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mark-burg

reference-mcp

by mark-burg

search_code

Search a code repository using exact/regex text matching or natural-language queries. Returns matching lines or symbols with file and line numbers.

Instructions

Search the repo, filtered and paginated. mode='lexical' does exact/regex text matching; mode='semantic' ranks symbols by natural-language meaning ("where is auth handled?").

Returns file:line plus the matching line (lexical) or matched symbol (semantic).
Use this when you do NOT know the exact symbol name. Prefer find_symbol /
find_references when you DO — they are structural and far more precise.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesText or regex to search for.
modeNo'lexical' (default, exact/regex) or 'semantic' (natural-language meaning; requires the optional 'semantic' extra).lexical
regexNoTreat query as a regular expression.
path_globNoRestrict to paths matching a glob, e.g. '*/api/*.py'.
case_sensitiveNoCase-sensitive match.
limitNoMax hits to return.
offsetNoPagination offset.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Describes return format (file:line plus matched text/symbol) and pagination. With no annotations, it provides good transparency but misses clarifying interactions between regex and modes, and doesn't mention auth/rate limits, though these are not critical for a search tool.

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?

Four sentences, front-loads primary purpose, then explains modes, results, and usage guidance. No redundancy or fluff.

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?

With output schema present, the description adequately covers key behaviors (mode difference, pagination, usage guidance) without needing to detail every parameter. It is complete for an agent to select and invoke correctly.

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 covers all 7 parameters. Description adds value by explaining lexical vs semantic mode behavior and result differences, going beyond what the schema provides. A solid improvement over baseline 3.

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?

Clearly states it searches the repo with filtering and pagination, and distinguishes two modes. It also contrasts with siblings by noting when to use structural tools instead.

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

Usage Guidelines5/5

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

Explicitly tells when to use this tool (when exact symbol name unknown) and when not to (prefer find_symbol/find_references). Also notes semantic mode requires optional extra.

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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