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codeinfuse

Search code context using natural language queries. Review a list of numbered matches, then select one to view its full context.

Instructions

INTERACTIVE code context search. First call (selection=0): Returns numbered list of matches. CRITICAL: After first call, you MUST IMMEDIATELY call AskUserQuestion to let user pick a number - DO NOT skip this step or pick for them. Second call (selection=N): Returns full context for selection N. User selections are logged for training data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language description of what you want to do
top_kNoNumber of results to show (default 10)
selectionNoUser's selection (1-N). If 0 or omitted, shows search results list.
Behavior5/5

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

With no annotations, the description fully discloses the interactive behavioral traits: the two-phase execution, mandatory user judgment call, and data logging for training purposes. No contradictions with non-existent annotations.

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 essential sentences: states purpose, explains first call, issues a critical warning with mandatory action, describes second call and logging. No wasted words, well front-loaded.

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 interactive complexity and lack of output schema, the description covers the core workflow, mandatory user interaction, and logging. Could elaborate slightly on return format details, but sufficient for effective use.

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% with adequate parameter descriptions. The description adds critical context on how the 'selection' parameter controls the two-step flow and that 'query' is a natural language description, but does not introduce new parameter-level meaning beyond the schema.

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 'INTERACTIVE code context search', specifies a two-step interaction (first call returns numbered list, second call returns full context), and distinguishes from siblings like 'search_code' by emphasizing the interactive user-driven selection process.

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?

Provides explicit step-by-step instructions: first call with selection=0, then MUST call AskUserQuestion, then second call with selection=N. Warns against skipping or picking for the user, ensuring correct usage.

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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