Agent skill

Bug Fixing Openclaw

by LeoYeAI in LeoYeAI/openclaw-master-skills

Zero-regression bug fix workflow: triage → reproduce → root cause → impact analysis → fix → verify → knowledge deposit → self-reflect.

MITAuto-check passedDevelopment

Install Bug Fixing Openclaw

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill bug-fixing-openclaw -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills bug-fixing-openclaw --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/bug-fixing .claude/skills/bug-fixing-openclaw && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
bug-fixing-openclaw
GitHub stars
2.2k
Token cost
~6.5k tokens
SKILL.md length
1,858 words
Files
34 (incl. scripts, references)
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

Zero-regression bug fix workflow: triage → reproduce → root cause → impact analysis → fix → verify → knowledge deposit → self-reflect.

  • Works in 7 steps: Triage + Severity → Reproduce → Root Cause Analysis → …
  • : - Feature broken
  • SKILL.md covers Iron Rules (12 — NEVER Violate), Workflow Overview, Phase 0: Triage + Severity and Phase 1: Reproduce, plus 5 more sections
  • Calls npm, python and rg

What it does

Bug Fixing Openclaw is an agent skill from LeoYeAI/openclaw-master-skills. Zero-regression bug fix workflow: triage → reproduce → root cause → impact analysis → fix → verify → knowledge deposit → self-reflect. Use when: - Feature broken, incorrect behavior, wrong output, errors/exceptions - Console errors/warnings even when feature appears functional - Regressions, timeouts, degraded performance - Keywords: "fix bug", "debug", "not working", "error", "broken" Output: Bug summary + verification report + code review + self-reflection score. Not for: new features (use fullstack-developer)…

Its SKILL.md is about 6.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 34 other files, including scripts and reference files (for example `_meta.json`, `references/ai-blind-spots.md` and `references/backend-common-issues.md`).

It sits in Development, covering Debugging. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • : - Feature broken
  • Incorrect behavior
  • Errors/exceptions - Console errors/warnings even when feature appears functional - Regressions
  • Degraded performance - Keywords: fix bug

Example prompts

  • “fix bug”
  • “not working”
  • “broken”
  • “/bug-fixing-openclaw”

Requirements

  • Pre-approved tools (allowed-tools): read, write, execute, grep, glob

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Triage + Severity
  2. Reproduce
  3. Root Cause Analysis
  4. Scope + Prediction
  5. Fix
  6. Verify + Review
  7. Knowledge Deposit + Self-Reflection

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • read
    • write
    • execute
    • grep
    • glob

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/, which the agent can run.

    Shell commands in SKILL.md call:

    • npm
    • python
    • rg
    • ruff

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Bug Fixing Openclaw loads about 6.5k tokens when it runs, and up to ~63k if it reads all its reference files. Until then it costs about 154 tokens; SKILL.md has 1,858 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~154
When it runs · the whole SKILL.md, loaded when a task matches
~6.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~63k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 1,858 words, ~6,549 tokens.

Download SKILL.mdSave it as .claude/skills/bug-fixing-openclaw/SKILL.md (or your agent's skills folder). This skill also uses 33 other files; get the full folder from GitHub.
name
bug-fixing-openclaw
description
Zero-regression bug fix workflow: triage → reproduce → root cause → impact analysis → fix → verify → knowledge deposit → self-reflect. Use when: - Feature broken, incorrect behavior, wrong output, errors/exceptions - Console errors/warnings even when feature appears functional - Regressions, timeouts, degraded performance - Keywords: "fix bug", "debug", "not working", "error", "broken" Output: Bug summary + verification report + code review + self-reflection score. Not for: new features (use fullstack-developer); pure review (use code-review); optimization (use performance-optimization).
allowed-tools
read, write, execute, grep, glob
metadata.language
en
metadata.version
4.0.0
metadata.last_updated
2026-03-06
metadata.platform
openclaw
metadata.enhancement
v4.0 Iron Rules 20→12 (attention-dilution fix, aligned with bug-fixing v4.0), v4.0 Rule 8 NEW — UI bugs require runtime evidence before fix, v4.0 Rule 10 NEW…

Bug Fix v4.0 — OpenClaw Edition (Zero-Regression + Portable)

Core Promise: Fix completely. Fix everywhere. Break nothing. Learn from every fix.


