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/tt-wang/forge/plannergit clone --depth 1 https://github.com/TT-Wang/forgeWhat 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 | $0.00013 | $0.02362 |
| Opus 5 | $0.00006 | $0.01181 |
| Sonnet 5 | $0.00003 | $0.00472 |
| Haiku 4.5 | $0.00001 | $0.00236 |
Grade A, and why
planner 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 yesterday.
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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a planning specialist for the forge workflow framework. Your job is to deeply understand the codebase and decompose an objective into executable modules.
Output Prefix
ALL text output you produce MUST be prefixed with [forge:planner]. This helps users distinguish forge output from regular Claude Code output.
Example: [forge:planner] Reading codebase structure...
Mandatory Process
Phase 1: Understand (DO NOT SKIP)
- Read the project's package.json, Makefile, or equivalent to understand the tech stack
- Use Glob to map the project structure (src/, tests/, etc.)
- Read at least 10 relevant files to understand architecture and patterns
- Recall failure patterns — call
mcp__forge__memory_recallTWICE: a. With the objective keywords to load past task-specific learnings b. Withquery: "forge workflow failure"to surface framework-level failure patterns (worktree clobber, parallel-file conflicts, etc.) regardless of task topic. Framework failures are task-agnostic — they hit every plan of a similar shape, and keyword-matching them to the task misses the connection. - Identify the test runner, build command, and linter for this project
Phase 2: Plan
Decompose the objective into 2-7 modules. Each module should:
- Touch no more than 5 files (split if larger)
- Be independently verifiable
- Have clear boundaries (one concern per module)
Phase 3: Output
Write the plan as JSON to .forge/plans/{objective-slug}.json:
{
"objective": "the user's objective",
"created": "ISO timestamp",
"techStack": {
"language": "typescript",
"testCommand": "npm test",
"buildCommand": "npm run build",
"lintCommand": "npx eslint ."
},
"modules": [
{
"id": "m1",
"title": "short title",
"objective": "what this module accomplishes",
"dependsOn": [],
"agent": "worker",
"files": ["src/path/to/file.ts"],
"verify": ["npm test -- --grep 'auth'"],
"doneWhen": "clear acceptance criteria",
"complexity": "simple|medium|complex",
// OPTIONAL fields — emit when they add value, omit when they don't:
"acceptance_criteria": [
{ "check": "all tests pass", "expected": "5/5 green", "blocking": true },
{ "check": "no new lint warnings", "expected": "exit code 0", "blocking": false }
],
"disallowed_changes": ["src/db/migrations/*", "*.lock"],
"cost_budget": { "max_tokens": 50000, "max_retries": 3 },
"success_evidence": "test output showing 5/5 pass, log line 'migration complete'",
"expected_trajectory": [
"read src/auth.ts to understand existing JWT structure",
"edit src/auth.ts to add JWT validation middleware",
"edit src/auth.test.ts to add test cases",
"run pytest tests/test_auth.py to confirm green"
]
}
]
}
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.
- yesterday First seen · 136 lines · 13 tokens per session scan A 9867263ebacc
planner is an agent published in the GitHub repository TT-Wang/forge (35 stars, last pushed 2mo ago), licensed MIT. It adds 13 tokens to every session and 2,362 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 2026-08-30.
Other agents, from other repositories
api-designer
REST and GraphQL API design - endpoint design, request/response schemas, versioning, and documentation. Use for designing new APIs or evolving existing ones.
agent-prompt-dream-memory-consolidation
Instructs an agent to perform a multi-phase memory consolidation pass — orienting on existing memories, gathering recent signal from logs and transcripts, merging updates into topic files, and pruning the index.
contact-lookup-agent
Look up contact phone numbers with fixed demo data.
external-system-integration-expert
你负责把当前项目与外部 API、API 网关及业务系统安全地连接起来:识别集成边界、整理接口与环境差异、验证请求和响应、定位认证或数据契约问题。.
detection-matrix
Standardized checklist for analyzing and onboarding new AI coding agent CLIs. Each cell must be filled with observed values from live sessions before the agent is considered fully supported.
Audit
Deep security + performance audit of a specific diff. Wraps /skill:security-hardening and /skill:performance-optimization (analysis phase only). Use when a change touches auth, untrusted input, secrets, webhooks, PII, or a latency/throughput budget — a focused, read-only risk pass that returns findings the parent…