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bulletproofbulletproof 搜索

Agent Skill

bulletproof 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

192

周安装

8

GitHub Stars

127

下载量

64
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:bulletproof(bulletproof 搜索)
来源仓库:https://github.com/artemiimillier/bulletproof
仓库路径:skills/bulletproof
安装命令:
npx skills add https://github.com/artemiimillier/bulletproof --skill bulletproof
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/artemiimillier/bulletproof --skill bulletproof

简介

自适应开发工作流框架,强调问题驱动而非代码驱动。

  • 每次变更前必须明确:是否解决实际问题?是否有更优方案?
  • 支持多种模式(Bug 修复、小编辑、大重构)以适应不同任务规模。
  • 建议结合具体场景选择模式,避免过度设计或流程僵化。
  • bulletproof 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Bulletproof — Adaptive Development Workflow

Author: Artemiy Miller (@artemiimillier) · Telegram · who.ismillerr@gmail.com · TG Channel Version: 5.0 · March 2026 License: MIT Compatible: Claude Code, Codex, Gemini CLI, Cursor, Windsurf, OpenCode

Core Principle

Code to solve problems, not code for code's sake.

Before EVERY change ask: "Does this actually solve our problem? Is this the most efficient solution?" If the answer isn't clear — stop, research alternatives, pick the best one.


Pick Your Mode

Not every task needs the full pipeline.

SizeExamplesModeStages
SBug fix, small edit, 1-2 filesLightweight1 → 4 → 5 → 6 → 7 → Gates (skip spec/plan)
MNew feature, module refactor, 3-10 filesStandardStages 1-10
LArchitecture change, new service, 10+ filesFullStages 1-12 (all)

How stages relate: Stages 5-6-7 (Self-Audit, Verification, Impact) run inside each implementation phase as an inner loop. Stages 8-12 run once after all phases complete as an outer loop.


Context Management (ALWAYS applies)

The 40% Rule

Code quality degrades when context fills beyond 40% ("Dumb Zone"). Rules:

  • Stay within 40-60% of the context window
  • Manual /compact at 50% — don't wait for auto
  • If overloaded: save progress → /clear → fresh start

Fresh Context Between Stages

Every major stage = clean context window:

  1. Save stage artifact (research / spec / plan / handoff)
  2. /clear
  3. Start new stage pointing the agent to the artifact path

Handoff Protocol

Before /clear always create progress/<task>-handoff.md. See templates/handoff.md for format.

Progressive Disclosure

Don't dump the entire codebase into context:

  • Research: sub-agents → compact summary
  • Planning: summary + key interfaces only
  • Implementation: only files for current phase
  • In CLAUDE.md: "For details, see path/to/docs.md" (not @file)

Stage 1: Deep Research

Mode: Read-Only. No code. No changes.

  • Launch parallel Explore agents (1 per area: structure, patterns, deps, tests)
  • WebSearch: Who has already solved this problem? How did they solve it? What is the most efficient known solution? Don't reinvent — find the best existing approach first.
  • Analyze all findings and make a conclusion: which solution is the BEST and why. The research artifact must end with a clear recommendation, not just a list of options.
  • Save to thoughts/research/YYYY-MM-DD-<task>.md (see templates/research.md for format)

/clear


Stage 2: Spec / PRD

Mode: Read + Write only in specs/. No code.

Spec = WHAT and WHY. Not how. Spec = contract.

  • Read Research Artifact from thoughts/research/
  • Create specs/YYYY-MM-DD-<name>.md (see templates/spec.md for format)
  • Key sections: Problem, Goal, Scope, Acceptance Criteria, Constraints, Non-Goals

Skip for size S tasks. /clear


Stage 3: Planning + Questions

Mode: Read + Write only in plans/. No code yet.

  • Read both Spec (specs/) and Research (thoughts/research/)
  • Launch Plan agents to check the approach
  • Find gaps: what's unthought? What edge cases? What could break?
  • Be creative and proactive: anticipate ALL possible problems BEFORE writing code. Think several steps ahead. What could go wrong in a week? A month? Under load? With unexpected user behavior? Solve problems before they exist.
  • WebSearch: How have others solved this exact problem? What libraries/patterns exist? What's the proven best practice? Choose the most efficient solution, not the first one that comes to mind.
  • After Plan agents verify the approach — rewrite the plan into an improved version incorporating all findings, edge cases, and research results. Not just patch it — rewrite it better.

Challenge Loop (mandatory before finalizing plan)

Before finalizing the plan, answer 3 questions:

1. DOES THIS SOLVE THE PROBLEM?
   Compare every plan item against acceptance criteria from spec.
   If any criterion is uncovered — the plan is incomplete.

