scan
Scans the codebase to generate project-doc.md and AGENTS.md. Use when bootstrapping a new agent-driven repo, refreshing project documentation after architectural changes, or running a delta scan to detect drift. Runs a full scan on first use and a smart delta scan on subsequent runs. Uses understand-anything + context-mode when available, falls back to native tools otherwise. Only updates AGENTS.md on detected architectural changes with human confirmation.
What this skill does
# Codebase Scanner
You are a technical analyst. Your job is to scan the project codebase and produce accurate, project-specific documentation used by all downstream agents.
## Step 1: Check Optional Plugin Dependencies
Check whether the two optional enhancement plugins are available:
```
understand-anything → /plugin list | grep understand-anything
context-mode → /plugin list | grep context-mode
```
These plugins are **optional**. They improve scan quality but are not required:
- **understand-anything** (Lum1104/Understand-Anything) — provides deeper semantic code analysis
- **context-mode** (mksglu/context-mode) — routes large outputs through a sandbox to protect the context window
If both are present, use them in Steps 3–4 as described below. If either or both are missing, proceed with the **native fallback** approach: use `find`, `grep`, `cat`, and `git` commands directly, routing large outputs through `ctx_execute` / `ctx_execute_file` if context-mode is available, otherwise summarise inline.
> **Note:** To install the optional plugins manually:
> ```
> /plugin marketplace add Lum1104/Understand-Anything && /plugin install understand-anything
> /plugin marketplace add mksglu/context-mode && /plugin install context-mode@context-mode
> ```
## Step 2: Determine Scan Mode
Check if `.claude/pipeline/project-doc.md` exists.
- **Does not exist** → FULL SCAN (first run)
- **Exists** → DELTA SCAN
## Step 3A: Full Scan
Use `understand-anything` to analyse the entire codebase. If **context-mode** is available (verified in Step 1), route ALL output through its tools (`ctx_batch_execute` / `ctx_execute_file`) — never dump raw file contents into the main context window. If context-mode is not available, summarise each file's findings inline and avoid printing raw file contents.
Produce `.claude/pipeline/project-doc.md` using the following structure (based on the architecture-blueprint-generator pattern):
```md
# Project Documentation
> Generated: [timestamp] | Mode: FULL
## Tech Stack
- Runtime: [e.g. Node.js 20, Python 3.11]
- Language: [e.g. TypeScript, Python]
- Framework: [e.g. Next.js 14 App Router, FastAPI]
- Database: [e.g. PostgreSQL via Prisma]
- Styling: [e.g. Tailwind CSS]
- State Management: [e.g. Zustand, Redux]
## Dependencies
[Key libraries with versions, grouped by: core / dev / testing]
## Architecture Pattern
[e.g. Feature-based, Layered MVC, Clean Architecture]
[Describe how the project is structured and why]
## Folder Structure
[Top-level directory map with purpose of each folder]
## Code Style Conventions
[Naming patterns, file naming, import ordering, export patterns]
[Inferred from actual code — not guessed]
## Modularity Practices
[How concerns are separated, shared module locations, service patterns]
## Data Architecture
[Entity relationships, data access patterns, ORM usage]
## Cross-Cutting Concerns
[Auth/authz approach, error handling patterns, logging, validation]
## Service Communication
[REST / GraphQL / event-driven — document what actually exists]
## Test Coverage
- Overall coverage: [X%]
- Testing framework: [e.g. Jest, Vitest, Pytest]
- Key untested areas: [list]
- Test patterns used: [unit / integration / e2e]
## Entry Points
[Main files, key config files, environment setup]
## Changed Files
[Only present in delta scans — list of files re-scanned]
## Last Scanned
[ISO timestamp]
```
After writing `project-doc.md`, proceed to **Step 4** to generate `AGENTS.md`.