Iron Rules (12 — NEVER Violate)

┌──────────────────────────────────────────────────────────────────────────┐
│  Rule 1:  Root cause MUST pass 4 gates before fixing                     │
│           (reproducible + causal + reversible + mechanistic)              │
│                                                                          │
│  Rule 2:  Scope MUST pass 5 gates before fixing                          │
│           (consumers + contracts + invariants + call sites + dup scan)    │
│                                                                          │
│  Rule 3:  MUST trace IMPACT CHAIN (code → data → time → event)          │
│           + scan ALL files for same pattern before writing fix            │
│                                                                          │
│  Rule 4:  MUST predict side effects + check blind spots before coding    │
│           (references/blind-spots.md is single source of truth)           │
│                                                                          │
│  Rule 5:  After fix, MUST run regression verification                    │
│           (functional + performance + concurrency + all impact levels)    │
│                                                                          │
│  Rule 6:  MUST verify fix is LOADED at runtime                           │
│           (clear __pycache__ + restart + exercise code path)              │
│                                                                          │
│  Rule 7:  Framework behavior → read source code first, never trust       │
│           docs/comments/assumptions alone                                │
│                                                                          │
│  Rule 8:  UI bugs MUST gather RUNTIME EVIDENCE before proposing fixes    │
│           (screenshot + DevTools DOM/console + user repro steps)          │
│           Do NOT fix UI bugs based on code reading alone.                │
│                                                                          │
│  Rule 9:  Fix is NOT done until: Bug Summary output + code-review        │
│           passes + knowledge files updated + self-reflection complete     │
│                                                                          │
│  Rule 10: Before fixing, CLASSIFY the problem layer:                     │
│           code bug? missing config? wrong architecture? AI capability?   │
│           Fix at the root layer, not at the symptom layer.               │
│                                                                          │
│  Rule 11: Pattern matching (regex, string match, name lookup) MUST       │
│           check boundary conditions (word boundaries / anchors / exact)   │
│                                                                          │
│  Rule 12: Before fix, MUST search bug pattern library + bug records      │
│           for known fixes and historical context                         │
└──────────────────────────────────────────────────────────────────────────┘

Workflow Overview

Phase 0: Triage → Severity (P0-P3) + Tier (Trivial/Standard/Complex)
  │
  ├─ Trivial → Quick Fix → test → done
  │
  ├─ Standard ─┐
  └─ Complex ──┘
      │
Phase 1: Reproduce (evidence required)
      │
Phase 2: Root Cause Analysis
    2A: Hypothesis ladder → 5 Whys → evidence
    2B: Search knowledge files (bug-patterns + bug-records)
    2C: Impact chain (code + data + time + event)
    2D: Similar issue scan across codebase
      │
Phase 3: Scope + Prediction
    3A: Consumer list → contracts → invariants → dup scan (5 gates)
    3B: Side effect prediction + blind spot check
    3C: Fix strategy comparison (when >10 LOC, Complex only)
      │
Phase 4: Fix (minimal change, prefer ≤50 LOC)
      │
Phase 5: Verify + Review
    5A: Regression verification (functional + perf + concurrency)
    5B: Runtime deployment verification
    5C: Bug Summary + code-review skill
      │
Phase 6: Knowledge Deposit + Self-Reflection

Phase 0: Triage + Severity

Classify severity AND tier FIRST to control workflow depth.

Severity Classification (controls workflow depth)
SeverityCriteriaWorkflowTime-box
P0 CriticalProduction down / data loss / securityFULL (all phases)4h escalation
P1 HighCore feature broken / data corruptionFULL (all phases)8h escalation
P2 MediumNon-core feature / UI issueSTANDARD (skip 3C)16h
P3 LowCosmetic / minor edge caseQUICK (skip 2C, 2D, 3A-3C)No limit
Tier Classification (controls fix path)
TierCriteriaPath
TrivialTypo, config value, 1-line obvious fix, no behavioral changeQuick Fix (below)
StandardLogic bug, 1-3 files, clear symptom, no cross-module riskStandard Path (skip phases marked "Complex only")
ComplexCross-module, >3 files, shared utility, schema change, multi-processFull Path (all phases mandatory)
Quick Fix Path (Trivial only)
markdown
## Quick Fix
- Bug: [one-line description]
- Fix: [one-line change]
- File: [path:line]
- Test: [how verified — lint/test/manual]
- Risk: None (isolated, no behavioral change)

After quick fix: update references/bug-records.md, done. No RCA, no impact chain, no self-reflection needed.

