fix-bug

A bug-fixing workflow for the tapd-ai-cli Go command-line project. It takes a bug report through analysis, an isolated work area, code changes, tests, verification, and merging into the main branch.

In plain words
What is it for?
Use it when you have a known bug and reproduction details. It helps locate the cause, apply the fix, add unit tests, run formatting, linting, builds, tests and coverage checks, then merge the result.
Why use it?
It organizes the full repair process so investigation, testing, and cleanup are not missed. An isolated work area keeps the repair separate while it is being developed.

Skill for Claude CodeCodex

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 skills/studyzy/tapd-ai-cli/fix-bug
Any agent
npx skills add studyzy/tapd-ai-cli --skill fix-bug
Clone the repo
git clone --depth 1 https://github.com/studyzy/tapd-ai-cli

Made for: Claude Code, Codex.

Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,919 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 $0.00073 $0.02919
Opus 5 $0.00036 $0.01460
Sonnet 5 $0.00015 $0.00584
Haiku 4.5 $0.00007 $0.00292

Measured 2d ago against content hash 550241a4ad80, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

fix-bug 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.

.codebuddy/skills/fix-bug/SKILL.md · 306 lines

How it starts

The opening of the file, as written. The whole thing — 306 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Bug 修复流水线

从 Bug 描述出发,自动完成:Bug 分析与定位 → 创建隔离 Worktree → 代码修复 → 补充测试 → 全量验证 → 合入主分支 → 清理 Worktree。

适用于 tapd-ai-cli 项目——一个纯 Go CLI 工具,无前端、无 E2E 测试。


流程总览

用户输入 Bug 描述
        |
        v
[阶段 1] Bug 分析与定位
        |
        v
  确认修复方案
        |
        v
[阶段 2] 创建 Worktree(隔离工作区)
        |
        v
[阶段 3] 代码修复
        |
        v
[阶段 4] 补充单元测试
        |
        v
[阶段 5] 全量验证(fmt / lint / build / test / coverage)
        |  ← 失败则修复代码并重新验证
        v
[阶段 6] 合入主分支并清理 Worktree
        |
        v
  完成

步骤

阶段 1:Bug 分析与定位

  1. 获取 Bug 信息

    用户在调用此 SKILL 时应附带 Bug 描述。如果未提供,使用 AskUserQuestion tool 询问:

    "请描述您遇到的 Bug,包括复现步骤、期望行为和实际行为。"

  2. 阅读项目上下文

    阅读以下文件获取项目背景:

    • CODEBUDDY.md — 项目架构、构建命令、代码规范
    • docs/requirement.md — 需求规格
  3. 分析 Bug 根因

    使用 Agent tool(subagent_type=Explore)深入分析 Bug:

    • 根据 Bug 描述定位相关代码文件
    • 项目目录结构:cmd/tapd/(入口)、internal/cmd/(命令层)、internal/client/(API 客户端层)、internal/config/(配置层)、internal/output/(输出层)、internal/model/(数据模型层)
    • 追踪数据流:参数解析 → API 调用 → 响应转换 → 格式化输出
    • 分析可能的根因
    • 检查是否有相关的已有测试覆盖该场景
  4. 提出修复方案并确认

    使用 AskUserQuestion tool 向用户展示分析结果并确认修复方案:

    • Bug 根因分析
    • 受影响的文件和模块
    • 修复方案(如有多种方案,列出各方案的优缺点)
    • 可能的影响范围

    等待用户确认修复方案后再继续。

阶段 2:创建 Worktree(隔离工作区)

  1. 确认当前分支状态

    在创建 worktree 前,先检查当前分支状态:

    git status
    git branch --show-current
    
    • 如果当前有未提交的更改,使用 AskUserQuestion tool 提醒用户并询问是否继续(worktree 是独立的,不影响当前工作区的更改)。
    • 记录当前所在的主分支名称(通常是 mainmaster),后续合入时使用。
  2. 创建隔离 Worktree

    使用 git 命令在项目父目录下创建 worktree,避免在项目内部产生额外目录:

    # 获取项目根目录的父目录路径
    PROJECT_ROOT=$(git rev-parse --show-toplevel)
    WORKTREE_DIR="$(dirname "$PROJECT_ROOT")/worktree/fix-<bug简述>"
    
    # 基于主分支创建新分支和 worktree
    git worktree add -b fix-<bug简述> "$WORKTREE_DIR" <主分支名>
    
    • 分支命名:使用 fix-<bug简述> 格式,例如 fix-auth-token-error
    • Worktree 路径:../worktree/fix-<bug简述>(相对于项目根目录)
    • 基于步骤 5 中记录的主分支创建

    创建成功后,使用 cd 切换到新的 worktree 目录中。后续所有代码修改和测试都在此工作区中进行。

Read the full file on GitHub · 306 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 · 306 lines · 73 tokens per session scan A 550241a4ad80

Subscribe to this mod's changes

fix-bug is a skill published in the GitHub repository studyzy/tapd-ai-cli (54 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 73 tokens to every session and 2,919 once invoked, about $0.0004 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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