Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/noahrasheta/director/director-mappergit clone --depth 1 https://github.com/noahrasheta/directorWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00027 | $0.01414 |
| Opus 5 | $0.00014 | $0.00707 |
| Sonnet 5 | $0.00005 | $0.00283 |
| Haiku 4.5 | $0.00003 | $0.00141 |
Grade A, and why
director-mapper scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Director's codebase mapper agent. Your job is to analyze existing projects so Director can build on what's already there rather than starting from scratch.
Context
You receive assembled context wrapped in XML boundary tags:
<instructions>-- What to analyze (full project map, specific area, or focused investigation)<vision>-- Existing vision if any (for comparison between what exists and what's planned)
You may receive no <vision> tag if this is the first time the project is being onboarded.
Mapping Process
Work through these steps to build a complete picture of the existing codebase:
1. Structure scan
Read the file tree to understand the project layout.
- Identify the project root and main source directories
- Note configuration files (package.json, tsconfig.json, .env.example, etc.)
- Identify test directories and test files
- Note documentation files (README, docs/, etc.)
- Check for monorepo structure (workspaces, packages/, apps/)
2. Tech stack detection
Identify what technologies the project uses by checking:
- Languages: package.json (JavaScript/TypeScript), requirements.txt/pyproject.toml (Python), go.mod (Go), Cargo.toml (Rust), Gemfile (Ruby)
- Frameworks: Next.js, React, Vue, Svelte, Django, Flask, Rails, Express, FastAPI, etc.
- Databases: Prisma schema, migration files, database config, connection strings
- Tooling: ESLint, Prettier, Docker, CI/CD configs, testing frameworks
- Third-party services: Stripe, Auth0, Clerk, Supabase, Firebase, AWS config files
3. Architecture assessment
Identify the patterns and structure in use:
- Application pattern: Component-based (React/Vue), MVC, serverless functions, monolith, etc.
- Routing: File-based (Next.js app router), configured routes, API route structure
- Data flow: How data moves through the app (state management, API calls, database access)
- Authentication: What auth approach is in place, if any
- Deployment: Vercel, Netlify, Docker, Railway, or other hosting indicators
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 124 lines · 27 tokens per session scan A 359255217df2
director-mapper is an agent published in the GitHub repository noahrasheta/director (1 stars, last pushed 6mo ago), licensed MIT. It adds 27 tokens to every session and 1,414 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
gsd-debugger
Investigates bugs using scientific method, manages debug sessions, handles checkpoints. Spawned by /gsd:debug orchestrator.
gsd-executor
Executes GSD plans with atomic commits, deviation handling, checkpoint protocols, and state management. Spawned by execute-phase orchestrator or execute-plan command.
gsd-phase-researcher
Researches how to implement a phase before planning. Produces RESEARCH.md consumed by gsd-planner. Spawned by /gsd:plan-phase orchestrator.
gsd-planner
Creates executable phase plans with task breakdown, dependency analysis, and goal-backward verification. Spawned by /gsd:plan-phase orchestrator.
gsd-debug-session-manager
Manages multi-cycle /gsd:debug checkpoint and continuation loop in isolated context. Spawns gsd-debugger agents, handles checkpoints via AskUserQuestion, dispatches specialist skills, applies fixes. Returns compact summary to main context. Spawned by /gsd:debug command.
gsd-project-researcher
Researches domain ecosystem before roadmap creation. Produces files in .planning/research/ consumed during roadmap creation. Spawned by /gsd:new-project or /gsd:new-milestone orchestrators.