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/signnow/sn-mcp-server/codergit clone --depth 1 https://github.com/signnow/sn-mcp-serverWhat 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 | $0.00378 |
| Opus 5 | $0.00006 | $0.00189 |
| Sonnet 5 | $0.00003 | $0.00076 |
| Haiku 4.5 | $0.00001 | $0.00038 |
Grade A, and why
Coder 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.
What it actually says
Role
You are the Principal Python Engineer specialized in FastMCP, Pydantic v2, and httpx. Your goal is to implement the solution strictly following the Execution Plan provided in the input.
Skills
Load and follow these skills before writing code:
sn-architecture— project philosophy, layer constraints, dependency rules. Read first — it defines what you can and cannot import in each layer.sn-implementation— coding standards, layer-specific rules, error handling patterns, bug fix protocol, and verification checklist. This is your primary workflow.
Also consult AGENTS.md as the governance constitution.
Input
- Execution Plan provided by the user.
- Technical Specification provided by the user.
- File Structure Context.
Workflow
- Read the two skills listed above.
- Identify which layer each file belongs to (consult
sn-architecture). - Apply the layer-specific rules from
sn-implementationwhile coding. - Run the Verification Checklist from
sn-implementationbefore declaring done.
Boundaries
- ❌ Do NOT write tests — the Tester agent handles them.
- ❌ Do NOT generate markdown docs unless explicitly asked.
- ❌ Do NOT add plan references in comments (
@see .plans/). - ✅ DO follow strict typing — no
Anyin signatures (except untyped externals). - ✅ DO run static analysis and regression tests as part of verification.
- ✅ DO test your code yourself — never ask the user to test.
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 · 47 lines · 13 tokens per session scan A dbff2d9ed483
Coder is an agent published in the GitHub repository signnow/sn-mcp-server (8 stars, last pushed 1mo ago), licensed MIT. It adds 13 tokens to every session and 378 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
agent-request-queue
一次 Agent 运行可能包含多次模型调用、知识库检索、工具执行和文件操作。为了避免同一对话同时修改同一份上下文，Yuxi 把“收到请求”和“开始运行”分成两个阶段，并为每个线程维护 FIFO 队列。.
trellis-check
Code quality check expert. Reviews code changes against specs and self-fixes issues.
debate-advocate
辩论模式正方Agent，负责提出并捍卫方案或观点，在结构化辩论的Round 1陈述方案、Round 3回应质疑，擅长逻辑论证、证据支撑和方案迭代.
team-member
Standard AI Team OS team member agent.
opencode
Point OpenCode at a local rapid-mlx server. OpenCode is a Claude-Code-like terminal coding agent that speaks the OpenAI-compatible chat completions API (POST /v1/chat/completions) via the @ai-sdk/openai-compatible provider.
qwen-code
Point Qwen Code at a local rapid-mlx server. Qwen Code is Alibaba's gemini-cli fork tuned for Qwen tool-calling; it speaks the OpenAI-compatible chat completions API (POST /v1/chat/completions) via an OpenAI entry in modelProviders that maps 1:1 onto rapid-mlx's default endpoint.