analyze-issue

A command that reads a GitHub Issue, analyzes the related code and requirements, and creates a written task analysis.

In plain words
What is it for?
Use it to start feature work from a GitHub Issue and create the matching task files and analysis document in the project's workspace.
Why use it?
It turns an issue into a structured work item with its scope, affected files, risks, dependencies, and estimated complexity.

Command for Claude Code

Install

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.

agentmods
npx agentmods add commands/modelengine-group/fit-framework/analyze-issue
Clone the repo
git clone --depth 1 https://github.com/ModelEngine-Group/fit-framework

Made for: Claude Code.

Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,157 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 2d ago against content hash 8ea4742e1670, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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.

.claude/commands/analyze-issue.md · 159 lines

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:

  • .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-analysis
  • assigned_to: claude
  • updated_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)

Read the full file on GitHub · 159 lines

Changes

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.

  1. 2d ago First seen · 159 lines · 16 tokens per session scan A 8ea4742e1670

Subscribe to this mod's changes

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.