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Structured failure knowledge for AI agents — dead ends, workarounds, error chains

Project description

deadends.dev

Errors Domains MCP Tools PyPI License

Structured failure knowledge for AI coding agents.

501 error entries across 14 domains. When AI agents encounter errors, they waste tokens on approaches that are known to fail. deadends.dev tells agents what NOT to try, what actually works, and what error comes next.

Website: deadends.dev · MCP Server: Smithery · PyPI: deadends-dev · API: /api/v1/index.json

Installation

pip install deadends-dev

Requirements: Python 3.10+

MCP Server

The MCP server exposes 7 tools for AI coding agents:

Tool Description
lookup_error Match an error message against 501 known patterns. Returns dead ends, workarounds, and error chains.
get_error_detail Get full details for a specific error by ID (e.g., python/modulenotfounderror/py311-linux).
list_error_domains List all 14 error domains and their counts.
search_errors Fuzzy keyword search across all domains (e.g., "memory limit", "permission denied").
list_errors_by_domain List all errors in a specific domain, sorted by fix rate, name, or confidence.
batch_lookup Look up multiple error messages at once (max 10).
get_domain_stats Get quality metrics for a domain: avg fix rate, resolvability, confidence breakdown.

Local (Claude Desktop / Cursor)

Add to ~/.claude/claude_desktop_config.json:

{
  "mcpServers": {
    "deadend": {
      "command": "python",
      "args": ["-m", "mcp.server"],
      "cwd": "/path/to/deadend.dev"
    }
  }
}

Hosted (Smithery — no local setup)

Install via Smithery:

# Claude Code
npx -y @smithery/cli@latest install deadend/deadends-dev --client claude

# Cursor
npx -y @smithery/cli@latest install deadend/deadends-dev --client cursor

Or connect directly: https://server.smithery.ai/deadend/deadends-dev

Example Response

When an agent encounters ModuleNotFoundError: No module named 'torch', the lookup_error tool returns:

## ModuleNotFoundError: No module named 'X' (Python 3.11+)
Resolvable: true | Fix rate: 0.88

### Dead Ends (DO NOT TRY):
- pip install X with system Python (fails 70%): venv not activated

### Workarounds (TRY THESE):
- Create venv, activate, then pip install (works 95%)
- Use python -m pip install instead of bare pip (works 90%)

Quick Start — Python SDK

from generator.lookup import lookup, batch_lookup, search

# Single error lookup
result = lookup("ModuleNotFoundError: No module named 'torch'")

# What NOT to try (saves tokens and time)
for d in result["dead_ends"]:
    print(f"AVOID: {d['action']} — fails {int(d['fail_rate']*100)}%")

# What actually works
for w in result["workarounds"]:
    print(f"TRY: {w['action']} — works {int(w['success_rate']*100)}%")

# Batch lookup (multiple errors at once)
results = batch_lookup([
    "ModuleNotFoundError: No module named 'torch'",
    "CUDA error: out of memory",
    "CrashLoopBackOff",
])

# Keyword search
hits = search("memory limit", domain="docker", limit=5)

Quick Start — CLI

pip install deadends-dev
deadends "CUDA error: out of memory"
deadends --list  # show all known errors

API Endpoints

Endpoint Description
/api/v1/match.json Lightweight regex matching (fits in context window)
/api/v1/index.json Full error index with all metadata
/api/v1/{domain}/{slug}/{env}.json Individual error canon (example)
/api/v1/openapi.json OpenAPI 3.1 spec with response examples
/api/v1/stats.json Dataset quality metrics by domain
/api/v1/errors.ndjson NDJSON streaming (one error per line)
/api/v1/version.json Service metadata and endpoint directory
/llms.txt LLM-optimized error listing (llmstxt.org standard)
/llms-full.txt Complete database dump
/.well-known/ai-plugin.json AI plugin manifest
/.well-known/agent-card.json Google A2A agent card
/.well-known/security.txt Security contact (RFC 9116)

Covered Domains (14)

Domain Errors Examples
python 86 ModuleNotFoundError, TypeError, KeyError, MemoryError, RecursionError
node 61 ERR_MODULE_NOT_FOUND, EACCES, EADDRINUSE, heap OOM, ERR_REQUIRE_ESM
docker 43 no space left, exec format error, bind address in use, healthcheck
git 34 failed to push, merge conflicts, detached HEAD, stash apply, tags
kubernetes 34 CrashLoopBackOff, ImagePullBackOff, OOMKilled, RBAC forbidden, HPA
go 32 nil pointer, unused import, interface conversion, slice out of range
nextjs 30 hydration failed, dynamic server, searchParams, metadata, Suspense
aws 29 AccessDenied, S3 NoSuchBucket, Lambda timeout, SQS, Secrets Manager
react 28 invalid hook call, too many re-renders, unique key, context, act()
terraform 27 state lock, cycle, provider not found, moved block, backend init
cuda 25 OOM, device-side assert, NCCL, cuDNN, nvcc not found, kernel image
typescript 25 TS2307, TS2322, TS2345, TS2532, TS7053, TS2769, TS18048
pip 24 build wheel failed, conflicting deps, externally-managed, hash mismatch
rust 23 E0382 borrow, E0308 mismatch, E0277 trait, E0106 lifetime, E0507

ErrorCanon Data Format

Each error is a JSON file with:

{
  "error": { "signature": "...", "regex": "...", "domain": "..." },
  "verdict": { "resolvable": "true|partial|false", "fix_success_rate": 0.88 },
  "dead_ends": [{ "action": "...", "why_fails": "...", "fail_rate": 0.75 }],
  "workarounds": [{ "action": "...", "success_rate": 0.92, "how": "..." }],
  "transition_graph": { "leads_to": [...], "preceded_by": [...] }
}

AI Agent Integration — 18 Discovery Formats

Every page on deadends.dev includes machine-readable data in 18 formats:

Format Location Purpose
JSON API /api/v1/{id}.json RESTful error data per canon
match.json /api/v1/match.json Compact regex-only file (load entire DB into context)
index.json /api/v1/index.json Master error index with metadata
stats.json /api/v1/stats.json Dataset quality metrics per domain
errors.ndjson /api/v1/errors.ndjson Streaming NDJSON for batch processing
OpenAPI /api/v1/openapi.json Full API spec with response examples
JSON-LD Every <head> Schema.org TechArticle + FAQPage
ai-summary Every page <pre id="ai-summary"> KEY=VALUE blocks
llms.txt /llms.txt llmstxt.org standard
llms-full.txt /llms-full.txt Complete database dump
ai-plugin.json /.well-known/ OpenAI plugin manifest
agent-card.json /.well-known/ Google A2A protocol
security.txt /.well-known/ RFC 9116 security contact
robots.txt /robots.txt 34 AI crawlers explicitly welcomed
CLAUDE.md /CLAUDE.md Claude Code instructions
AGENTS.md /AGENTS.md OpenAI Codex CLI instructions
.clinerules /.clinerules Cline AI instructions

Development

pip install -e ".[dev]"

# Full pipeline (validate → generate → build → test)
python -m generator.pipeline

# Individual steps
python -m generator.bulk_generate     # Generate canons from seeds
python -m generator.build_site        # Build static site
python -m generator.validate          # Validate data + site
python -m pytest tests/ -v            # Run tests

Contributing

Add error definitions to generator/bulk_generate.py or create JSON files directly in data/canons/.

python -m generator.validate --data-only  # Validate before submitting

License

MIT (code) · CC BY 4.0 (data)

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