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library_lookup

Find standard-library declarations by name or a few words before calling a library function, so names and arguments are not invented. Get each match's signature, effects, and purpose.

Instructions

Find standard library declarations by name or by a few words (case-insensitive; every word must occur in the module name, the signature or the purpose). Each match is given with its signature, effects and purpose. Use it before calling a library function, so that names and arguments are not invented.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesa name or a few words, such as `get_with` or `read file`

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does reasonably well: it discloses the match algorithm (case-insensitive, every word must appear in module name, signature or purpose) and the shape of each result (signature, effects, purpose). It omits ranking, result limits, and search scope beyond 'standard library', which keeps it below 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.

Conciseness5/5

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

Two sentences, front-loaded with what is found and how matching works, then the usage cue. The parenthetical earns its place by defining the match rule; nothing is redundant.

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?

For a single-parameter lookup with no annotations and no output schema, the description covers scope, matching semantics, returned fields, and intended workflow. Only secondary details such as result ordering or match limits are missing, which is acceptable here.

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

Parameters4/5

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

Schema coverage is 100% and the schema already supplies examples ('get_with', 'read file'), so the baseline would be 3. The description goes further by explaining how the query string is interpreted (multi-word AND across name/signature/purpose, case-insensitive), which is genuine semantics the schema does not convey.

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

Purpose4/5

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

States a specific verb ('Find') and a specific resource ('standard library declarations'), plus the matching rule. It is clearly distinguishable from action siblings like run/format/check, though it never contrasts itself with the plausibly overlapping `definition` or `cheat_sheet` siblings, so it stops short of a 5.

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?

Gives an explicit trigger: 'Use it before calling a library function, so that names and arguments are not invented.' That is actionable context, but there are no exclusions or alternatives named (e.g. when to prefer `definition` or `cheat_sheet` instead).

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