Structured failure knowledge for AI agents — dead ends, workarounds, error chains
Structured failure knowledge for AI agents — dead ends, workarounds, error chains
AI assistants reliably fumble two kinds of problems: known-failed code fixes, and country-specific real-world rules they've never been exposed to in training. deadends.dev now covers both:
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| Tool | What it does |
|---|---|
| lookup_error | Match an error message against 2000+ known patterns |
| get_error_detail | Full canon by ID |
| list_error_domains | All 54 domains with counts |
| search_errors | TF-IDF keyword search across all domains |
| list_errors_by_domain | All errors in a domain |
| list_errors_by_country | All country-scoped dead ends for an ISO alpha-2 code |
| get_country_summary | Country-level summary (entries, fix rate, domain mix) |
| batch_lookup | Look up multiple errors at once (max 10) |
| get_domain_stats | Domain quality metrics and confidence levels |
| get_error_chain | Traverse the error transition graph |
| report_outcome | Report whether a workaround worked (feeds back into success rates) |
{
"mcpServers": {
"deadend": {
"serverUrl": "https://deadends.dev/mcp",
"type": "http"
}
}
}Configuration as documented by the project. Restart the client after saving.
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