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find_tests

Find test files for any source file via naming patterns and reverse import lookup. Optionally narrow to tests referencing a specific symbol, and run them with the test bridge.

Instructions

Find test files for a source file (naming + import reverse lookup). Run them? test_bridge. AUTO-FRESH: files modified after last index are re-indexed automatically on read — explicit reindex only needed for brand-new workspaces/files.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileYesSource file path relative to workspace_dir (e.g. "src/auth.py")
symbolNoOptional: narrow to tests referencing a specific symbol
workspace_dirYesREQUIRED: project root (abs).

Schema Changelog

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

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It reveals the auto-fresh re-indexing behavior and notes when explicit reindex is needed, which is useful. However, it doesn't explicitly state whether the operation is read-only, what side effects occur during auto-fresh, or what return format to expect, leaving gaps in 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 only two sentences, with the purpose stated first and the essential behavioral note (auto-fresh) in the second. Every word earns its place; there is no fluff or redundancy.

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?

This tool has no output schema and no annotations, so the description should cover key context. It explains what it does and the auto-fresh behavior, and points to test_bridge. However, it lacks any mention of return format (e.g., paths) and what 'import reverse lookup' entails, which could be important for an agent to gauge if the tool meets its needs. Given the simple scope, this is adequate but not complete.

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 baseline is 3. The description's phrase 'naming + import reverse lookup' adds semantic nuance to how the 'file' parameter is used, but it doesn't elaborate on 'symbol' or 'workspace_dir' beyond schema. It adds marginal value without compensating for any missing parameter details.

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 the specific verb 'Find' with a clear resource ('test files for a source file') and explains the mechanism ('naming + import reverse lookup'). It also distinguishes itself from test_bridge, a sibling tool, by explicitly pointing to test_bridge for running tests.

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 explicitly says 'Run them? test_bridge', which tells the agent to use test_bridge for execution, providing a clear when-not-to-use and alternative. It also gives context about when explicit reindex is needed (brand-new workspaces/files) and that auto-fresh handles modified files, informing usage decisions.

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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