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 commands/cacr92/wereply/checkgit clone --depth 1 https://github.com/cacr92/WeReplyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/cacr92/wereply/check)<a href="https://agentmods.dev/commands/cacr92/wereply/check"><img src="https://agentmods.dev/badge/commands/cacr92/wereply/check.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.00000 | $0.00491 |
| Opus 5 | $0.00000 | $0.00246 |
| Sonnet 5 | $0.00000 | $0.00098 |
| Haiku 4.5 | $0.00000 | $0.00049 |
Grade A, and why
check 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 3d 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
/check - 代码质量和安全检查
用途
执行全面的代码质量和安全检查，包括 lint、类型检查、安全审计等。
执行步骤
1. Rust 后端检查
# Clippy 检查
cargo clippy --all-targets --all-features -- -D warnings
# 格式检查
cargo fmt -- --check
# 安全审计
cargo audit
# 类型检查
cargo check --all-targets
2. TypeScript 前端检查
# ESLint 检查
cd frontend && npm run lint
# TypeScript 类型检查
cd frontend && npm run type-check
# 格式检查
cd frontend && npm run format:check
3. 测试覆盖率检查
# Rust 测试覆盖率
cargo tarpaulin --out Html --output-dir coverage
# TypeScript 测试覆盖率
cd frontend && npm run test:coverage
4. 依赖检查
# Rust 依赖更新检查
cargo outdated
# TypeScript 依赖检查
cd frontend && npm outdated
输出报告
检查完成后，生成报告：
## 代码质量检查报告
### Rust 后端
- ✅ Clippy: 无警告
- ✅ 格式: 符合规范
- ✅ 安全审计: 无已知漏洞
- ✅ 类型检查: 通过
### TypeScript 前端
- ✅ ESLint: 无错误
- ✅ 类型检查: 通过
- ✅ 格式: 符合规范
### 测试覆盖率
- Rust: 85% (目标: 80%)
- TypeScript: 82% (目标: 80%)
### 依赖状态
- Rust: 3 个依赖可更新
- TypeScript: 5 个依赖可更新
## 建议
1. 更新过时的依赖
2. 继续保持测试覆盖率
何时使用
- 提交代码前
- Pull Request 前
- 定期代码质量检查
- CI/CD 流程中
相关 Skills
- code-review
- security-review
- testing-strategy
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.
- 3d ago First seen · 94 lines · 0 tokens per session scan A ae882c53e19e
check is a command published in the GitHub repository cacr92/WeReply (6 stars, last pushed 7mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 491 tokens. 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 commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.