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minga-graph

minga-graph

by dmminga1983
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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graph_impact

Find transitive callers, importers, and subclasses of a code node before changing or deleting code.

Instructions

What depends on a node (transitive callers, importers, subclasses). Use before changing or deleting code.

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": {
      "name": "<name>"
    },
    "name": "graph_impact"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes
depthNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does convey that this is an analysis/read operation reporting transitive dependents. However, it says nothing about the default traversal depth (a depth of 3 exists in the schema), whether results are truncated, or what the response shape is.

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?

Two sentences, no filler, with the core purpose front-loaded and the usage cue second. Nothing is wasted.

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

Completeness2/5

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

No output schema and no annotations mean the description must explain behavior, yet it omits the depth parameter entirely and gives no sense of result contents or limits. For a graph traversal tool where depth dramatically changes cost and output, this leaves an agent guessing.

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%, so the description must compensate for both parameters and does not: 'name' is only obliquely referenced as 'a node', and 'depth' (default 3) is never mentioned at all, leaving the word 'transitive' as the only clue about traversal.

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?

States a specific relationship being computed ('what depends on a node') and enumerates the kinds of dependents (callers, importers, subclasses), which separates it from graph_explain/graph_path/graph_stats. It never names the siblings explicitly, so the differentiation is inferred rather than stated.

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?

'Use before changing or deleting code' gives a concrete triggering situation, which is more than most tools offer. It does not say when NOT to use it or which sibling to pick for plain queries, so the guidance is one-sided.

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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