Automation and workflowsThis version has been reviewed.
Article knowledge base: every answer has a source
Turn authorized articles and internal documents into a source ledger, knowledge chunks, retrieval questions, and answer evidence, handling outdated versions, conflicts, and insufficient materials.
Suitability & requirements
Best for
Knowledge operations, customer service, training, policy management, and enterprise AI project leads
Turn authorized articles and internal documents into a source ledger, knowledge chunks, retrieval questions, and answer evidence, handling outdated versions, conflicts, and insufficient materials.
Who it's for
Knowledge operations, customer service, training, policy management, and enterprise AI project leads
Reading & practice reference
35minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; documents, templates, and samples
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · FORMWEFT independently authored Chinese methods, templates, and fictional samples; Feishu original package not redistributed. Current fixed version has completed file structure, static rules, and content review, no high-risk behavior found. Real data permissions and generated results still need user review.
Content growth and video productionThis version has been reviewed.
Tool hands-on reviews: no steps left to imagination
Write reproducible tutorials using real versions, operation logs, screenshots, and read-back evidence; parts not actually verified remain as pending verification rather than being fabricated as definite steps.
Tool hands-on reviews: no steps left to imagination
Write reproducible tutorials using real versions, operation logs, screenshots, and read-back evidence; parts not actually verified remain as pending verification rather than being fabricated as definite steps.
30minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; documents, templates, and samples
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · FORMWEFT independently authored Chinese methods, templates, and fictional samples; Feishu original package not redistributed. Current fixed version has completed file structure, static rules, and content review, no high-risk behavior found. Real data permissions and generated results still need user review.
Content growth and video productionThis version has been reviewed.
Xiaohongshu content planning: from evidence to review
Score topics, create image-text drafts, hand off for manual publishing, and review performance based on real audience questions and brand evidence, with account actions always individually authorized.
Suitability & requirements
Best for
Brand marketing, content operations, founder IP teams, and enterprise content leads
Xiaohongshu content planning: from evidence to review
Score topics, create image-text drafts, hand off for manual publishing, and review performance based on real audience questions and brand evidence, with account actions always individually authorized.
Who it's for
Brand marketing, content operations, founder IP teams, and enterprise content leads
Reading & practice reference
35minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; documents, templates, and samples
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · FORMWEFT independently authored Chinese methods, templates, and fictional samples; Feishu original package not redistributed. Current fixed version has completed file structure, static rules, and content review, no high-risk behavior found. Real data permissions and generated results still need user review.
Enterprise AI and FDEThis version has been reviewed.
UI design review: turn 'premium feel' into testable questions
Use page goals, information hierarchy, font size and line height, spacing and alignment, and responsive testing to turn vague aesthetic opinions into a corrective checklist with evidence, priorities, and re-testing conditions.
Suitability & requirements
Best for
Product leads, UI/UX designers, frontend engineers, and FDE teams involved in delivery
UI design review: turn 'premium feel' into testable questions
Use page goals, information hierarchy, font size and line height, spacing and alignment, and responsive testing to turn vague aesthetic opinions into a corrective checklist with evidence, priorities, and re-testing conditions.
Who it's for
Product leads, UI/UX designers, frontend engineers, and FDE teams involved in delivery
Reading & practice reference
30minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; documents, templates, and samples
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · FORMWEFT independently authored Chinese methods, templates, and fictional samples; Feishu original package not redistributed. Current fixed version has completed file structure, static rules, and content review, no high-risk behavior found. Real data permissions and generated results still need user review.
E-commerce operations and data analysisThis version has been reviewed.
Customer review analysis: dedupe first, then discuss trends
Define deduplication, tag definitions, unique counts, denominators, and priorities clearly to avoid duplicate reviews, word frequency, and a few quotes being mistaken for all customer conclusions.
Suitability & requirements
Best for
Product, customer service, e-commerce operations, customer success, quality, and enterprise data teams
Customer review analysis: dedupe first, then discuss trends
Define deduplication, tag definitions, unique counts, denominators, and priorities clearly to avoid duplicate reviews, word frequency, and a few quotes being mistaken for all customer conclusions.
Who it's for
Product, customer service, e-commerce operations, customer success, quality, and enterprise data teams
Reading & practice reference
35minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; documents, templates, and samples
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · FORMWEFT independently authored Chinese methods, templates, and fictional samples; Feishu original package not redistributed. Current fixed version has completed file structure, static rules, and content review, no high-risk behavior found. Real data permissions and generated results still need user review.
Content growth and video productionThis version has been reviewed.
TikTok content operations: plan that executes, account without overreach
Use brand evidence to select original topics, organize weekly content, and vet creators; reserve login, contact, publishing, ad placement, and budget strictly for clearly authorized personnel.
