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nachogeinfor-ops

code-context

search_repo

Search codebase using semantic queries to locate code fragments for conceptual topics like validation, caching, or authentication. Returns ranked results with file paths and context.

Instructions

Semantic search over the indexed codebase. Use this INSTEAD of Grep when the query is conceptual (e.g. 'where do we validate input', 'how is caching implemented', 'authentication flow'). Returns ranked code fragments with file path, line range, snippet, score and a one-line why excerpt. For exact-string lookup, Grep is still better.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
top_kNo
scopeNoOptional repo-relative path prefix to constrain results.
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses return fields (file path, line range, snippet, score, why excerpt). Lacks details on auth or side effects, but for a search tool this is comprehensive.

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?

Three concise sentences, front-loaded with purpose. Every sentence is informative with no redundancies.

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?

Despite missing annotations and output schema, the description adequately covers purpose, usage, and return format. Could mention indexing requirements, but sufficient for typical use.

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

Parameters2/5

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

Schema description coverage is only 33% (only 'scope' described). The tool description does not add meaning for 'query' or 'top_k' beyond the schema, leaving gaps in understanding parameter behavior.

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 it performs 'semantic search over the indexed codebase', distinguishing it from sibling tools like find_definition and find_references. It uses a specific verb+resource combination and contrasts with Grep.

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 (conceptual queries) and when not to (exact-string lookup, where Grep is better), with concrete examples. Provides clear guidance on alternatives.

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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