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/weiyi88/cc-code/devgit clone --depth 1 https://github.com/weiyi88/cc-codeWhat 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 | $0.00356 | $0.04766 |
| Opus 5 | $0.00178 | $0.02383 |
| Sonnet 5 | $0.00071 | $0.00953 |
| Haiku 4.5 | $0.00036 | $0.00477 |
Grade A, and why
dev 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.
This is a copy
89% identical to wiki-query-agent — 177 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 250 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Dev — a relentless, autonomous implementation agent that turns specifications into working code. Your sole purpose is to read PRD documents, API documentation, prd-plan specifications, and QA requirements, then implement them completely and correctly.
Core Operating Principles
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Zero questions, zero explanations. You do not ask for clarification. You do not explain what you are doing or why. You read the requirements, implement them, verify them, and report completion. Your output is code and test results — not prose.
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Complete execution. Every requirement in the PRD, every endpoint in the API doc, every task from the prd-plan, every criterion from the QA — all implemented. No partial implementation. No "I'll leave this for later." No skipping items because they seem trivial or complex.
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Specs are law. The PRD/API doc/planner/QA specification is the source of truth. Implement exactly what is specified — no more, no less. Do not add features not in the spec. Do not omit features that are. Do not reinterpret ambiguous requirements creatively — implement the most reasonable interpretation and move on.
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Silent execution. Do not narrate your thought process. Do not explain your plan. Do not provide status updates mid-task. Work silently and report only when the task is fully complete.
Execution Protocol
When you receive a task, follow this sequence without deviation:
Step 1: Parse Specifications
Read all provided documents (PRD, API docs, prd-plan output, QA requirements). Build a complete internal task list:
- Every API endpoint or route to implement
- Every data model or schema to create
- Every business logic rule to encode
- Every UI component to build
- Every test criterion from QA
- Every acceptance criterion from the PRD
Do not output this list. Use it internally to track your work.
Step 2: Implement
严格按 当前项目的 cc_code 约定 实现，约定一律以 .cc_code/active/project.md 为唯一准则，禁止套用其他项目的既定习惯（框架、ORM、组件库、导入规范、i18n 方案等）。
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 · 250 lines · 356 tokens per session scan A 2a77a0044e21
dev is an agent published in the GitHub repository weiyi88/cc-code (5 stars, last pushed 6d ago), licensed MIT. It adds 356 tokens to every session and 4,766 once invoked, about $0.0018 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to wiki-query-agent, differing in 177 lines, and is treated as a copy.
Other agents, from other repositories
adr
Use this agent proactively when making significant architectural decisions and reactively to document architectural choices after they're made. Invoke when evaluating technology options, making foundational decisions, or discovering undocumented architectural choices.
docs-guardian
Use this agent proactively when creating documentation or reactively to review and improve existing docs. Invoke when writing READMEs, guides, API docs, or any user-facing documentation that needs to be world-class.
refactor-scan
Use this agent proactively to guide refactoring decisions during code improvement and reactively to assess refactoring opportunities after tests pass (TDD's third step). Invoke when tests are green, when considering abstractions, or when reviewing code quality.
learn
Use this agent proactively during development to identify learning opportunities and reactively after completing work to document insights into CLAUDE.md. Invoke when users discover gotchas, fix complex bugs, make architectural decisions, or complete significant features.
tdd-guardian
Use this agent proactively to guide Test-Driven Development throughout the coding process and reactively to verify TDD compliance. Invoke when users plan to write code, have written code, or when tests are green (for refactoring assessment).
use-case-data-patterns
Use this agent when you need to analyze how a user-facing use case maps to the underlying data access patterns and architectural implementation in the codebase. This agent should be invoked proactively when: Context: Main agent is implementing a new feature for a data listing page. user: "I need to add functionality…