tentra

query_symbols

Search for code symbols by name using fuzzy matching to analyze function, class, and variable relationships within codebases.

Instructions

Search for symbols by name or qualified name using fuzzy trigram matching. Replaces 10+ grep calls. Returns symbol kind, file path, fan-in/out, semantic role.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "snapshot_id": "<snapshot_id>",
      "q": "<q>"
    },
    "name": "query_symbols"
  }
}

Input Schema

Name	Required	Description
`snapshot_id`	Yes	Snapshot ID to query against
`q`	Yes	Fuzzy search query (symbol name or qualified name)
`kind`	No	Filter by symbol kind
`role`	No	Filter by semantic role slug (e.g. "service", "repository")
`limit`	No	Max results to return (default 50)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.2.0Apr 18, 2026

TDQS

A3.7/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses behavioral traits like 'fuzzy trigram matching' and the return format ('symbol kind, file path, fan-in/out, semantic role'), but doesn't cover aspects like rate limits, authentication needs, or error handling. It adds value beyond the schema but isn't comprehensive.

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 appropriately sized and front-loaded, with every sentence earning its place: it states the purpose, provides a performance comparison, and details the return format efficiently in three concise sentences without waste.

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 the complexity (5 parameters, no output schema, no annotations), the description is moderately complete. It covers the purpose, search method, and return values, but lacks details on error cases, pagination (beyond the limit parameter), or how results are ordered. Without an output schema, more return format explanation would be helpful.

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 100%, so the schema already documents all parameters thoroughly. The description adds context by mentioning 'fuzzy trigram matching' for the 'q' parameter and listing return fields that relate to parameters like 'kind' and 'role', but doesn't provide additional syntax or format details beyond the schema. Baseline 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's purpose with specific verbs ('Search for symbols') and resources ('symbols by name or qualified name'), and distinguishes it from siblings by mentioning 'Replaces 10+ grep calls', which implies it's a specialized search tool unlike broader analysis tools like analyze_codebase or get_symbol_neighbors.

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 implies usage for fuzzy symbol searching, but doesn't explicitly state when to use this tool versus alternatives like find_similar_code or get_symbol_neighbors. It mentions replacing grep calls, which suggests a specific context, but lacks clear exclusions or named alternatives.

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