project-bootstrap
Skill1 starsChanged 5 months agoMITView on GitHub
Bootstrap a new project's knowledge layer by interviewing the user across a fixed taxonomy of concerns, then generating a CONTEXT.md index and separate detail files. Use this skill whenever the user wants to set up a new project, bootstrap project context, create project documentation for LLM consumption, initialize a knowledge layer, or says "bootstrap this project", "set up project context", "new project setup". Also trigger when the user has a new codebase and wants to document its architecture, conventions, and decisions for future sessions.
40 other projects use a version of this.
Adopted by
Most recently taken up by
- ice-lfernandes/claude-spring-architecttheir own version, first seen Nov 7, 2026
- nerviz-ai/nerviztheir own version, first seen Nov 7, 2026
- Cure-Consulting-Group/ProductEngineeringSkillstheir own version, first seen Nov 4, 2026
- NoobyGains/godmodetheir own version, first seen Nov 1, 2026
- jerseycheese/agent-skillstheir own version, first seen Oct 28, 2026
- alfonsusenrico/pakemtheir own version, first seen Oct 25, 2026
Used with
Projects with it also use delivery-planning, diagnose and 4 more.
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Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
lzx-BillSkilldelivery-planning
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MicrosoftSkillapi-design
Guide for designing and documenting RESTful APIs. Use when asked to design an API, create endpoints, or document an API.
Also in 3 projects that use this
GoogleSkilltdd
Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
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GoogleSkillgrill-me
A relentless interview to sharpen a plan or design.
Also in 3 projects that use this
- +1 more from google
Other versions40 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 40
- NoobyGains/godmode★ 118same name
- ice-lfernandes/claude-spring-architect★ 11same name
- nerviz-ai/nerviz★ 11same name
- Mozurok/fhorja.dev★ 10same name
- m16khb-org/issueops★ 6same name
- Eydenn/loomy★ 4same name
- fortmort/jeltz★ 4same name
- jerseycheese/agent-skills★ 4same name
- Cure-Consulting-Group/ProductEngineeringSkills★ 3same name
- hams-ollo/zen-agent-skills★ 2same name
30 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository2 other files it gives its agents.
- export-projectSkill
- skill-inspectorSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
17 rules. 0 are common, 13 are distinctive, and 4 are very specific to this project.
0
Common
Most of the 32 edited versions we read keep these.
13
Distinctive
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 32
Not every project needs every file.
- Distinctive: line 80
Write detail files in concrete, factual language.
- Very specific: line 109
If a question can be answered by exploring an existing codebase (checking package.json, reading folder structure, inspecting config files), …
- Distinctive: line 127
If the user's answer is ambiguous, follow up on that specific point before advancing.
- Distinctive: line 128
If the user says "skip" or "not applicable", drop the domain — don't generate a file for it.
- Distinctive: line 129
If the user says "default" or "you decide", pick a reasonable default and state it clearly.
- Distinctive: line 131
Before generating, present a summary of all decisions and let the user confirm or amend.
- Distinctive: line 135
If a codebase already exists, read it before starting the interview:
- Very specific: line 137
Check for package.json, Cargo.toml, go.mod, pyproject.toml, etc.
- Distinctive: line 139
Check for .eslintrc, prettier, .editorconfig — infer conventions.
- Very specific: line 140
Check for CI configs (.github/workflows, Jenkinsfile, etc.) — infer deployment.
- Distinctive: line 141
Check for test directories and config — infer testing approach.
- Distinctive: line 147
After the interview is confirmed:
- Very specific: line 149
Create docs/ directory and docs/adr/ if any ADRs are needed.
- Distinctive: line 157
If the user wants to change a decision after generation:
- Distinctive: line 160
Update CONTEXT.md's table rows only if a file was added or removed.
- Distinctive: line 161
Do not regenerate unaffected files.
“Common” is measured: kept by at least 6 in 10 of the 32 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Project Bootstrap
Generate a project's knowledge layer through a structured interview, producing a stable CONTEXT.md index and separate detail files optimized for both human reading and LLM context caching.
Why this structure matters
LLM context caching works on prefix stability — content that doesn't change stays cached. A single monolith file invalidates the entire cache on any edit. By splitting into a small, stable index (CONTEXT.md) and separate detail files, only the changed file costs tokens on re-read. The index stays in cache across almost every session.
