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Suyash2013

omni-rag-mcp

by Suyash2013

search

Find relevant information in indexed files using semantic or hybrid search with natural language queries.

Instructions

Search indexed files using semantic or hybrid search.

Args: query: Natural language query. n_results: Optional number of results to return (default: 10).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
n_resultsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description carries the full burden but only states it uses 'semantic or hybrid search' without explaining behavioral implications like whether results are ranked, if it supports exact matches, or any side effects. Minimal transparency.

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 with two sentences and a parameter list. It front-loads the purpose, and every sentence is meaningful, with no redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the number of sibling search tools and lack of annotations, the description is incomplete. It does not explain the output schema, the meaning of semantic/hybrid search, or how results differ from other search tools. The agent lacks sufficient context to use it optimally.

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 0%, so the description adds meaning by describing 'query' as a natural language query and noting n_results defaults to 10. This adds value beyond schema types, but the explanation is brief and does not cover any optional constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches indexed files with semantic or hybrid search, providing a specific verb and resource. However, it does not differentiate from sibling tools like search_codebase or search_by_file, which also search files, so it lacks sibling differentiation.

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?

No guidance on when to use this tool versus alternatives. The description does not mention when semantic/hybrid search is appropriate or when to use other search tools, leaving the agent without context for selection.

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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