Suitability & requirements
Best for
Overseas brands, content operations, short-video production, creator partnerships, and growth teams
TikTok content operations: plan that executes, account without overreach
Use brand evidence to select original topics, organize weekly content, and vet creators; reserve login, contact, publishing, ad placement, and budget strictly for clearly authorized personnel.
Who it's for
Overseas brands, content operations, short-video production, creator partnerships, and growth teams
Reading & practice reference
35minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; documents, templates, and samples
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · FORMWEFT independently authored Chinese methods, templates, and fictional samples; Feishu original package not redistributed. Current fixed version has completed file structure, static rules, and content review, no high-risk behavior found. Real data permissions and generated results still need user review.
E-commerce operations and data analysisThis version has been reviewed.
Amazon operations review: orders, ads, inventory on the same basis
Separate order, refund, ad, and inventory granularity, then use traceable formulas to calculate ACOS, TACOS, refunds, and coverage days, forming pending actions that do not auto-modify accounts.
Suitability & requirements
Best for
Amazon operations, advertising, supply chain, finance, brand leads, and data teams
Amazon operations review: orders, ads, inventory on the same basis
Separate order, refund, ad, and inventory granularity, then use traceable formulas to calculate ACOS, TACOS, refunds, and coverage days, forming pending actions that do not auto-modify accounts.
Who it's for
Amazon operations, advertising, supply chain, finance, brand leads, and data teams
Reading & practice reference
40minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; documents, templates, and samples
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · FORMWEFT independently authored Chinese methods, templates, and fictional samples; Feishu original package not redistributed. Current fixed version has completed file structure, static rules, and content review, no high-risk behavior found. Real data permissions and generated results still need user review.
Data analysis and dashboardsThis version has been reviewed.
Group chat insights: see problems, don't profile individuals
Turn authorized, exported, minimized group chat spreadsheets into a ledger of group-level issues, decisions, and actions; after deduplication, disclose the denominator, protect privacy, and avoid profiling members by performance or personality.
Suitability & requirements
Best for
Business operations, customer success, project leads, knowledge management, and teams needing to review collaboration issues
Group chat insights: see problems, don't profile individuals
Turn authorized, exported, minimized group chat spreadsheets into a ledger of group-level issues, decisions, and actions; after deduplication, disclose the denominator, protect privacy, and avoid profiling members by performance or personality.
Who it's for
Business operations, customer success, project leads, knowledge management, and teams needing to review collaboration issues
Reading & practice reference
35minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; documents, templates, and samples
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · FORMWEFT independently authored Chinese methods, templates, and fictional samples; Feishu original package not redistributed. Current fixed version has completed file structure, static rules, and content review, no high-risk behavior found. Real data permissions and generated results still need user review.
Agents and workflowsThis version has been reviewed.
RPA process blueprint: design for failure first, then discuss automation
Break processes into deterministic, assisted, and fully manual steps; define states, idempotency, authoritative readback, failure paths, and takeover materials; stop immediately at CAPTCHAs - do not auto-recognize, bypass, or retry.
Suitability & requirements
Best for
Business operations, process leads, automation engineers, risk control, operations, and teams preparing to adopt RPA
RPA process blueprint: design for failure first, then discuss automation
Break processes into deterministic, assisted, and fully manual steps; define states, idempotency, authoritative readback, failure paths, and takeover materials; stop immediately at CAPTCHAs - do not auto-recognize, bypass, or retry.
Who it's for
Business operations, process leads, automation engineers, risk control, operations, and teams preparing to adopt RPA
Reading & practice reference
40minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; documents, templates, and samples
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · FORMWEFT independently authored Chinese methods, templates, and fictional samples; Feishu original package not redistributed. Current fixed version has completed file structure, static rules, and content review, no high-risk behavior found. Real data permissions and generated results still need user review.
Enterprise AI and FDEThis version has been reviewed.
Team SOP handover: only counts as received when someone can pass independently
Turn role experience into role-based SOPs, least-privilege checklists, exception paths, and calculable acceptance records; document handoff is not done until independent reproduction and reverse handoff serve as release evidence.
Suitability & requirements
Best for
Business managers, FDE engineers, project delivery, customer success, training leads, and teams taking over roles
Team SOP handover: only counts as received when someone can pass independently
Turn role experience into role-based SOPs, least-privilege checklists, exception paths, and calculable acceptance records; document handoff is not done until independent reproduction and reverse handoff serve as release evidence.
Who it's for
Business managers, FDE engineers, project delivery, customer success, training leads, and teams taking over roles
Reading & practice reference
35minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; documents, templates, and samples
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · FORMWEFT independently authored Chinese methods, templates, and fictional samples; Feishu original package not redistributed. Current fixed version has completed file structure, static rules, and content review, no high-risk behavior found. Real data permissions and generated results still need user review.
