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/joe-rq/harness-lab/bugfixgit clone --depth 1 https://github.com/Joe-rq/harness-labWrote 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/joe-rq/harness-lab/bugfix)<a href="https://agentmods.dev/commands/joe-rq/harness-lab/bugfix"><img src="https://agentmods.dev/badge/commands/joe-rq/harness-lab/bugfix.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 | $0.00023 | $0.00478 |
| Opus 5 | $0.00012 | $0.00239 |
| Sonnet 5 | $0.00005 | $0.00096 |
| Haiku 4.5 | $0.00002 | $0.00048 |
Grade A, and why
bugfix 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 4d 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
/bugfix
目标
引导用户快速创建 bugfix 型 REQ。
前置检查
- 确认
requirements/目录存在。不存在 → 提示先运行/harness-setup - 确认
package.json中有req:create脚本。不存在 → 提示先运行/harness-setup - 确认当前无活跃 REQ（
requirements/INDEX.md中## 当前活跃 REQ下为"无"）。有活跃 REQ → 提示先完成或搁置当前 REQ
执行步骤
Step 1: 收集 Bug 信息
使用 AskUserQuestion 询问：
- Bug 简述（必填）：一句话描述 Bug 现象，如"登录页面点击提交后无响应"
- 影响范围（必填）：哪些功能/用户受影响，如"所有使用邮箱登录的用户"
Step 2: 创建 bugfix REQ
运行：
npm run req:create -- --title "fix: [Bug 简述]" --type bugfix
Step 3: 补充 Bug 详情
用 Edit 将 REQ 中的占位符替换为用户提供的实际信息：
[请描述]（背景-Bug 现象）→ 用户的 Bug 简述[请描述]（背景-影响范围）→ 用户的影响范围
Step 4: 提示用户确认
提示用户：
- 检查自动填充的内容是否符合实际情况
- 补充"颗粒度自检"
- 确认后运行
npm run req:start -- --id {reqId} --phase implementation
输出
- 创建的 REQ ID 和文件路径
- REQ 类型：bugfix
- 已预填充：Bug 特化目标、skip-design-validation、回归测试验收标准
- 下一步：补充颗粒度自检，运行
req:start
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.
- 4d ago First seen · 54 lines · 23 tokens per session scan A 75aac089f7b9
bugfix is a command published in the GitHub repository Joe-rq/harness-lab (20 stars, last pushed 22d ago), licensed MIT. It adds 23 tokens to every session and 478 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 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.