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search_documentation

Find documentation matches by searching the bundled skill tree and any local Synthesizer checkout. Returns hits with file paths, line numbers, and snippets.

Instructions

Search the bundled skill tree and any Synthesizer checkout docs.

Args: query: Words to look for. Matching is plain substring and token matching, not a query language.

Returns: A mapping with query, corpora_searched (a list of {corpus, root} recording what was actually covered), corpora_unavailable explaining, in a sentence each, any corpus that was not, files_scanned, hit_count, and hits. Each hit is {corpus, path, line, score, snippet} where snippet is an untrusted-content envelope. truncated records whether a cap bit, notes explains an unsearchable query, and error is present only when the search itself failed.

The bundled skill tree is always searched; a Synthesizer source
checkout is searched in addition to it when one is found, never
instead of it. Synthesizer's own documentation is not installed
by pip, so it is unavailable unless such a checkout exists.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and fully discloses behavior: plain substring/token matching, the exact result mapping, corpora coverage/unavailability, the untrusted-content envelope for snippets, truncation, notes, and error-only-on-failure. This is unusually transparent.

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?

The description is front-loaded with a one-sentence purpose and then structured into Args and Returns. It is dense and mostly efficient, but the lengthy return listing and a minor typo ('cap bit') keep it from a top score.

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

Completeness5/5

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

For a one-parameter search tool, the description covers input semantics, output shape, hit entry fields, truncation, notes, errors, and corpus availability. Nothing an agent needs to call it correctly is missing.

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

Parameters5/5

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

Schema description coverage is 0%, but the description compensates fully by defining query as words to look for and specifying plain substring/token matching, not a query language. This adds exactly the semantic meaning an agent needs beyond the bare string type.

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 opening sentence uses a specific verb ('Search') and names the two corpora ('bundled skill tree', 'Synthesizer checkout docs'), clearly distinguishing this from example-finding or grid-inspection siblings. It does not merely restate the tool name.

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?

The description clearly explains the tool's scope and availability: the bundled skill tree is always searched, while Synthesizer docs are only searched when a checkout exists and never instead of the bundled tree. It does not explicitly name an alternative tool, but the usage context is clear.

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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