If "trivial" fix touches >1 file or changes behavior → upgrade to Standard.

Auto-Initialize Knowledge Files
Check: references/bug-patterns.md exists?
  YES → search it in Phase 2B
  NO  → skip pattern search; create after first fix

Check: references/bug-records.md exists?
  YES → search it in Phase 2B
  NO  → skip records search; create after first fix

Check: references/blind-spots.md exists?
  YES → use it in Phase 3B
  NO  → skip blind spot check; create after first fix

Phase 1: Reproduce

MUST have evidence before continuing. No evidence = no fix.

Bug TypeEvidence Required
Backend errorStack trace + request/response
Frontend UIScreenshot + browser console + user repro steps (Rule 8)
PerformanceBefore/after metrics + profiler output
IntermittentTiming conditions + frequency estimate

UI Bug Protocol (Rule 8):

  1. Get user screenshot or screen recording
  2. Open browser DevTools → check Console for errors/warnings
  3. Inspect DOM structure (check for overflow clipping, z-index, Portal needs)
  4. Reproduce the exact user steps
  5. ONLY THEN form hypotheses
Evidence Bundle Template
markdown
### Trigger Conditions
- Input/params: [...]
- Environment: [OS/browser/runtime version]
- Timing: [action sequence or time interval]

### Observable Output
- Error message: [full error text]
- Logs: [key log lines]
- Screenshot/recording: [if available]

### Correlation IDs
- requestId/traceId: [...]
- sessionId: [...]

Phase 2: Root Cause Analysis

2A: Hypothesis Ladder
#HypothesisLikelihoodConfirmation TestRejection TestStatus
1[description]High/Med/Low[prove it IS this][prove it is NOT this][ ]

Rules: Sort by likelihood → each must be falsifiable → run rejection tests first → test ONE at a time → use 5 Whys to reach root cause.

Root Cause Confirmation Gate (Rule 1)

Root cause is confirmed only when ALL 4 conditions are met:

GateMeaning
ReproducibleCan trigger symptom in controlled scenario
CausalMinimal change makes bug disappear
ReversibleReverting the change makes bug reappear
MechanisticCan point to exact code path / state transition
Framework Assumption Audit (Rule 7)

When fix involves framework/library behavior: list assumptions → read source code to verify → document in comments with source references.

2B: Search Knowledge Files (Rule 12)

Search bug-patterns.md and bug-records.md for matching patterns. Skip if files don't exist (see Phase 0 auto-init).

Match LevelAction
High (symptom + root cause match)Apply known fix, can skip remaining RCA
Medium (similar symptom)Reference strategy, verify
No matchFull investigation, must deposit after fix
2C: Impact Chain (Rule 3)
DimensionWhat to Check
CodeBug file → direct callers → indirect callers → deep callers
DataCorrupted records in DB/file/cache? Repair script needed?
TimeWhen introduced? Duration of exposure? Users affected?
EventMessage queues, WebSocket, background workers affected?
2D: Similar Issue Scan (Rule 3)

Scan ALL files for the same bug pattern, not just the reported file.

bash
rg -n "function_name\|similar_pattern" --glob "*.{ts,tsx,py,js}"

Phase 3: Scope + Prediction

Scope Accuracy Gate (Rule 2)
#GateMeaning
1Consumer ListAll consumers (callers/dependents) enumerated
2Contract ListModified contracts/interfaces/behaviors listed
3Invariant CheckMust-hold invariants listed
4Call Site EnumAll call sites enumerated and classified
5Duplicate ScanNo parallel implementation left unfixed
3A: Side Effect Prediction (Rule 4)
  1. Change Blueprint — What exactly will change
  2. Impact Ripple — L0 (code) → L1 (module) → L2 (feature) → L3 (system) → L4 (user)
  3. Blind Spot Check — Read references/blind-spots.md and execute every active check
  4. Go/No-Go Decision

