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inspect_topology

Read-onlyIdempotent

Map a Python repository's dependency-first components, cycles, and static entry flows to show how modules connect and where circular imports occur.

Instructions

Read source and return dependency-first components, cycles and static entry flows.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "path": "<path>"
    },
    "name": "inspect_topology"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is fully covered by structured data and the description is consistent with it. The description adds value by disclosing the kind of analysis returned (components ordered dependency-first, cycles, entry flows), but says nothing about cost, supported languages, or failure modes.

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?

One front-loaded sentence with no wasted wording. It is dense with domain jargon ('dependency-first components', 'static entry flows') that could be plainer but every clause conveys output content.

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

Completeness3/5

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

For a simple one-parameter read tool with full annotations, the description is roughly adequate, and with no output schema it usefully names the returned artifacts. It falls short on what 'path' accepts and on how this differs from scan_repository, leaving real ambiguity for the agent.

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

Parameters2/5

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

Schema description coverage is 0% for the single required 'path' parameter, so the description must compensate, and it only implies the path points at 'source'. It never states whether path is a file or directory, absolute or relative, or whether it must be a project root.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a concrete verb ('Read source') and enumerates three outputs (dependency-first components, cycles, static entry flows), so an agent can infer this builds a static dependency graph. It does not differentiate the tool from its sibling scan_repository, which likely overlaps in scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no statement of when to choose this over scan_repository or verify_course, and no prerequisites such as whether the path must be a repository root or a language-supported source tree. Usage is left entirely to inference from the verb.

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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