2. IS THIS THE MOST EFFICIENT SOLUTION?
   Search: who has already solved this problem? What approach did they use?
   Name 2-3 alternative approaches (including ones found via research).
   For each: pros, cons, effort.
   Justify why the chosen approach is better than all alternatives.

3. IS THERE "CODE FOR CODE'S SAKE"?
   Every change must directly serve acceptance criteria.
   If a change isn't tied to solving the problem — remove it.
   Drive-by refactoring = separate task, not part of this one.

Annotation Cycle

  1. Claude drafts the plan
  2. Ctrl+G — plan opens in editor
  3. User adds > NOTE: annotations
  4. Claude: "Address all notes, don't implement yet"
  5. Repeat until no notes remain

Questions for User

  • Only for real forks where there's a genuine decision to make
  • Use AskUserQuestion with options
  • For each question: recommend which option you think is best and why
  • Don't ask the obvious

Final Plan

Create plans/YYYY-MM-DD-<name>.md (see templates/plan.md for full template with Challenge Log, phases, prompts)

/clear


Stage 4: Phased Implementation

Each phase = separate session, fresh context, feature branch.

Phases can be run in parallel via separate Claude Code sessions/terminals when they don't depend on each other. Check the plan for dependencies before parallelizing.

Guard phrase to start coding: Only begin implementation after the plan is finalized and all annotation notes are addressed. The trigger: "Implement Phase N according to plan."

Order within each phase:

  1. Create/switch to feature branch: feature/<task>
  2. Update status → in_progress
  3. TDD: tests FIRST (red)
  4. Implement: code to make tests pass (green)
  5. Refactor (if needed)
  6. Self-Audit (Stage 5)
  7. Verification (Stage 6)
  8. Impact Analysis (Stage 7)
  9. Gates (see Gates section)
  10. Commit (checkpoint)
  11. Status → completed, write to Changelog
  12. Handoff/clear

Stage 5: Self-Audit (after each phase)

Mandatory BEFORE marking completed:

Check the phase implementation:

1. SPEC COMPLIANCE
   Open spec. Walk through every acceptance criterion.
   For each: implemented? Where exactly in code?
   If any not covered — finish it.

2. CHALLENGE THE SOLUTION
   Look at the written code with fresh eyes.
   Does this actually solve the problem from spec?
   Is there a simpler/more efficient way?
   Any "code for code's sake" — changes unrelated to the task?

Stage 6: Verification — Deep Bug Hunt

Not just linting. Thoughtful review with false-positive filtering.

Step 1: Find errors

Check ALL code from this phase for:
- Logic errors (wrong conditions, off-by-one, race conditions)
- Data handling (null/undefined, type mismatches)
- Security (injection, auth bypass, exposed secrets)
- Performance (N+1 queries, memory leaks, unnecessary re-renders)

Step 2: Verify bugs are REAL

For EACH found bug:
1. Is this a REAL bug or a false positive?
2. Can you prove this bug is reproducible?
3. If you can't prove it — it's NOT a bug. Don't touch it.

RULE: Don't fix code "for beauty" or "just in case".
Fix ONLY proven bugs that actually affect functionality.
Every "fix" without proof = risk of introducing a new bug.

Step 3: Logic and efficiency check

Final code cleanliness check:
- Logic: is the data flow correct from input to output?
- Efficiency: any redundant operations?
- Readability: is the code understandable without comments?
BUT: don't refactor "for beauty". Only if it affects correctness.

Stage 7: Impact Analysis — "Did we break anything?"

The most underestimated stage. 75% of AI agents break previously working code.

MANDATORY CHECK BEFORE MERGE:

1. REGRESSION
   What other modules/functions depend on changed files?
   Run ALL project tests (not just current phase).
   If anything broke — this is priority #1.

2. SIDE EFFECTS
   Did any contracts/interfaces change (API, props, types)?
   If yes — who uses them? Are all consumers updated?

3. THINK AHEAD
   What problems could these changes cause in a week/month?
   Edge cases we haven't tested?
   What happens with: zero data? Huge data? Concurrent requests?
   What if the user does something unexpected?

4. COMPATIBILITY
   Backward compatibility preserved?
   Data migrations needed?
   Feature flags needed for gradual rollout?

Stage 8: Integration Check

  • All phases completed → run gates across entire project
  • Explore agents for audit: everything from spec implemented?
  • Every acceptance criterion → fulfilled?

Stage 9: Code Review (fresh context)

New session. No implementation bias.

  • Launch @code-reviewer agent (see agents/code-reviewer.md)
  • Checklist: edge cases, race conditions, backward compat, security, error handling, performance
  • If possible: cross-model review (different model checks Claude's work)
  • Warning: AI reviewing AI has shared blind spots. For critical code — human review is mandatory.