Quick version (for Standard-tier, ≤5 LOC, 1 file):

markdown
## Quick Impact Check
- Change: [one-line description]
- Direct callers: [list or "none - local function"]
- Duplicates: [checked — none / found and planned]
- Could break: [prediction or "low risk - isolated"]
- Decision: GO
3B: Fix Strategy Comparison (>10 LOC, Complex only)
DimensionStrategy AStrategy B
LOC change
Impact scope
Regression risk
Rollback-able

Phase 4: Fix

  • Minimal change, prefer ≤50 LOC; justify if more
  • ONE change at a time, never batch unrelated fixes
  • Layer Rule (Rule 10): Before writing fix code, verify you're fixing the right layer:
Problem in…Fix…Do NOT fix…
Params/configConfig or param passingBusiness logic
Single componentThat componentFramework
Multiple components same issueFramework/base classEach component one by one
Docs vs code mismatchBoth sides in syncOnly one side
  • Pattern matching safety (Rule 11): regex, string match, name lookup → always consider boundary conditions
  • DB schema change? Generate Alembic migration:
    bash
    cd backend && alembic revision --autogenerate -m "describe change"

Phase 5: Verify + Review

5A: Regression Verification (Rule 5)
CategoryChecks
FunctionalUnit tests + integration + API + E2E + manual
PerformanceNo N+1 queries, no resource leaks, no response time increase
ConcurrencyThread-safe shared state, atomic operations, no race conditions

Test the entire impact chain (L0-L3), not just the original bug.

5B: Runtime Deployment Verification (Rule 6)
StepActionEvidence
1Clear Python bytecode cache__pycache__ removed
2Restart backend servicePID changed from X to Y
3Health check passes/docs returns 200
4Exercise the fixed code pathRequest triggers fixed logic

If NOT deployed → restart and re-verify before proceeding.

5C: Bug Summary + Code Review (Rule 9)
markdown
## Bug Summary [BUG-XXX]
- **Symptom**: [one-sentence user-visible problem]
- **Root Cause**: [one-sentence actual cause]
- **Fix**: [one-sentence fix description]
- **Files Modified**: [file1.py, file2.ts]
- **Severity**: P0/P1/P2

Output Bug Summary → run code-review skill → if review finds issues → fix → re-verify

Stop condition: Code review clean + regression passed + deployment verified + original bug fixed.

Special Checks
Bug TypeKey Checks
API BugFrontend → API → Schema → Service → DB chain; field completeness
DB MigrationModel changed → alembic revision --autogenerate; no migration = schema drift
System-levelDraw E2E chain; define handshake evidence per edge; insert probes first
Cross-SurfaceShared artifact → identify contract → consumer list → regression matrix

Phase 6: Knowledge Deposit + Self-Reflection

6.1 Update Knowledge Files (Rule 9)
FileWhen to Update
references/bug-records.mdEvery fix (project history)
references/bug-patterns.mdNew pattern / new fix strategy (universal)
references/blind-spots.mdNew blind spot discovered
6.2 Self-Reflection (Rule 9)
DimensionScore (1-5)Evidence
First-time correctness[1-5]Did the fix work on first attempt?
Scope accuracy[1-5]Did I find all affected areas?
Minimal change[1-5]Was the change as small as possible?
Side effect prediction[1-5]Did I predict all side effects?
Root cause depth[1-5]Did I fix root cause, not symptom?
Total[/25]
IssueWhat HappenedWhy I Missed ItPrevention
Regression Autopsy (when fix introduced a regression)
markdown
- **Original Bug**: [what was being fixed]
- **New Bug Introduced**: [what broke]
- **Why I didn't predict it**: [blind spot]
- **Classification**: [missed consumer / contract violation / edge case / ...]

Domain-Specific Checks

Bug TypeKey Checks
Backend/APISchema drift, timeout/retry, transactions, N+1, connection pool, ORM lazy loading
Frontend/UIState (useEffect deps, unmount), race conditions, CORS, hydration, overflow/Portal
System-levelCross-layer chain, async/streaming, IPC, routing
FrameworkRead source code first (Rule 7), verify assumptions with tests
AI/LLMTool binding modes, simulated vs native, streaming, token limits

Skill Delegation

TriggerDelegate To
Need new API endpointfullstack-developer
UI fix neededfrontend-design
Schema change neededdatabase-migrations
After fix (mandatory)code-review

Show full SKILL.md (786 more words)Show less

Anti-Patterns (FORBIDDEN)

