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analyze_files

Delegate analysis of large or multiple files to a specialized CLI, receiving only the answer to preserve context.

Instructions

Delegate file analysis to the Antigravity CLI (Gemini) instead of reading files yourself. USE THIS whenever a file is large (>200 lines) or the task spans more than 3 files: logs, database dumps, generated code, cross-file reviews, comparisons. The files never enter your context — only the answer does.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdNoAbsolute path to the working directory / project root. Defaults to the server's cwd.
filesYesFile paths to analyze (relative to cwd or absolute).
modelNoOverride the model (exact name from `agy models`, e.g. "Gemini 3.1 Pro (High)"). Normally omit — the tool routes automatically.
questionYesWhat you want to know about these files.

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?

With no annotations, the description carries the full burden. It discloses the key behavioral trait that files never enter the agent's context and only the answer is returned, plus the delegation mechanism (Antigravity CLI/Gemini). It doesn't mention latency, cost, or failure modes, but it does reveal the most important side effect.

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 compact and front-loaded: it states the core action first, then gives crisp usage thresholds and a final context-preservation note. Every sentence earns its place, with no redundant wording.

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 no output schema or annotations, the description covers the essential context: what the tool does, when to use it, and a crucial behavioral trait. It doesn't detail the answer format, but the phrase 'only the answer does' implies a returned answer, which is sufficient for most decisions.

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 covers all parameters at 100%, so the baseline is 3. The description adds some color to the 'files' parameter by listing example file types (logs, database dumps) and to the overall use case, but it doesn't add detailed semantics for 'cwd' or 'model' beyond the schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as delegating file analysis to the Antigravity CLI (Gemini) instead of reading files directly, and even lists concrete scenarios (logs, database dumps, generated code, cross-file reviews, comparisons). It does not explicitly name sibling tools, but the purpose is unambiguous and distinct from generic file reading.

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

Usage Guidelines5/5

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

Provides explicit, actionable guidance: 'USE THIS whenever a file is large (>200 lines) or the task spans more than 3 files' and enumerates specific use cases. This leaves no doubt about when to choose this tool, and implicitly indicates when not to (small/simple cases).

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