Skip to main content
Glama

inspect_active_model

Read-only

Inspect your active ArchiMate model: view summary, type counts, validation issues, orphans, and get recommended next actions without extracting full source code.

Instructions

Inspect the active model without dumping full XML or source code.

Use this immediately after loading an existing model and before
editing. It combines model info, summaries, type counts, visual
validation, compact semantic validation, compact orphan summaries,
and recommended next calls.

Args:
    include_semantic_validation: Include compact semantic validation
        summary. Defaults to true.
    include_orphans: Include compact orphan element summary.
        Defaults to true.
    sample_limit: Maximum number of issue/orphan examples to include.
        Clamped to 0-50.

Returns:
    Success envelope with compact inspection data.

Errors:
    `ModelNotFoundError` if no model is active.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sample_limitNo
include_orphansNo
include_semantic_validationNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Beyond the readOnlyHint annotation, the description details what the tool includes (model info, summaries, type counts, etc.) and mentions error conditions (ModelNotFoundError). No contradictions with annotations.

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 paragraphs for purpose, usage, args, returns, and errors. It is concise yet comprehensive, with no redundant 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 presence of an output schema and the detailed description covering purpose, parameters, return, and errors, the description is fully complete. It does not rely on the output schema to explain return values.

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?

Despite 0% schema description coverage, the description fully documents all three parameters with defaults, meanings, and constraints (e.g., sample_limit clamped to 0-50). This compensates completely.

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 the tool inspects the active model without dumping full XML or source code, and lists the types of data it combines. It distinguishes itself from related tools by specifying it is an inspection-only step after loading and before editing.

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 'Use this immediately after loading an existing model and before editing.' This provides clear guidance on when to use the tool and implicitly indicates it is not for editing.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/byrondelgado/mcp-archimate'

If you have feedback or need assistance with the MCP directory API, please join our Discord server