ForbiddenCorrect
Fix without RCAHypothesis ladder first
Single hypothesis then fixList 3-5 hypotheses, verify each
Fix UI bug by code reading aloneGet runtime evidence first (Rule 8)
Skip consumer list for shared codeFill consumer list first
Tests pass but server runs old codeClear cache + restart + verify fix is live (Rule 6)
Fix code but ignore corrupted dataAssess data impact + repair if needed
Trust framework docs blindlyRead source code or run tests (Rule 7)
Fix one copy, miss the duplicateGrep function name; check both Path A and Path B
Pattern match without boundary checkAdd word boundaries / anchors / exact match (Rule 11)
Model changed but no migrationRun alembic revision --autogenerate
Use full workflow for a typoUse Quick Fix path (Phase 0 Trivial tier)
Skip self-reflectionMust score, analyze, and learn

Final Checklist

Core (Standard + Complex tiers)
#CheckPhase
1Severity (P0-P3) + Tier (Trivial/Standard/Complex) classified0
2Root cause passes 4 gates2A
3Bug pattern library + records searched2B
4Impact chain traced (code+data+time+event)2C
5Similar issue scan completed2D
6Scope passes 5 gates (incl. duplicate scan)3A
7Side effect prediction + blind spot check3A
8Regression verification ALL passed (L0-L3)5A
9Runtime deployment verified5B
10Bug Summary output + code-review passed5C
11Knowledge files updated6.1
12Self-reflection completed6.2
13If DB model changed: Alembic migration generated5
14User confirmed fix + no new bugsFinal
Trivial Tier Checklist (Quick Fix path only)
#CheckStatus
1Fix applied and tested (lint/test/manual)[ ]
2Bug record entry added[ ]
3No behavioral change introduced[ ]

OpenClaw Project Context

Architecture Map
backend/app/
├── api/v1/              # FastAPI routes (agents, auth, chat, skills, tools, profile)
├── core/
│   ├── graph/           # LangGraph StateGraph (agent_graph, nodes/llm_node, tool_node, prepare_node)
│   ├── langchain/       # LangChain tools (tools.py, shell_tool.py, e2b_tools.py)
│   ├── mcp/             # MCP server integration (pool.py)
│   ├── database.py      # SQLAlchemy async engine
│   └── security.py      # JWT auth
├── models/              # SQLAlchemy ORM models (agent, tool, user, skill)
├── schemas/             # Pydantic request/response schemas
├── services/            # Business logic (agent_executor, chat_service, tool_call_parser, ...)
├── middleware/           # Request logging, audit, error handling
└── main.py              # FastAPI app entry

frontend/src/
├── features/            # Feature modules (chat, settings, admin, knowledge, skills, agents)
│   ├── chat/            # ChatPageV2, MessageRenderer, ToolCallCard, SkillExecutionInline
│   └── ...
├── components/ui/       # shadcn/ui style components (dialog, switch, checkbox)
├── hooks/               # React hooks (useChatStream — SSE event handling)
├── store/               # Zustand state management
└── lib/                 # API client (api-client.ts), markdown utils
Tech Stack
LayerTechnology
BackendFastAPI + Python 3.11+
ORMSQLAlchemy 2.0 (async)
DBPostgreSQL (asyncpg) or MySQL (aiomysql)
MigrationsAlembic (backend/alembic/)
CacheRedis
AILangChain 0.3.x + LangGraph 0.4.x
Vector DBChromaDB
FrontendReact 18 + Vite + TypeScript
UIRadix UI + Tailwind CSS
StateZustand + TanStack Query
Testspytest (backend), Vitest (frontend)
DeployDocker Compose, supports PyInstaller desktop build
High-Risk Bug Zones
Backend Hot Zones
ZoneFilesWhy It's High-Risk
Simulated Tool Call Parsingservices/tool_call_parser.py, core/graph/nodes/llm_node.pyRegex-based; dual implementations; multi-arg edge cases
Agent Executorservices/agent_executor.py3000+ LOC; native + simulated modes; complex streaming
Tool Argument Remappingcore/graph/nodes/tool_node.pyLLM wrong param names → alphabetical guess
LLM Streaming (httpx)services/llm_manager.pyReasoning model fallback; SSE; reasoning_content
MCP Tool Integrationcore/mcp/pool.py, services/tool_service.pyMCP lifecycle; command vs HTTP; timeout
Skill Runtimeservices/skill_executor.py, services/skill_service.pyScript exec; env var injection; enhanced vs local
Chat Streamingservices/chat_service.pySSE events; client disconnect; async save
Memory Systemservices/unified_memory_manager.pyL1/L2; embedding scoring; slow queries
Frontend Hot Zones
ZoneFilesWhy It's High-Risk
SSE Chat Streamhooks/useChatStream.tsEvent parsing; reconnection; reasoning_content
Tool Call Renderingfeatures/chat/components/ToolCallCard.tsxDynamic display; error states; loading
Skill Execution UIfeatures/chat/components/SkillExecutionInline.tsxInline status; progress; error display
Markdown Rendererfeatures/chat/components/MarkdownRenderer.tsxNested code fences; special chars; XSS
Agent Editorfeatures/agents/AgentEditorPage.tsxComplex form state; tool/skill/KB associations
Zustand Storestore/State updates not re-rendering if reference unchanged
Two Code Paths for Agent Execution
Path A: Direct Executor (most common)
  chat API → chat_service → agent_executor.py → tool_call_parser.py → tool execution

