project-docs-prep
Skill4 starsChanged 2 months agoMITView on GitHub
Use this skill whenever the user wants to prepare or scaffold documentation for a new (or existing) software project before handing it to an AI coding agent — for example when they ask to "set up project docs", "write a project spec", "prepare AGENTS.md", "prepare DESIGN.md", "เตรียมเอกสารโปรเจกต์", "เริ่มโปรเจกต์ใหม่ให้ AI เขียนโค้ด", or describe a project idea and want it turned into proper docs. Also trigger when the user wants a full docs/ folder (numbered specs — project overview, system requirements, tech stack & architecture, system modeling, UX/UI design) plus root-level agent-facing files (AGENTS.md, DESIGN.md, CLAUDE.md, README.md). Trigger even if the user only gives an informal one-line project idea and doesn't name any file explicitly — this skill's job is to turn that idea into the full documentation set. Also use when the user wants to review or upgrade an existing project's docs to be "AI-agent ready".
In this repository58 other files it gives its agents.
- AGENTS.mdAGENTS.md
- skills/project-docs-prep/templates/AGENTS.mdAGENTS.md
- skills/project-docs-prep/templates/CLAUDE.mdCLAUDE.md
- deep-planningSkill
- deep-planningSkill
- deprecatedSkill
- architecture-reviewSkill
- code-reviewSkill
- diagnoseSkill
- tddSkill
- ui-design-engineeringSkill
- ux-ui-design-assessmentSkill
- in-progressSkill
- mcp-tool-managementSkill
- skill-managementSkill
- obsidian-canvasSkill
- obsidian-markdownSkill
- obsidian-notion-bridgeSkill
- obsidian-vault-workflowSkill
- boomz-preferencesSkill
- personal-agent-workflowSkill
- personalSkill
- automation-designSkill
- grill-with-docsSkill
- handoffSkill
- inbox-meeting-triageSkill
- markdown-reportSkill
- prompt-improvementSkill
- claim-citation-checkSkill
- daily-news-reportSkill
- github-skill-researchSkill
- project-discoverySkill
- repo-tourSkill
- research-methodologySkill
- seo-website-evaluatorSkill
- thaiSkill
- thai-addressSkill
- thai-customer-serviceSkill
- thai-date-formatSkill
- thai-festival-cardSkill
- thai-government-formSkill
- thai-id-validateSkill
- thai-invoiceSkill
- thai-pdpaSkill
- thai-resumeSkill
- thai-social-captionSkill
- thai-text-processingSkill
- thai-translateSkill
- backtest-expertSkill
- dividend-value-screenerSkill
- drawdown-circuit-breakerSkill
- exposure-coachSkill
- market-breadth-analyzerSkill
- portfolio-managerSkill
- position-sizerSkill
- tradingSkill
- trader-memory-coreSkill
- uptrend-analyzerSkill
The file
We split this skill into the rules it gives an agent
11 rules. About 0 are common, 2 are distinctive, and 9 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
9
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 28
Read the relevant template from templates/ as your starting structure.
- Distinctive: line 30
Delete any sections that don't apply — do NOT leave empty headings.
- Distinctive: line 31
Add project-specific sections where the template doesn't cover them.
- Very specific: line 40
If given a short idea (e.g.
- Very specific: line 43
Create numbered specs in docs/.
- Very specific: line 46
Use templates/AGENTS.md as base.
- Very specific: line 49
Use templates/DESIGN.md as base.
- Very specific: line 81
No Emoji in
docs/05-ux-ui-design.mdorDESIGN.md, ever: Use Lucide Icons or named SVGs instead. - Very specific: line 82
Token Efficiency: Keep AGENTS.md, DESIGN.md, and docs/ high-density and free of generic fluff.
- Very specific: line 83
No Fabricated Performance Figures: Use > ⚠️ TODO: confirm target NFR for unconfirmed metrics.
- Very specific: line 84
Language Strategy: Keep operational files (AGENTS.md, DESIGN.md, CLAUDE.md) in English for optimal LLM token efficiency.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Project Docs Prep
Turns a short project idea (or an existing incomplete docs folder) into a complete, AI-agent-ready documentation set. Produces two operational layers:
- Spec Layer (
docs/) — describes what to build. Five numbered files:01-project-overview.md02-system-requirements.md03-tech-stack-architecture.md04-system-modeling.md05-ux-ui-design.md
- Operational Layer (repo root) — describes how the agent should work and what design tokens/commands look like:
AGENTS.mdDESIGN.mdCLAUDE.mdREADME.md
These two layers are complementary, not redundant. The spec layer is read once during planning. The operational layer is loaded by the agent every session — keep it concise and omit facts inferable from code.
Templates
This skill ships with skeleton templates in templates/. When generating docs for a new project:
- Read the relevant template from
templates/as your starting structure. - Replace all
{{PLACEHOLDER}}markers with project-specific content. - Delete any sections that don't apply — do NOT leave empty headings.
- Add project-specific sections where the template doesn't cover them.
See references/template-usage-guide.md for detailed instructions on each template.
Workflow
Step 1 — Gather Project Info
If given a short idea (e.g. "Meeting room booking system for 50 users"), do not interrogate field-by-field. Draft reasonable content and mark uncertain items with > ⚠️ TODO:. Only ask clarifying questions when the answer would alter architecture or design direction.
Step 2 — Generate docs/01–05
Create numbered specs in docs/. Use the templates in templates/docs/ as starting structure. Maintain consistent section headings. Fill placeholders with project specifics. Keep descriptions clear and accessible for both human developers and AI agents.
Step 3 — Generate AGENTS.md
Use templates/AGENTS.md as base. Include build, test, and lint commands for the chosen stack, directory layout, and hard constraints. Delete non-applicable template sections to conserve token budget.
Step 4 — Generate DESIGN.md
Use templates/DESIGN.md as base. Create a design specification with:
- YAML front matter containing design tokens (colors, typography, spacing, breakpoints, z-index).
- Markdown body detailing design rationale, accessibility, and component standards.
Hard Rule — NO Emoji in UI-facing files.
docs/05-ux-ui-design.md and DESIGN.md must never contain emoji as UI elements (status markers, buttons, icons, flags). Always specify an icon library (e.g. Lucide Icons) or named inline SVGs, referencing icons by name (e.g. CheckCircle icon or <i data-lucide="check-circle"></i>).
Step 5 — Generate CLAUDE.md and README.md
CLAUDE.md: thin pointer file linking toAGENTS.mdandDESIGN.mdplus Claude Code notes. Usetemplates/CLAUDE.md.README.md: concise human-facing summary condensed from01-project-overview.md. Usetemplates/README.md.
Step 6 — Assemble and Deliver
Deliver the full file tree:
/
├── README.md
├── AGENTS.md
├── CLAUDE.md
├── DESIGN.md
└── docs/
├── 01-project-overview.md
├── 02-system-requirements.md
├── 03-tech-stack-architecture.md
├── 04-system-modeling.md
└── 05-ux-ui-design.mdGuardrails
- No Emoji in
docs/05-ux-ui-design.mdorDESIGN.md, ever. Use Lucide Icons or named SVGs instead. - Token Efficiency: Keep
AGENTS.md,DESIGN.md, anddocs/high-density and free of generic fluff. - No Fabricated Performance Figures: Use
> ⚠️ TODO: confirm target NFRfor unconfirmed metrics. - Language Strategy: Keep operational files (
AGENTS.md,DESIGN.md,CLAUDE.md) in English for optimal LLM token efficiency.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