Enterprise AI and FDEThis version has been reviewed.
Enterprise AI practice collection: 23 methods in one take
Combine R&D, short-drama voiceover, e-commerce, data, Feishu, knowledge base, and process handoff methods into one learning collection. Choose a set based on business problems, do a sample first, then apply to your own materials.
Suitability & requirements
Best for
Business teams and FDE learners who want to practice AI with real business
Enterprise AI practice collection: 23 methods in one take
Combine R&D, short-drama voiceover, e-commerce, data, Feishu, knowledge base, and process handoff methods into one learning collection. Choose a set based on business problems, do a sample first, then apply to your own materials.
Who it's for
Business teams and FDE learners who want to practice AI with real business
Reading & practice reference
15minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
None; documents, templates, and samples
Version & license
1.0.0 · MIT
Public review record
This version has been reviewed. · 2026/09/05 · FORMWEFT independently authored Chinese methods, templates, and fictional samples; Feishu original package not redistributed. Current fixed version has completed file structure, static rules, and content review, no high-risk behavior found. Real data permissions and generated results still need user review.
Security, governance, and trusted deploymentConstrained learning
Agent Skill security audit and clean release guide
Learn how to isolate, statically check, verify licenses, declare capabilities, manually review, and cleanly rebuild third-party Agent Skills to avoid installing unknown code directly into production environments.
Suitability & requirements
Best for
Enterprise AI platforms, security, IT, open-source governance, and resource maintenance personnel
Agent Skill security audit and clean release guide
Learn how to isolate, statically check, verify licenses, declare capabilities, manually review, and cleanly rebuild third-party Agent Skills to avoid installing unknown code directly into production environments.
Who it's for
Enterprise AI platforms, security, IT, open-source governance, and resource maintenance personnel
Reading & practice reference
30minutes; excludes installation, model generation, and business validation
Internet access
Offline by default
Local software / dependencies
Python 3 standard library scanner (download not yet open)
Version & license
0.9.0 · MIT
Public review record
Constrained learning · 2026/09/05 · Methods and rules are public; scanner source code still requires independent code review and malicious archive fixture validation; currently for learning only, no executable package download.
Share your validated methods with the next practitioner.
Welcome submissions of AI Skills that solve real problems. Provide reproducible steps, examples, and usage boundaries. Quality works will be credited and included after review.
24 original packages reviewed; only independently rebuilt versions are released publicly.
Original attachments fully obtained and isolated. Risks in execution, networking, CAPTCHA automation, privacy, and authorization were found, so original attachments were not released directly. The study packages below are rewritten from a business-topic perspective.
24 / 24 obtained
Recorded per-package source, attachment structure, and fixed hash.
24 / 24 static review completed
Including nested documents and script recheck; original packages were not installed or executed. Static review cannot prove absence of backdoors.
23 independent study packages
Covering R&D, content, e-commerce, data, Feishu, knowledge base, and process handover; single and bundle downloads provided.
Publicly learnable and adaptable
MIT covers only documents, templates, and examples written by FORMWEFT; it does not authorize use of third-party brands, materials, models, or customer data.
FROM RESOURCE TO CAPABILITY
Download is not the goal; team capability is.
Verify resources in a real task, with FDE engineers completing configuration, evidence recording, controlled rollout, and internal handover.
01 · UNDERSTAND01
Understand the applicable problem first
Use resource detail pages to judge inputs, outputs, boundaries, and non-applicable cases; do not create needs for the sake of tools.
Stay
Problem definition and applicability assessment
02 · REHEARSE02
Practice in a non-sensitive data environment
Run the full process with sample data, recording dependencies, permissions, failure states, and manual confirmation points.
Stay
Practice records and risk checklist
03 · PILOT03
Integrate one real business process
Limit user, data, and action scope; validate quality, latency, cost, and rollback with representative samples.
Stay
Pilot version, evaluation, and stop conditions
04 · HANDOVER04
Enable the business team to take over
Complete the runbook, knowledge updates, version tracking, and review so internal staff can continue maintenance.
Review is about this version, not just a “safe” label.
Source, license, capability claims, static rules, human review, version, and SHA-256 must be visible. For third-party packages without redistribution license, only original source and research conclusions are kept.
Isolate
Do not install, execute, or read user credentials.
Inventory
List files, dependencies, network, processes, and write capabilities.
Review
After rule checks, humans still read the code and licenses.
Clean release
Repackage with fixed version, hash, and known limitations.
Incubate your workflow into a Skill your team can use.
Describe the current task, existing process, data and tools, and the deliverables you want to keep. We can organize it into a teachable, testable, maintainable enterprise capability package.