## Step 3B: Delta Scan
1. Run `git diff HEAD~1 --name-only` to get changed files
2. If no changed files, report "No changes detected — project-doc.md is current" and exit
3. Use `understand-anything` to re-analyse only the changed files; route output through `ctx_execute_file` if context-mode is available, otherwise summarise inline
4. Patch only the affected sections of `.claude/pipeline/project-doc.md`
5. Update the `Last Scanned` and `Changed Files` fields
6. Proceed to **Step 4B** (architectural change detection)
## Step 4A: Generate AGENTS.md (First Run Only)
Write `AGENTS.md` to the repo root. This is NOT a copy of `project-doc.md` — it is rewritten as agent instructions, tailored to this specific project. Every agent reads this file first.
Structure:
```md
# AGENTS.md — [Project Name]
> Auto-generated by the dev pipeline scanner. Do not edit manually.
> Last updated: [timestamp]
> ⚠️ To update this file, architectural changes must be detected by the scanner and confirmed by a human.
## How to Read This File
Every agent in this pipeline reads this file before doing any work.
It defines the rules, patterns, and guardrails specific to this project.
## Stack Context
[One-line summary: e.g. "Next.js 14 App Router + Prisma + PostgreSQL + Tailwind + Vitest"]
## Code Style Rules
[Written as DO/DON'T instructions inferred from actual codebase patterns]
Example:
- DO use named exports. Default exports are not used in this project.
- DON'T add business logic to API route handlers — delegate to /lib/services/
- DO use [naming convention] for [file type]
## Architecture Guardrails
[Rules derived from the actual architecture — not generic advice]
Example:
- This project uses the Repository pattern. Never query the DB directly from components.
- All API responses must go through the [ResponseWrapper] utility.
## Testing Requirements
[Coverage stat + specific rules for this project]
Example:
- Current coverage: 67%. All new code must include unit tests.
- QA agent: flag any feature with <80% coverage on new code.
- Integration tests use [real DB / mock DB] — do not change this.
## Modularity Conventions
[Specific rules about where code goes]
Example:
- Shared UI components → /components/ui
- Business logic → /lib/services/[domain]/
- Types → /types/[domain].ts
## Security Rules (All Agents)
- Never hardcode secrets, tokens, or credentials
- Use environment variables for all sensitive config
- Flag any auth-adjacent code changes immediately
## Agent-Specific Instructions
### Orchestrator
[Project-specific questions to always ask — e.g. "Does this touch the payment flow?"]
### Architect
[Known complexity areas, performance constraints, patterns to prefer]
[e.g. "This project has a known N+1 issue in /lib/services/orders — avoid adding more eager loading"]
### Developer
[Specific libraries to use, anti-patterns banned in this codebase]
[e.g. "Use dayjs — moment is banned", "Use React Query for all data fetching — no raw fetch()"]
### PR Reviewer
[What counts as 🔴 Critical vs 🟡 Should Fix in this project]
[e.g. "Any change to /lib/auth/ is automatically 🔴 Critical — requires human approval"]
### QA Agent
[Known edge cases for this domain, critical user paths to always test]
[e.g. "Always test empty state, loading state, and error state for every UI feature"]
```
If the project is MERN stack (MongoDB + Express + React + Node.js — detected from package.json / requirements), append a `### MERN Stack Notes` section to AGENTS.md covering: use Mongoose middleware over raw queries, handle async errors in Express with a central error handler, avoid storing JWT tokens in localStorage (use httpOnly cookies), and never expose Mongoose error objects directly in API responses.
## Step 4B: Architectural Change Detection (Delta Runs Only)
After patching `project-doc.md`, compare the new version against the previous. Check for:
- New framework or major library added
- New architectural directory pattern created (e.g. new `/lib/hooks/`, `/services/`)
- Major dependency swap (e.g. axios → fetch, moment → dayjs)
- New auth or session handling pattern
If any detected, show:
```
⚠️ Architectural change detected in delta scan:
[List specific changes found]
AGENTS.md may need updating. Review and confirm:
[y] Update AGENTS.md — patch affected sections only
[n] Skip — this is not an architectural change
```
Only on `[y]` confirmation: patch the relevant sections of `AGENTS.md`. Never rewrite the full file.
## Step 5: ReportRelated in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.