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Inspect Changes

inspect_changes

See what an experiment changed in the sandbox by getting created, modified, and deleted file lists with insertion/deletion counts and an optional unified diff. Build and dependency directories are excluded so evidence stays clear.

Instructions

Show what the experiment changed, against the project as it was copied in.

USE THIS before destroying a sandbox, and before telling the developer what you found. It is the evidence for your conclusion.

RETURNS created / modified / deleted file lists plus insertion and deletion counts, and optionally the unified diff. Build output and dependency directories are excluded, so a 30,000-file node_modules will not bury the two lines that matter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
include_diffNoInclude unified diff bodies, not just statistics.
experiment_idYesThe experiment to inspect.
max_files_with_diffNoCap on files given line-level detail.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNo
changesNo
deletionsNo
truncatedNo
insertionsNo
experiment_idYes
files_createdNo
files_deletedNo
files_modifiedNo

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A4.3/5.0
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. It discloses return contents (created/modified/deleted files, counts, optional diff) and filtering behavior (build output and dependency directories excluded). It does not explicitly state that the tool is non-destructive, which would make this a 5.

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, front-loaded with the core purpose, and every sentence earns its place: what it does, when to use it, and what it returns. The node_modules example efficiently justifies the exclusion behavior.

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

Completeness5/5

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

The description tells the agent why this matters, when to invoke it, what baseline is used, what outputs to expect, and how noise is filtered. The presence of an output schema covers the return structure, so nothing important is missing.

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. The description's mention of 'optionally the unified diff' aligns with include_diff but adds little beyond the schema. Baseline 3 is appropriate because the schema handles parameter meaning.

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 states a specific verb and resource: 'Show what the experiment changed, against the project as it was copied in.' It clearly distinguishes this from siblings like compare_experiments or get_experiment by defining the baseline and the evidence role.

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?

The description gives explicit usage timing: 'USE THIS before destroying a sandbox, and before telling the developer what you found.' It does not explicitly name alternatives or when-not-to-use, so it stops short of a 5, but the usage context is strong.

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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