Skip to main content
Glama

codebase_context_search

Search across database schemas, API specs, and infrastructure configs using natural language queries to find relevant domain knowledge and infrastructure details.

Instructions

Semantic search across context artifacts (database schemas, API specs, infra configs, etc.) defined in .socraticodecontextartifacts.json. Auto-indexes on first use and auto-detects stale artifacts. Use this to find relevant infrastructure or domain knowledge.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language search query (e.g. 'tables related to billing', 'authentication endpoints', 'deployment resource limits').
projectPathNoAbsolute path to the project directory.
artifactNameNoFilter search to a specific artifact by name (e.g. 'database-schema'). Omit to search across all artifacts.
limitNoMaximum number of results to return. Default: 10.
minScoreNoMinimum RRF score threshold (0-1). Results below this are filtered out. Default: 0.10 (override globally via SEARCH_MIN_SCORE env var). Set to 0 to disable filtering.
Behavior4/5

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

No annotations provided, so the description carries the burden. It discloses that the tool 'auto-indexes on first use and auto-detects stale artifacts,' which are side effects. However, it doesn't explicitly state whether it's read-only or details on return format.

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, each serving a purpose: first sentence defines scope and auto-behavior, second states usage. No wasted words; front-loaded with key info.

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?

Given no output schema and 5 parameters, the description explains the source file and auto-indexing but does not describe the result format or how to interpret scores. It is adequate but could be more complete regarding output.

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?

Input schema has 100% coverage with descriptions for all 5 parameters. The description does not add extra parameter-level information beyond the schema, so 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 clearly states the tool performs semantic search over context artifacts (database schemas, API specs, etc.) defined in a specific file. This distinguishes it from sibling tools like codebase_search (general search) by specifying the resource type and config source.

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 description says 'Use this to find relevant infrastructure or domain knowledge' but does not explicitly mention when not to use it or contrast with alternatives like codebase_search. This is a clear usage context but lacks explicit exclusions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/giancarloerra/SocratiCode'

If you have feedback or need assistance with the MCP directory API, please join our Discord server