Output structure
project-root/
├── CONTEXT.md ← stable index, rarely changes (~50-80 lines)
└── docs/
├── stack.md ← languages, frameworks, runtimes
├── architecture.md ← boundaries, data flow, state
├── data.md ← storage, schemas, migrations, caching
├── conventions.md ← naming, file structure, code style, commits, branching
├── testing.md ← strategy, frameworks, coverage
├── deployment.md ← environments, CI/CD, infra
├── team-workflow.md ← PR process, review norms, ownership
├── constraints.md ← performance, compliance, accessibility, platform
└── adr/
└── 0001-<title>.md ← one file per architectural decisionNot every project needs every file. If a domain has no decisions yet, skip the file entirely — don't generate stubs. CONTEXT.md only links to files that exist.
CONTEXT.md format
# <Project Name>
<One paragraph: what this is, who it's for, what problem it solves.>
## Quick reference
| Concern | Detail |
|---------|--------|
| Stack | [docs/stack.md](docs/stack.md) |
| Architecture | [docs/architecture.md](docs/architecture.md) |
| ... | ... |
## Decisions
| ID | Date | Decision | Detail |
|----|------|----------|--------|
| ADR-0001 | YYYY-MM-DD | <short title> | [docs/adr/0001-<title>.md](docs/adr/0001-<title>.md) |
## Open items
- <thing explicitly not yet decided, with enough context to revisit later>The quick reference table only includes rows for files that were generated. Keep this file under 80 lines. It is an index, not a summary — don't duplicate content from detail files.
Detail file format
Each detail file follows the same pattern:
# <Concern>
<2-3 sentence summary of the current state.>
## Decisions
- <Decision>: <rationale in one sentence>
## Specifics
<The actual content — concrete, not aspirational. What IS, not what SHOULD BE.>Write detail files in concrete, factual language. "We use PostgreSQL 16 on RDS" not "A relational database should be considered." If something is undecided, it belongs in CONTEXT.md's open items, not in a detail file as a hedge.
ADR format
# ADR-<NNNN>: <Title>
**Date**: YYYY-MM-DD
**Status**: accepted | proposed | superseded by ADR-NNNN
## Context
<What forced this decision.>
## Decision
<What was decided.>
## Consequences
<What follows from this — both positive and negative.>Generate an ADR for any decision where the rationale is non-obvious or where the team might later ask "why did we do it this way?" Not every decision needs an ADR — only the ones worth explaining.
Interview process
Walk through the following domains in order. Ask one question at a time. For each domain, provide a recommended answer based on what you've learned so far — the user can accept, modify, or reject.
If a question can be answered by exploring an existing codebase (checking package.json, reading folder structure, inspecting config files), do that instead of asking.
Domain sequence
- Project identity — name, purpose, problem it solves, target users
- Stack — languages, frameworks, runtimes, package managers, key dependencies
- Architecture — monolith/microservices, module boundaries, data flow, state management
- Data — storage engines, schema approach, migrations, caching
- Conventions — naming, file/folder structure, code style tools, commit format, branching model
- Testing — strategy (unit/integration/e2e), frameworks, coverage targets
- Deployment — environments, CI/CD, hosting, infra-as-code
- Team workflow — PR process, review expectations, ownership model
- Constraints — performance budgets, compliance requirements, accessibility, platform/browser support
- Open decisions — things explicitly deferred, with context on why and when to revisit
Interview rules
- One question per turn. Wait for the answer before moving on.
- If the user's answer is ambiguous, follow up on that specific point before advancing.
- If the user says "skip" or "not applicable", drop the domain — don't generate a file for it.
- If the user says "default" or "you decide", pick a reasonable default and state it clearly. The user can override.
- Track which domains are complete. When all 10 are resolved (answered or skipped), move to generation.
- Before generating, present a summary of all decisions and let the user confirm or amend.
Codebase inference
If a codebase already exists, read it before starting the interview:
- Check for package.json, Cargo.toml, go.mod, pyproject.toml, etc. — infer stack.
- Scan folder structure — infer architecture patterns.
- Check for .eslintrc, prettier, .editorconfig — infer conventions.
- Check for CI configs (.github/workflows, Jenkinsfile, etc.) — infer deployment.
- Check for test directories and config — infer testing approach.
Present inferences as "Here's what I found — confirm or correct" rather than re-asking what's already visible.
Generation phase
After the interview is confirmed:
- Create
docs/directory anddocs/adr/if any ADRs are needed. - Generate each detail file for domains that were not skipped.
- Generate ADRs for decisions with non-obvious rationale.
- Generate CONTEXT.md last — it references the files above.
- Present all files for review.
Regeneration rules
If the user wants to change a decision after generation:
- Regenerate only the affected detail file(s).
- Update CONTEXT.md's table rows only if a file was added or removed.
- Do not regenerate unaffected files. State which files were changed and why.
This keeps token cost proportional to the change, not the project size.
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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.

