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duysolo

codebaxing

by duysolo

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Read-onlyIdempotent

Find relevant code chunks using natural language queries. Returns ranked results with file paths and line numbers to speed up code navigation and understanding.

Instructions

Semantic search for code. Returns ranked code chunks with file paths and line numbers.

Examples:

  • search(question="authentication login flow")

  • search(question="user model", language="python", symbol_type="class")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoCodebase path for auto-loading
languageNoFilter by language
questionYesNatural language search query
n_resultsNoNumber of results
symbol_typeNoFilter by symbol type
Behavior3/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the agent knows this is a safe, read-only operation. The description adds value by describing the return format ('ranked code chunks with file paths and line numbers'), but does not disclose additional behavioral details such as whether results are transient or depend on an index. With annotations present, this level of detail is adequate.

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?

The description is extremely concise: two sentences and two examples. The first sentence front-loads purpose and output format. Examples are compact and directly demonstrate typical usage. There is no redundancy or wasted text.

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?

Given the tool's moderate complexity (5 parameters, no output schema), the description covers the core functionality and output format. However, it omits important context such as whether an index must be built first (sibling 'index' suggests a dependency), or how the ranking works. The presence of good annotations partly compensates, but a mention of prerequisites would make it complete.

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 coverage is 100% for all 5 parameters, providing baseline descriptions. The description's examples illustrate usage of 'question', 'language', and 'symbol_type', but these do not add meaningful semantics beyond what the schema already conveys. The description does not clarify how 'semantic search' leverages these parameters or what values are valid for 'language' or 'symbol_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 description clearly states 'Semantic search for code' and specifies that it returns ranked code chunks with file paths and line numbers. This is a specific verb+resource combination and easily distinguishes from sibling tools like index, stats, or memory operations.

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

Usage Guidelines2/5

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

The description does not provide any guidance on when to use this tool versus alternatives. For example, it does not mention prerequisites like needing to run 'index' first, nor does it specify when a different search approach (like grep or exact match) would be more appropriate. The user must infer usage from the examples alone.

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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