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build_quality_report

Read-only

Build a structured quality report for ArchiMate models, covering visual, semantic, and coverage validation, with optional TOGAF readiness assessment. Aggregates counts without full issue lists.

Instructions

Build a structured visual, semantic, coverage, and optional TOGAF report.

Aggregate counts throughout — this is the tool to poll during a
build without paying for full issue lists.

Args:
    include_togaf: Add `data.togaf_readiness`. Advisory only; see
        `assess_togaf_readiness` for the scoring scale and the
        standing `compliance_claim: false` disclaimer.
    include_quality_assurance_views: Count QA-marked views as
        stakeholder-facing in the TOGAF checks.

Returns:
    Success envelope with `data.visual_validation`,
    `data.semantic_validation` (`is_valid`, `issues_count`,
    `issue_counts`), and `data.coverage`. With `include_togaf`,
    `data.togaf_readiness` carries `status`, `score`, `max_score`,
    `advisory_findings`, `advisory_findings_count`,
    `hard_failures_count`, and `compliance_claim`.

Errors:
    `ModelNotFoundError` if no model is active.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
include_togafNo
include_quality_assurance_viewsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Annotations provide readOnlyHint=true and openWorldHint=false, and the description aligns with these by presenting a read-only report generation. The description adds behavioral details beyond annotations: it explains the aggregation nature ('aggregate counts throughout'), parameter effects on the report, and the exact structure of the returned data, including optional TOGAF fields and error conditions.

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 well-structured with separate sections for purpose, usage note, args, returns, and errors. Every sentence adds value, from the opening verb+resource to the detailed return envelope. It is concise but not terse, hitting an optimal length.

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 simplicity (two optional booleans, no required params) and the presence of an output schema (described in detail), the description covers all relevant aspects: purpose, parameters, return structure, error conditions, and usage context. It leaves no gaps for effective agent invocation.

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

Parameters5/5

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

Schema description coverage is 0%, so the description fully compensates by detailing both parameters. It explains that include_togaf adds data.togaf_readiness with a disclaimer and references assess_togaf_readiness, and that include_quality_assurance_views counts QA-marked views as stakeholder-facing. This adds significant semantic context beyond the parameter names and types.

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 clearly states it 'builds a structured visual, semantic, coverage, and optional TOGAF report', specifying the verb and resource. It further distinguishes itself from siblings by noting it is 'the tool to poll during a build without paying for full issue lists', making its purpose and niche explicit.

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 explicitly advises using this tool during a build for lightweight aggregation ('the tool to poll during a build without paying for full issue lists'). It references assess_togaf_readiness for additional TOGAF scoring, implying an alternative for detailed TOGAF assessment, but does not provide clear exclusion criteria or alternative use cases for other report types.

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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