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/modelengine-group/fit-framework/analyze-issuegit clone --depth 1 https://github.com/ModelEngine-Group/fit-frameworkWhat 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 | $0.00016 | $0.01157 |
| Opus 5 | $0.00008 | $0.00579 |
| Sonnet 5 | $0.00003 | $0.00231 |
| Haiku 4.5 | $0.00002 | $0.00116 |
Grade A, and why
analyze-issue 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.
How it starts
The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze Issue Command
功能说明
分析指定的 GitHub Issue,创建任务并输出需求分析文档。
⚠️ CRITICAL: 状态更新要求
执行此命令后,你必须立即更新任务状态。参见规则 7。
执行流程
1. 获取 Issue 信息
gh issue view <issue-number> --json number,title,body,labels
2. 创建任务目录和文件
检查是否已存在该 Issue 的任务:
- 在
.ai-workspace/active/中搜索相关任务 - 如果找到,询问是否重新分析
- 如果没有,创建任务目录:
.ai-workspace/active/TASK-{yyyyMMdd-HHmmss}/ - 使用
.agents/templates/task.md模板创建任务文件:task.md
3. 执行需求分析
按照 .agents/workflows/feature-development.yaml 中的 requirement-analysis 步骤:
必须完成的任务:
- 阅读并理解 Issue 描述
- 搜索相关代码文件(使用 Glob/Grep 工具)
- 分析代码结构和影响范围
- 识别潜在的技术风险和依赖
- 评估工作量和复杂度
4. 输出分析文档
创建 .ai-workspace/active/{task-id}/analysis.md,必须包含以下章节:
# 需求分析报告
## 需求理解
{用自己的话重新描述需求,确保理解正确}
## 相关文件列表
- `{file-path}:{line-number}` - {说明}
## 影响范围评估
**直接影响**:
- {影响的模块和文件}
**间接影响**:
- {可能影响的其他部分}
## 技术风险
- {风险描述和应对思路}
## 依赖关系
- {需要的依赖和其他模块的配合}
## 工作量和复杂度评估
- 复杂度:{高/中/低}
- 工作量:{预估时间}
- 风险等级:{高/中/低}
5. 更新任务状态
更新 .ai-workspace/active/{task-id}/task.md:
current_step: requirement-analysisassigned_to: claudeupdated_at: {当前时间}- 标记 analysis.md 为已完成
6. 告知用户
输出格式:
✅ Issue #{number} 分析完成
**任务信息**:
- 任务ID: {task-id}
- 任务标题: {title}
- 工作流: feature-development
**输出文件**:
- 任务文件: .ai-workspace/active/{task-id}/task.md
- 分析文档: .ai-workspace/active/{task-id}/analysis.md
**下一步**:
审查需求分析后,使用以下命令设计技术方案:
- Claude Code / OpenCode: `/plan-task {task-id}`
- Gemini CLI: `/fit:plan-task {task-id}`
- Codex CLI: `/prompts:fit-plan-task {task-id}`
✅ 完成检查清单
执行此命令后,确认:
- 已创建任务文件
.ai-workspace/active/{task-id}/task.md - 已创建分析文档
.ai-workspace/active/{task-id}/analysis.md - 已更新 task.md 中的
current_step为 requirement-analysis - 已更新 task.md 中的
updated_at为当前时间 - 已更新 task.md 中的
assigned_to为你的名字 - 已在"工作流进度"中标记 requirement-analysis 为完成 ✅
- 已告知用户下一步操作(/plan-task)
- 如果有关联 Issue,已在 task.md 中记录 Issue 编号
参数说明
<issue-number>: GitHub Issue 编号(必需)
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 · 159 lines · 16 tokens per session scan A 8ea4742e1670
analyze-issue is a command published in the GitHub repository ModelEngine-Group/fit-framework (2,117 stars, last pushed 5mo ago), licensed MIT. It adds 16 tokens to every session and 1,157 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.
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