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EasyModeOnly

@ezquill/mcp-server

by EasyModeOnly

search_project

Read-only

Find where something is discussed in a writer's project by meaning, not keywords. Describe what you need, and get results ranked by similarity to your query.

Instructions

Search a project semantically — by meaning, not keywords. Use this to find where something is discussed when you do not know what words the writer used. Results are ordered by similarity; there is no relevance score and no threshold.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoDefault 10, maximum 50.
queryYesA question or a description of what you are looking for.
projectIdYes
sourceTypesNoNarrow the search. Omit to search everything.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true, and the description adds useful behavioral context: results are ordered by similarity, with no relevance score and no threshold. This goes beyond the annotation and helps the agent set expectations. It doesn't cover all edge cases (e.g., empty results, pagination), but for a read-only search it is reasonably transparent.

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 two sentences with no filler. The core semantic-search purpose and the key behavioral caveats (ordering, no threshold) are front-loaded. Every sentence earns its place.

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 lack of an output schema, the description could clarify what the results actually contain (e.g., a list of matches with snippets). It does mention ordering and lack of threshold, but not the result shape. However, since sibling tools like get_entity and read_scene likely clarify the object types, and the annotations cover safety, the description is reasonably complete for the agent's needs.

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 75%, which is moderate. The description does not add any parameter-specific details beyond what the schema already provides (e.g., limit default, query format, sourceTypes narrowing). Since it neither compensates for a low-coverage schema nor adds value on top, a baseline of 3 is appropriate.

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 states a specific verb+resource ('Search a project semantically') and clearly distinguishes from keyword search by emphasizing 'by meaning, not keywords'. It also explains the use case ('when you do not know what words the writer used'), making the purpose unambiguous and distinct from sibling list/get tools.

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

Usage Guidelines4/5

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

It provides an explicit condition for use ('when you do not know what words the writer used'), which tells the agent when to choose this over other tools. However, it does not explicitly mention when not to use it or name alternative tools, so it stops short of full when/when-not guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.