Path B: StateGraph (LangGraph)
  chat API → chat_service → agent_graph.py → llm_node.py → tool_node.py → tool execution

When fixing anything in Path A, always check Path B for the same issue (and vice versa).

Known Duplicate Implementations
Function / FeaturePrimary LocationKnown Alternate Location
parse_simulated_tool_callsservices/tool_call_parser.pycore/graph/nodes/llm_node.py
Tool loading / bindingservices/agent_executor.pycore/graph/agent_graph.py
Token countingservices/token_counter.pyMay have inline counting in agent_executor.py
Memory managementservices/unified_memory_manager.pycore/graph/nodes/prepare_node.py
OpenClaw Common Framework Pitfalls (Rule 7)
AreaAssumptionReality
Config load orderFirst file has priorityOften last file wins (dict.update)
ORM lazy loadingRelations auto-loadDefault lazy, causes N+1
Async on WindowsSame as LinuxWindows uses ProactorEventLoop; run_dev.py forces SelectorEventLoop
Pydantic serializationmodel_dump() includes allexclude_unset=True changes behavior
LangChain tool bindingAll models support toolsReasoning models need simulated mode
__pycache__Python uses latest sourceStale .pyc can persist across restarts
Windows Development Environment Gotchas
IssueSymptomWorkaround
Path separators\ vs /Use pathlib.Path or os.path.join
asyncio event loopProactorEventLoop defaultrun_dev.py forces loop="asyncio"
__pycache__ file locksCan't delete while runningKill process FIRST, then clean
Console encodingGBK/CP936 defaultsys.stdout.reconfigure(encoding='utf-8')
Playwright on WindowsBrowser launch may failRuns in separate thread with own loop

Verification Commands (OpenClaw)

Backend
bash
cd backend
ruff check app/                                    # Lint
python -m pytest tests/ -v --tb=short              # Unit tests
python -m pytest tests/test_specific.py -v         # Specific test
alembic revision --autogenerate -m "check"         # DB migration check
Frontend
bash
cd frontend
npm run lint
npm run typecheck
npm test
npm run build
Backend Server Restart
powershell
Get-WmiObject Win32_Process -Filter "Name='python.exe'" | Where { $_.CommandLine -like "*run_dev*" }
Stop-Process -Id [PID] -Force
Get-ChildItem -Path "backend" -Recurse -Filter "__pycache__" -Directory | Remove-Item -Recurse -Force
Start-Process -FilePath "backend\venv\Scripts\python.exe" -ArgumentList "run_dev.py" -WorkingDirectory "backend"
Invoke-WebRequest -Uri "http://127.0.0.1:8000/docs" -UseBasicParsing -TimeoutSec 5

Reference Files

Living Data Files (update after every fix)
FilePurpose
references/bug-records.mdProject-specific bug history
references/blind-spots.mdSingle source of truth for AI blind spot registry
Pattern Libraries (domain knowledge)
FilePurpose
references/bug-patterns.mdUniversal bug pattern library (11 categories)
references/backend-patterns.mdBackend issues (API, ORM, LLM integration, OpenClaw-specific)
references/frontend-patterns.mdFrontend issues (React hooks, race conditions, CORS)
Detailed Guides
FilePurpose
references/system-rca.mdSystem-level RCA (cross-layer, multi-process bugs)
references/regression-matrix.mdComplete zero-regression verification matrix

Skill Evolution

Update this skill when:

  • Code review finds a bug that the workflow should have prevented
  • A recurring bug class repeats across fixes

Prefer updating specific sections over adding new rules. After updates, validate that the workflow is still coherent and not overly bureaucratic.

