Best for
- Use when the user wants to set up docs, bootstrap documentation, initialize project docs, scaffold a docs/ folder, or create docs from scratch for a new or undocumented project.
mgiovani/cc-arsenal/skills/docs-init/SKILL.md
Bootstraps a documentation structure (architecture, onboarding, data-model, deployment, security, contributing, and a first ADR) for a project that has little or no docs/ directory, exploring the codebase and populating templates only with content evidenced in the code. Use when the user wants to set up docs, bootstrap documentation, initialize project docs, scaffold a docs/ folder, or create docs from scratch for a new or undocumented project. Not for refreshing or syncing docs that already exi
Decision brief
Bootstrap a docs/ structure for a project with little or no existing documentation. Only generate what the codebase actually evidences.
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/mgiovani/cc-arsenal --skill "skills/docs-init"Inspect the Agent Skill "docs-init" from https://github.com/mgiovani/cc-arsenal/blob/410f2649860bb1892ee8c66721f57462eeefcf13/skills/docs-init/SKILL.md at commit 410f2649860bb1892ee8c66721f57462eeefcf13. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
Find: source directories with actual code, package manager files (package.json, pyproject.toml, go.mod, Cargo.toml, ...), database/ORM files, infrastructure configs (Docker, k8s, Terraform), and any existing docs/. See Detection Commands below for the exact patterns.
Review the “Usage Examples” section in the pinned source before continuing.
Every claim in generated docs must trace to something read or grepped in this run:
Find: source directories with actual code, package manager files (package.json, pyproject.toml, go.mod, Cargo.toml, ...), database/ORM files, infrastructure configs (Docker, k8s, Terraform), and any existing docs/. See Detection Commands below for the exact patterns.
From the exploration, determine: language/framework stack, project type (web app, CLI, library, service), whether a database/ORM is present, and whether infrastructure/deployment configs exist.
Permission review
The documentation asks the agent to read local files, directories, or repositories.
Verify every finding before using it: read the package manifest, read the model file, confirm a directory has real files inside it, not just an empty folder.The documentation asks the agent to read local files, directories, or repositories.
Scan `docs/`. For any target file that already exists, do not overwrite it: list it under "skipped" and ask the user before touching it. This skill is safe to rerun: by default it only fills gaps.The documentation asks the agent to create, modify, or delete local files.
Create `docs/` (and `docs/adr/`, `docs/rfc/` if needed). Write each file that isn't being skipped.Evidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 84/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 6 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Bootstrap a docs/ structure for a project with little or no existing documentation. Only generate what the codebase actually evidences.
Every claim in generated docs must trace to something read or grepped in this run:
ls/find/grep, never estimate.Find: source directories with actual code, package manager files (package.json, pyproject.toml, go.mod, Cargo.toml, ...), database/ORM files, infrastructure configs (Docker, k8s, Terraform), and any existing docs/. See Detection Commands below for the exact patterns.
If a Task/subagent tool is available, delegate this to an Explore agent with that scope. Otherwise run the same grep/find commands inline and Read each hit: the result must be the same either way.
Verify every finding before using it: read the package manifest, read the model file, confirm a directory has real files inside it, not just an empty folder.
From the exploration, determine: language/framework stack, project type (web app, CLI, library, service), whether a database/ORM is present, and whether infrastructure/deployment configs exist.
docs/architecture.md, docs/onboarding.md, docs/adr/0001-record-architecture-decisions.md (Nygard-format meta-ADR, generate inline, no template file)docs/data-model.mddocs/deployment.md, docs/security.mdgit log, an open-source license, no existing CONTRIBUTING): docs/contributing.md, docs/rfc/ directoryDon't generate a doc type with no supporting evidence: an empty data-model.md for a stateless CLI is worse than no file at all.
Scan docs/. For any target file that already exists, do not overwrite it: list it under "skipped" and ask the user before touching it. This skill is safe to rerun: by default it only fills gaps.