Stage 10: Security Scan (for M and L)

semgrep --config=auto .
# or
/security-review    # built into Claude Code

Stage 11: Fixes + Re-verification

If review/scan found issues:

  1. Fix (only proven bugs — rule from Stage 6)
  2. Re-run gates
  3. Repeat Impact Analysis (Stage 7) — fixes didn't break anything else?
  4. Re-review if major changes were made

Stage 12: Cleanup + Deploy

  • Archive plan: mv plans/<file> plans/archive/
  • Keep spec as documentation
  • Squash merge → main
  • Deploy — ONLY on explicit user request

Deterministic Gates

A phase CANNOT be completed without passing ALL required gates.

Tier 1: Required (block the phase)

# Frontend
cd frontend && npx tsc --noEmit          # 0 type errors
cd frontend && npm run lint               # 0 lint errors
cd frontend && npm test                   # all tests green

# Backend
cd backend && python -m py_compile app/main.py
cd backend && pytest --tb=short -q
cd backend && ruff check .

Tier 2: Recommended (for M and L)

npx madge --circular src/         # circular dependencies
npm audit --audit-level=high      # dependency vulnerabilities
pip-audit

Tier 3: Deep Security (for Security Scan stage)

semgrep --config=auto .
# or /security-review

If a gate fails — fix and re-run. Never skip.


Hooks

Add to .claude/settings.json:

{
  "hooks": {
    "PreToolUse": [
      {
        "matcher": "Bash",
        "hooks": [{
          "type": "command",
          "command": "bash -c \"CMD=$(echo $TOOL_INPUT | jq -r '.command // empty'); echo \\\"$CMD\\\" | grep -qE '(git push.*(main|master)|rm -rf /|DROP TABLE)' && echo 'BLOCKED: Use feature branch / safe alternative.' >&2 && exit 2 || exit 0\""
        }]
      }
    ],
    "Stop": [
      {
        "hooks": [{
          "type": "prompt",
          "prompt": "You are a JSON-only evaluator. Respond ONLY with raw JSON, no markdown.\n\nReview the assistant's final response. Reject if:\n- Rationalizing incomplete work ('pre-existing', 'out of scope', 'follow-up')\n- Listing problems without fixing them\n- Skipping test/lint failures with excuses\n- Making changes unrelated to the stated problem ('code for code's sake')\n- Claiming completion without running verification gates\n\nRespond: {\"ok\": false, \"reason\": \"[issue]. Go back and finish.\"}\nor: {\"ok\": true}"
        }]
      }
    ]
  }
}

Git Discipline

  • Each task = feature/<task> branch
  • Commit after each passed gate (checkpoint for rollback)
  • NEVER push to main directly (hook blocks it)
  • Squash merge on completion

Optional Enhancements

PostToolUse: Auto-format after every file write

{
  "matcher": "Write|Edit",
  "hooks": [{
    "type": "command",
    "command": "npx prettier --write \"$FILE_PATH\" 2>/dev/null || true"
  }]
}

Claude generates well-formatted code; the hook handles the last 10% to avoid CI failures.

PreToolUse: Block hardcoded secrets on file write

{
  "matcher": "Write|Edit",
  "hooks": [{
    "type": "command",
    "command": "bash -c \"CONTENT=$(echo $TOOL_INPUT | jq -r '.content // empty'); echo \\\"$CONTENT\\\" | grep -qiP '(api.?key|secret|password)\\s*=\\s*[\\x27\\\"][^\\x27\\\"]{10,}' && echo 'BLOCKED: Hardcoded secret. Use env vars.' >&2 && exit 2 || exit 0\""
  }]
}

Fragile (regex-based) but catches obvious mistakes. For production, use semgrep or /security-review instead.


Model Recommendations

StageModelWhy
Research, PlanningOpusCross-file reasoning
ImplementationSonnetSpeed, cost-efficiency
Code Review, SecurityOpusDeep analysis
Anti-rationalization hookHaikuFast, cheap gate

Project Structure

project/
├── .claude/
│   ├── settings.json           # hooks config
│   ├── skills/
│   │   └── bulletproof/
│   │       ├── SKILL.md        # ← this file
│   │       ├── templates/
│   │       │   ├── research.md
│   │       │   ├── spec.md
│   │       │   ├── plan.md
│   │       │   └── handoff.md
│   │       └── agents/
│   │           └── code-reviewer.md
│   └── agents/                 # project-level agents
├── CLAUDE.md                   # project brain
├── specs/                      # WHAT and WHY
├── plans/                      # HOW
│   └── archive/                # completed plans
├── thoughts/research/          # research artifacts
└── progress/                   # handoff files

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.8%
按下载量换算23

Claude

29.98%
按下载量换算19

Cursor

21.04%
按下载量换算13

Gemini CLI

8.94%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

未通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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