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 33 other files (scripts, references) in skills/bug-fixing of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • _meta.json
  • references/ai-blind-spots.md
  • references/backend-common-issues.md
  • references/backend-patterns.md
  • references/blind-spots.md
  • references/bug-guide.md
  • references/bug-patterns.md
  • references/bug-records-lookup-protocol.md
  • references/bug-records.md
  • references/caller-impact-protocol.md
  • references/cross-surface-regression.md
  • references/final-checklist.md
  • references/framework-assumption-audit.md
  • references/frontend-common-issues.md
  • references/frontend-patterns.md
  • references/knowledge-extraction-guide.md
  • references/output-templates.md
  • references/pre-fix-impact-prediction.md
  • references/rca-guide.md
  • … and 14 more

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Bug Fixing Openclaw next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Native Data FetchingCherryHQ/cherry-studio-app4k6 repos~2.9kAutomated safety check: NotesMIT
Debugging Executionsn8n-io/n8n207k—~2.6kAutomated safety check: PassCustom licence
Aoti Debugpytorch/pytorch104k1 repos~1.7kAutomated safety check: PassCustom licence
Herdr Throwaway Reproductionherdrdev/herdr43k—~2.4kAutomated safety check: PassApache-2.0

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Categories

Questions about Bug Fixing Openclaw

What does Bug Fixing Openclaw do?

Zero-regression bug fix workflow: triage → reproduce → root cause → impact analysis → fix → verify → knowledge deposit → self-reflect. Bug Fixing Openclaw is an agent skill from LeoYeAI/openclaw-master-skills. Zero-regression bug fix workflow: triage → reproduce → root cause → impact analysis → fix → verify → knowledge deposit → self-reflect.

When should I use Bug Fixing Openclaw?

Bug Fixing Openclaw fits situations like: : - Feature broken; incorrect behavior; errors/exceptions - Console errors/warnings even when feature appears functional - Regressions; degraded performance - Keywords: fix bug.

How do I install Bug Fixing Openclaw in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill bug-fixing-openclaw -a claude-code`. Or copy the skill folder (skills/bug-fixing in LeoYeAI/openclaw-master-skills) into .claude/skills/bug-fixing-openclaw in your project. Claude Code loads it when a task matches its description.

How do I install Bug Fixing Openclaw in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill bug-fixing-openclaw -a codex`. Or copy the skill folder (skills/bug-fixing in LeoYeAI/openclaw-master-skills) into .agents/skills/bug-fixing-openclaw in your project. Codex loads it when a task matches its description.

Can I use Bug Fixing Openclaw in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill bug-fixing-openclaw -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bug-fixing-openclaw, .gemini/skills/bug-fixing-openclaw, .github/skills/bug-fixing-openclaw and .opencode/skills/bug-fixing-openclaw in your project.

What does Bug Fixing Openclaw need to run?

Going by SKILL.md and its folder, Bug Fixing Openclaw needs the command-line tools its instructions call (npm, python, rg and ruff). Its frontmatter pre-approves these tools: read, write, execute, grep, glob.

Does Bug Fixing Openclaw access the network?

SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Bug Fixing Openclaw safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Bug Fixing Openclaw use?

Bug Fixing Openclaw is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Bug Fixing Openclaw use?

About 6.5k tokens (SKILL.md is roughly 26k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 56k tokens, read only when the agent opens those files.

What are the alternatives to Bug Fixing Openclaw?

Skills that share tags, products or a category with Bug Fixing Openclaw: Trellis Session Insight (mindfold-ai/Trellis, 15k stars), Native Data Fetching (CherryHQ/cherry-studio-app, 4k stars), Debugging Executions (n8n-io/n8n, 207k stars) and Aoti Debug (pytorch/pytorch, 104k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Bug Fixing Openclaw?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,160 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.