Templates live in assets/templates/ (see reference table below). For each one you're using:
grep -oE '\{\{[A-Z_0-9]+\}\}' assets/templates/<name>.md | sort -u{{TOKEN}} in the output.\{\{[A-Z_0-9]+\}\} again. Zero matches. If any remain, resolve or delete them before moving on.Worked example (a FastAPI + PostgreSQL service):
$ grep -oE '\{\{[A-Z_0-9]+\}\}' assets/templates/architecture.md | sort -u
{{COMPONENT_DEPENDENCIES}}
{{COMPONENT_DESCRIPTION}}
{{COMPONENT_NAME}}
{{DATA_FLOW}}
{{DATE}}
{{DEPLOYMENT_SUMMARY}}
...
Map each to a verified finding: {{TECHNOLOGY_STACK}} becomes "Python 3.12, FastAPI 0.115, PostgreSQL 16 via SQLAlchemy", read from pyproject.toml and the model files, not assumed. If security.md's Compliance section has no GDPR/HIPAA evidence in the codebase (no consent flow, no PHI handling), delete that whole section rather than fill it with a guess.
Create docs/ (and docs/adr/, docs/rfc/ if needed). Write each file that isn't being skipped.
List what was created, what was skipped (already existed), and next steps.
| Document | Template | Generated when |
|---|---|---|
| Architecture | architecture.md | always |
| Onboarding | onboarding.md | always |
| First ADR | inline (Nygard format) | always |
| Data Model | data-model.md | database/ORM detected |
| Deployment | deployment.md | deployment config detected |
| Security | security.md | deployment config detected |
| Contributing | contributing.md | collaborative project |
Run these directly (or hand them to the Explore agent from step 1):
# Language/framework
find . -name "package.json" -o -name "pyproject.toml" -o -name "go.mod" -o -name "Cargo.toml" | head -5
# Database/ORM
find . -name "*models.py" -o -name "*schema.prisma" -o -name "*entity.ts" | head -5
# Infrastructure
find . -name "Dockerfile" -o -name "docker-compose.yml" -o -name "*.k8s.yaml" | head -5
# Project name and description
basename "$(git rev-parse --show-toplevel 2>/dev/null || pwd)"
head -20 README.md 2>/dev/null
docs-init
docs-init for Python FastAPI microservice
docs-init for Next.js SaaS application
Documentation Initialization Complete
Created:
docs/architecture.md - System architecture overview
docs/onboarding.md - Developer onboarding guide
docs/adr/0001-record-architecture-decisions.md - Meta-ADR
docs/data-model.md - Database schema (SQLAlchemy detected)
docs/deployment.md - Deployment guide (Docker detected)
Skipped (already exists):
docs/contributing.md
Next steps:
1. Review and customize the generated docs
2. docs-diagram er / docs-diagram arch for standalone diagrams
3. docs-adr "Decision Title" for future ADRs
Alternatives
ruvnet/ruflo
Agent skill for workflow-automation - invoke with $agent-workflow-automation
daymade/claude-code-skills
Use it for deployment and documentation tasks; the detail page covers purpose, installation, and practical steps.
mgiovani/cc-arsenal
Read-only audit of documentation against the current codebase, flags stale docs, missing sections, broken links, and hallucinated claims (wrong file references, wrong counts, diagram entities that don't exist in code). Use for "check the docs", "audit documentation", "are the docs stale", "find hallucinations in docs", "docs health check", "does this doc still match the code", or before onboarding/release. Reports only, never edits files, for actually fixing or regenerating docs use docs-update
mgiovani/cc-arsenal
Refresh existing docs (architecture, onboarding, data-model, deployment, security, contributing) so they match the current codebase, verifying every claim against real code instead of guessing. Use when the user says docs are stale, asks to sync docs with recent code changes, update a specific doc file, or update a whole category (core/data/infrastructure/development) after a refactor or schema change. Not for creating docs that don't exist yet (use docs-init) or scoring/auditing doc health with