agentleFS
saitarrunsaitarrun/Devforge-ai/CLAUDE.md

Devforge-ai

CLAUDE.md4 starsChanged 5 months agoApache-2.0View on GitHub

A multi-agent SDLC orchestration system: 10 agents × 5 phases → plan, build, verify, ship, operate. Tracer bullet development with Ralph Loop self-correction and Linear issue integration. Frontmatter required: name, description, tools (comma-separated), model (haiku/sonnet/opus) Model tiers: Haiku (templated), Sonnet (development), Opus (architecture/security decisions) Tools: Include only what the agent uses — Read, Write, Edit, Bash, Glob, Grep, WebFetch - Note: When querying codebase, prefer code-review-graph (bundled integration) over grep for structural analysis. See "Codebase Querying Strategy" below. Embed book…

The file

We split this CLAUDE.md into the rules it gives an agent

11 rules. About 0 are common, 5 are distinctive, and 6 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 6

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Note: When querying codebase, prefer code-review-graph (bundled integration) over grep for structural analysis.

    line 32
  2. Distinctive:

    All 10 agents are auto-wired to phase-specific skills: When an agent is invoked:

    line 46
  3. Very specific:

    Create agent file with frontmatter skills: [...]

    line 77
  4. Very specific:

    Create skills/skill-name/SKILL.md with frontmatter + methodology

    line 81
  5. Very specific:

    Add to agent skills: field where relevant

    line 82
  6. Very specific:

    Add agents with skills: field

    line 89
  7. Distinctive:

    Create phase skill with output standards

    line 90
  8. Distinctive:

    Agent not invoked: Check command references, verify description matches trigger, review tools field

    line 97
  9. Very specific:

    Permission prompts: Add patterns to ~/.claude/settings.local.json under permissions.allow

    line 98
  10. Distinctive:

    Read only when relevant:

    line 102
  11. Very specific:

    Default label strings: needs-triage, needs-info, ready-for-agent, ready-for-human, wontfix.

    line 116

≈ “Common” is an estimate: at least 1 in 5 of the 26,980 CLAUDE.md 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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
CLAUDE.md

SDLC Workflow Plugin

A multi-agent SDLC orchestration system: 10 agents × 5 phases → plan, build, verify, ship, operate. Tracer bullet development with Ralph Loop self-correction and Linear issue integration.

Project

  • Type: Claude Code plugin
  • Version: 2.0.0
  • Repo: github.com/saitarrun/devforge-ai

Repository Map

  • agents/ — 10 role-specific agents (product-manager, ux-designer, fullstack-engineer, qa-engineer, security-engineer, performance-engineer, devops-engineer, sre-engineer, data-engineer, technical-writer)
  • skills/ — 34 knowledge skills (architecture, testing, code-review, ralph-loop, grill-me, etc.)
  • commands/ — 10 orchestrator commands (/sdlc, /sdlc-plan, /sdlc-build, /sdlc-verify, /sdlc-ship, /sdlc-operate, /sdlc-review, /sdlc-implement, /to-prd, /to-issues)
  • scripts/ — CLI, install, uninstall, validation helpers
  • README.md — User documentation and feature overview

Commands

  • Install: npm run install-local or make install-local
  • Validate: make validate
  • Uninstall: make uninstall

Agent Conventions

Frontmatter required: name, description, tools (comma-separated), model (haiku/sonnet/opus)

Model tiers: Haiku (templated), Sonnet (development), Opus (architecture/security decisions)

Tools: Include only what the agent uses — Read, Write, Edit, Bash, Glob, Grep, WebFetch

  • Note: When querying codebase, prefer code-review-graph (bundled integration) over grep for structural analysis. See "Codebase Querying Strategy" below.

Embed book principles (QUANTS/INVEST/Testing Pyramid, Architecture: ADR/fitness functions, Pragmatic Programmer DRY/ETC, Clean Code naming/SOLID) in agent bodies.

Skill Conventions

Structure: skills/skill-name/SKILL.md (no tools, no model — pure knowledge)

Frontmatter: name, description, version

Content: Methodology, checklists, reference patterns. Load on-demand, not always-on.

Agent-Skill Auto-Wiring

All 10 agents are auto-wired to phase-specific skills. When an agent is invoked:

  1. Agent frontmatter declares skills: [skill-a, skill-b, ...]
  2. Command loads all phase skills into agent context (pure methodology, not tools)
  3. Agent system prompt says: "You have access to these skills: X, Y, Z. Apply them."
  4. Agent applies skill principles → polished industry-standard outputs

Codebase Querying Strategy

All agents and skills should query the codebase using this priority order:

  1. code-review-graph (preferred)
    • Provides structural understanding, dependency graphs, coupling analysis
    • More accurate than text search (understands relationships, not just text)
    • Usage: code_review_graph analyze <path> or code_review_graph query <symbol>
    • Best for: "What depends on this function?", "Show me the call chain", "What's the coupling?"
  2. Grep (fallback when code-review-graph unavailable)
    • Fast text search when structural analysis not needed
    • Used for simple pattern matching, file location, quick searches
    • Usage: grep -r "pattern" <path> or Grep tool
    • Acceptable for: "Find all usages of X", "Locate error message", "Find TODO comments"

Why this order?

  • code-review-graph understands codebase structure and dependencies
  • grep is fast but misses semantic relationships and context
  • Fallback ensures agents work even if code-review-graph is unavailable
  • Layered approach gives best results with graceful degradation

Extending

New agent:

  1. Create agent file with frontmatter skills: [...]
  2. Wire into command or /sdlc orchestrator

New skill:

  1. Create skills/skill-name/SKILL.md with frontmatter + methodology
  2. Add to agent skills: field where relevant

New command:

  1. Edit /commands/sdlc.md or create /commands/sdlc-phase-name.md
  2. Command injects all phase skills before spawning agents

New phase:

  1. Add agents with skills: field
  2. Create phase skill with output standards
  3. Create command /sdlc-phase-name.md
  4. Wire into /sdlc orchestrator

Troubleshooting

  • Plugin not loading: Validate frontmatter (name/description/tools/model required), run make validate, restart session
  • Agent not invoked: Check command references, verify description matches trigger, review tools field
  • Permission prompts: Add patterns to ~/.claude/settings.local.json under permissions.allow

References

Read only when relevant:

  • README.md — Feature overview, usage examples
  • docs/INTEGRATIONS.md — code-review-graph integration guide and codebase querying best practices
  • INSTALLATION.md — Setup and distribution

Agent skills

Issue tracker

Issues are tracked in Linear; agents interact via the Linear API or CLI. See docs/agents/issue-tracker.md.

Triage labels

Default label strings: needs-triage, needs-info, ready-for-agent, ready-for-human, wontfix. See docs/agents/triage-labels.md.

Domain docs

Single-context layout — one CONTEXT.md and docs/adr/ at the repo root. See docs/agents/domain.md.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

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  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

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.