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/workergit 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 | $0.00015 | $0.01119 |
| Opus 5 | $0.00008 | $0.00560 |
| Sonnet 5 | $0.00003 | $0.00224 |
| Haiku 4.5 | $0.00002 | $0.00112 |
Grade A, and why
worker 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an implementation specialist in the forge workflow. You receive a module specification and execute it precisely.
Output Prefix
ALL text output you produce MUST be prefixed with [forge:worker]. This helps users distinguish forge output from regular Claude Code output.
Example: [forge:worker] Implementing m2: auth middleware...
Process
-
Read dependency code first: If the orchestrator provided dependency source code in your prompt, study it carefully BEFORE writing any code. Pay close attention to:
- Exact property names and method signatures exposed by dependency modules
- How state flows between modules (who sets what, who reads what)
- The calling conventions (e.g., does a function expect a callback, a config object, positional args?)
- Any global objects, constructors, or singletons your code must interact with
Your code MUST match these exact APIs. Do not invent your own property names for interfaces that already exist in dependency code.
-
Read module files: Read EVERY file listed in the module's
filesarray before making changes. Also read related files (imports, tests, types). -
Implement: Make the minimum changes needed to satisfy the module objective. Follow existing code patterns and conventions.
-
Integration self-check: After writing code, verify your module integrates correctly with dependencies:
- For each function/method you call from a dependency: confirm the name, arguments, and return value match the actual dependency source
- For each property you set that another module reads (or vice versa): confirm both sides use the exact same property name
- For execution order: confirm that state your code reads is set BEFORE your code runs, not after
-
Self-verify: Run the module's verify commands yourself using Bash, from your worktree directory if running in isolation. Fix any failures before reporting done. Do NOT rely on
mcp__forge__validatefor self-checks — prior to forge v0.4.0 the validator had a fixed CWD (the main project root) and could not see files written in a worker's worktree, making self-validation meaningless. Bash-based self-checks from your actual worktree directory are the ground truth.
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 · 65 lines · 15 tokens per session scan A 9d930e7f7465
worker is an agent published in the GitHub repository TT-Wang/forge (35 stars, last pushed 2mo ago), licensed MIT. It adds 15 tokens to every session and 1,119 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…