Agent Reliability

dev.agentreliability/agent-reliability · v0.6.14 · agents-and-memory

Agent Reliability is healthy: it completed an MCP handshake in 3637 ms and exposes 9 tools. It scores 60/100.

Testing, benchmarking and auditing autonomous AI agents — methods, harnesses, evidence

Endpoint: https://agentreliability.dev/mcp?via=manifest (streamable-http)

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Score 60/100

health17 / 25
authEase15 / 15
toolQuality15 / 15
maintenance5 / 15
adoption0 / 10
usage0 / 10
security8 / 10

Scoring v0.3, computed 2026-10-15T02:36:22.716Z.

Health history

Checked (UTC)StatusLatencyError
2026-10-14T23:10:41.506ZHealthy3637

Tools (9)

searchFull-text search over the knowledge graph. Matching ignores accents and apostrophes, so query in the user's own words; every hit carries the fields it matched and a score. BM25 relevance: each query term is weighted by how RARE it is in this corpus and by where it hits (name 3, tags 2, questions 2,
get_entityFetch one knowledge object by id, with its claims and the sources each claim cites. Use this once search, answer or get_topic has given you an id. An unknown id is not a dead end: the answer names near-miss ids you can retry with.
get_topicList the knowledge objects carrying a tag (topics are content-backed tags). PAGED: 25 objects by default, 200 at most, and a response budget of about 64 KB per call — a page over budget comes back shorter WITH a next_cursor, never truncated. Read next_cursor and call again to continue, and its absen
answerAnswer a question from the corpus, or refuse. Returns only the claims that bear on the question, each with the sources it cites and its editorial confidence. When the corpus cannot answer, answered is false and abstention_reason plus missing_topics say what was not covered — a refusal is a real resu
get_sourcesThe instance's source registry — each entry with its evidence tier, reliability and access date. PAGED: 25 entries by default, 200 at most, and a response budget of about 64 KB per call — a page over budget comes back shorter WITH a next_cursor, never truncated. Read next_cursor and call again to co
get_relatedGraph neighbours of an object: outgoing and incoming relations, each with its relation type. PAGED: 25 relations by default, 200 at most, and a response budget of about 64 KB per call — a page over budget comes back shorter WITH a next_cursor, never truncated. One cursor walks both directions, outgo
get_latestMost recently verified knowledge objects (freshness signal). Use this to judge how current the corpus is, or to see what changed since you last read it. It ranks by verification date and ignores your topic entirely — use search or get_topic when you want objects that are relevant rather than recent.
get_overviewCorpus overview: what this instance knows, counts by type, published tags, freshness. Use this first when you land here and do not yet know whether this corpus can answer your question.
compareTwo to six knowledge objects side by side: their cards, every indexed attribute as a matrix (the same fields api/index.json publishes, null where an object does not say), the tags they share, the relations that run between them, the neighbours they have in common, and each one's claims with sources