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CosmGrid

Local MCP Dev Runner

by CosmGrid

Search project text

search_text

Find exact text strings in project files with controlled output limits. Use this tool for plain-text searches that avoid regex complexity and shell execution.

Instructions

Search for a fixed text string in project files with bounded output; regex and shell execution are not used.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNo.
queryYes
projectYes
maxResultsNo
caseSensitiveNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
projectYes
resultsYes
truncatedYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv2.0.0

TDQS

A3.9/5.0
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, and it spends it well: it discloses that matching is literal, results are capped ('bounded output'), and — critically — that regex and shell execution are explicitly not used, preventing dangerous assumptions about ReDoS or command injection. It omits recursion scope and binary/hidden file handling, but the most safety-relevant boundaries are stated.

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?

A single front-loaded sentence where every clause earns its place: the action comes first, then the output-bounding constraint, then the two safety exclusions. There is no filler and no repetition of schema defaults like maxResults=100 or caseSensitive=false.

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

Completeness3/5

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

The output schema exists, so return values need not be explained, and the description covers the core invocation-safe facts. However, with 5 parameters, 0% schema coverage, and zero annotations, the absence of any guidance on search scope (recursion, how path interacts with project) and no sibling routing leaves the agent with adequate-but-gappy information.

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 0%, so the description must compensate. It adds meaning for query ('fixed text string' = literal, not regex) and maxResults ('bounded output'), but provides nothing for project, path, or caseSensitive, which must be inferred from parameter names alone. That is partial compensation for a significant coverage gap.

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 uses a specific verb and resource — 'Search for a fixed text string in project files' — and adds two scoping constraints ('fixed text string', 'bounded output'). These constraints distinguish it from siblings like find_files (filename search), replace_text (text mutation), and run_script (shell execution) without needing to open the schema.

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

Usage Guidelines3/5

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

The exclusions 'regex and shell execution are not used' imply when NOT to use this tool, but the description never names the alternative to prefer for regex or shell-based search (e.g., run_script, grep-style tools). Usage context is implied rather than explicit, so the agent must infer routing from sibling tool names.

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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