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sassy_minify_test

Read-onlyIdempotent

Measure GitHub response minification savings on sample JSON input. Determine reduced size and token counts to decide whether a full API call is worthwhile.

Instructions

Read-only diagnostic. sample_json is a JSON string containing a sample GitHub API response; nothing is sent anywhere. The tool parses it, runs it through the same minifier applied to GitHub tool responses, and reports original_chars, minified_chars, savings_percent, original/minified estimated tokens (chars divided by 4), tokens_saved, and the minified_data itself. Invalid JSON returns an error instead of results. Use it to gauge how much the GitHub response shrinker will reduce a heavy github_full response before you commit to a large call; it is a test harness, not a live API caller.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`sample_json`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedv1.15.1Sep 18, 2026

addedOutput schema / additionalProperties
```
Added value: +true
```

removedOutput schema / properties

Removed value: -{
-  "result": {
-    "title": "Result",
-    "type": "string"
-  }
-}

removedOutput schema / required
```
Removed value: -[
-  "result"
-]
```

changedOutput schema / title

Previous value: -"sassy_minify_testOutput"New value: +"sassy_minify_testDictOutput"

First observedv0.1.0Jul 31, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already declare read-only, idempotent, and non-destructive. The description adds important behavioral context beyond that: nothing is sent anywhere, invalid JSON returns an error instead of results, and it lists the exact computed metrics returned.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with 'Read-only diagnostic' and then gives complete, actionable detail. Some phrasing is slightly redundant (e.g., referencing the minifier twice), but every sentence contributes useful information.

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?

Given the tool's low complexity, one parameter, existing annotations, and output schema, the description covers everything needed to call it correctly: input meaning, local processing, output fields, invalid-input behavior, and recommended usage context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must carry the meaning of sample_json. It does so by stating that it is a JSON string containing a sample GitHub API response. It could include an example or more structure, but for a single parameter this is adequate guidance.

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: it parses a sample JSON string, runs it through the GitHub response minifier, and reports size/token metrics. It also distinguishes itself as a diagnostic/test harness rather than a live API caller, which separates it from sibling tools.

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?

The description explicitly says when to use it: before committing to a heavy github_full call, to gauge how much the response shrinker will reduce size. It also explicitly says what it is not ('a test harness, not a live API caller'), giving clear exclusion guidance.

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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