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Aayat AI

Error known ($0.005)

error-known
Read-only

Is this error known? Paste an error message or stack trace (and optionally the library): it is cleaned of paths and line numbers, then searched in the library's own GitHub issues, all GitHub issues and Stack Overflow, returning the best matches with status (closed, accepted answer...), links and excerpts. For a likely fix use /error/explain. Price: $0.005 in USDC per call (x402 or prepaid credits). In the free trial.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
libraryNoThe package the error comes from, to search its own issues first.
messageYesThe error message (a stack trace is fine; paths and line numbers are stripped).
ecosystemNoPackage ecosystem: npm, pypi, crates (Rust) or go (Go modules).npm

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
knownYes
queryYesThe cleaned-up phrase that was searched.
libraryNo
matchesYesBest matches first.
sourcesYes
summaryYes
checkedAtNo
repositoryNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations cover the safety profile (readOnlyHint, openWorldHint), and the description adds genuinely useful behavior beyond them: inputs are cleaned of paths and line numbers, three search sources are queried, and results carry status, links and excerpts. It also discloses pricing ($0.005 USDC per call, x402 or prepaid, free trial), which no structured field conveys. It doesn't explain result ranking or result-count limits, keeping it short of a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the key question and the search scope, then the alternative, then pricing. The middle sentence is dense but every clause carries information; only the pricing mention slightly competes with the functional framing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, the description needn't detail return values, and it nonetheless sketches them (matches, status, links, excerpts). Combined with 100% schema coverage and annotations covering safety, an agent has enough to call it correctly; only edge-case behavior (empty results, rate/cost interaction with the free trial) is left implicit.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents library, message and ecosystem (including the enum and defaults). The description reiterates that library is optional and that paths/line numbers are stripped, but adds no syntax or format detail beyond what the schema provides. Baseline 3 is correct.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a concrete verb+resource (search pasted error messages across the library's GitHub issues, all GitHub issues, and Stack Overflow) and explicitly distinguishes itself from the sibling error-explain tool. An agent can tell immediately this answers 'is this error known?' rather than 'how do I fix it?'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly routes the agent to /error/explain when a likely fix is wanted, which is clear alternative-handling for the nearest sibling. It doesn't state exclusions (e.g. what happens for very short or non-error inputs) beyond the schema's minLength, but the core when-to-use is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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