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Quality report

quality_report
Read-only

Assess an SVG document's health with validation findings, quantitative metrics, and optimization opportunities to identify what can be improved.

Instructions

Build a machine-readable quality report for a document: validation findings plus metrics.

When to use: assessing a document's health and what optimizing would save. For pass/fail correctness only use validate_document; to actually strip the opportunities use svg_web_optimize.

Key params: none beyond doc_id.

Return shape: QualityReportok, the validate_document findings (missing fonts, external assets, large rasters, id problems, viewBox sanity), quantitative metrics (object/node/layer counts, embedded-raster weight in bytes, font coverage, viewBox health), and opportunities (keyed identically to svg_web_optimize.removed: editor metadata, unused defs, unreferenced ids, empty groups, reducible coordinate precision). Every field is structured (not prose).

Example: quality_report(doc_id)

Risk class: low (read-only; document unchanged).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
doc_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
scoreYes
doc_idYes
metricsYesQuantitative document metrics (all read-only).
findingsYes
error_countYes
opportunitiesYes
warning_countYes
Behavior5/5

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

Annotations declare readOnlyHint=true, destructiveHint=false. Description adds 'Risk class: low (read-only; document unchanged)' and details return shape including fields and structure. Adds significant context beyond annotations.

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?

Well-structured with clear sections (purpose, usage, params, return shape, example, risk). Each sentence adds value, though slightly verbose. No wasted words.

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 output schema existence, description comprehensively covers validation findings, metrics, opportunities structure. Single param is simple. No gaps for tool complexity.

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 coverage is 0%, but tool has only one parameter doc_id. Description mentions 'Key params: none beyond doc_id' and includes it in example, but does not explain its purpose or format. Adequate for a simple single-param tool but not exceptional.

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?

Clearly states verb 'build' and resource 'machine-readable quality report for a document'. Distinguishes from siblings validate_document and svg_web_optimize by scope and use case.

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?

Explicitly states when to use (assessing document health) and when not (pass/fail correctness -> validate_document, stripping opportunities -> svg_web_optimize). Provides clear alternatives.

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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