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Platano78

Smart-AI-Bridge

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Search your codebase using natural language questions to locate files and lines that implement specific features, with optional LLM-generated context.

Instructions

Natural-language search across the codebase: combines grep-style matching with optional LLM summarization to answer 'where is X handled?' or 'what files implement Y?' Returns a summary + the matching file:line list, not raw file contents. Use when you DON'T already know which file to look at. For a deep analysis of ONE known file, use analyze_file. For a structured question across a known set of files (glob patterns), use batch_analyze. depth:'shallow' is fast grep; depth:'deep' adds LLM-generated context per match. Read-only: walks the filesystem and reads matched files but never writes. Returns: {success, summary (LLM- or template-generated answer), files_found:[paths], search_patterns:[strings actually grepped], evidence:[{file, line, match}] (capped at 15), tokens_saved, processing_time_ms, depth, backend_used}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYesNatural language question about the codebase (e.g., "where is user authentication handled?")
optionsNo
Behavior4/5

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

With no annotations provided, the description carries the full burden. It states the tool is read-only ('never writes'), describes the search process (grep + optional LLM), and details the return format including caps (evidence capped at 15). However, it does not mention auth needs or rate limits, which is acceptable for a read-only tool.

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 well-structured: it starts with the core purpose, then usage guidelines, then details. It is not overly verbose, though it could be slightly more concise by separating the return format into its own section. The front-loading of key information aids quick comprehension.

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?

Given no output schema, the description fully specifies the return structure and caps. It covers behavioral traits, parameter meanings, and usage contexts. It distinguishes from all relevant sibling tools. The description is complete and leaves no major gaps for an agent to invoke the tool correctly.

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 description coverage is 50% (top-level 'options' missing description). The description adds value by explaining the 'depth' parameter's behavior and the purpose of 'question', but does not elaborate on 'scope', 'maxFiles', or 'backend' beyond what's in the schema. Overall, it provides moderate additional context.

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 the tool performs natural-language search across the codebase, returning a summary and file:line matches. It explicitly distinguishes itself from sibling tools by stating when to use each (analyze_file for a known file, batch_analyze for structured queries). This provides a specific verb+resource and differentiates from alternatives.

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?

The description provides explicit usage guidance: 'Use when you DON'T already know which file to look at' and instructs to use analyze_file or batch_analyze for other scenarios. It also explains the depth options (shallow vs deep) and their use cases, giving clear context and exclusions.

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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