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codegraph-brain

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cgis_init_ontology

Generate a starter patterns.yaml from a measured code graph, proposing domain labels and tolerance baselines. Review the YAML, save it, then use it for drift detection.

Instructions

Propose a starter patterns.yaml from the measured graph (read-only).

Returns the YAML text — save it yourself (e.g. to patterns.yaml), review
the proposed labels, then run ``cgis_drift`` with it. Tolerances are the
measured scores plus ``margin``: a baseline to ratchet down, not a verdict.

No files are written; the caller decides where to persist the output.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNoFixed FQN segment depth for domain discovery (positive); omit to pick it automatically.
marginNoHeadroom added to each measured score to form the proposed tolerance.
db_pathNoSQLite graph built by cgis_ingest. A relative path resolves against the MCP server's working directory, not the agent's — prefer an absolute path.graph.db
min_nodesNoDomains with fewer nodes stay hygiene-only instead of getting a label.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv0.21.1
    • addedInput schema / properties / db_path / description
      Added value: +"SQLite graph built by cgis_ingest. A relative path resolves against the MCP server's working directory, not the agent's — prefer an absolute path."
    • addedInput schema / properties / depth / description
      Added value: +"Fixed FQN segment depth for domain discovery (positive); omit to pick it automatically."
    • addedInput schema / properties / margin / description
      Added value: +"Headroom added to each measured score to form the proposed tolerance."
    • addedInput schema / properties / min_nodes / description
      Added value: +"Domains with fewer nodes stay hygiene-only instead of getting a label."
  2. First observedv0.21.0

TDQS

A4.7/5.0
Behavior5/5

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

No annotations are provided, so the description carries the full burden. It explicitly states the operation is read-only, that 'No files are written', and that the caller decides where to persist the output. This fully discloses the behavioral impact, leaving no hidden side effects.

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 compact and front-loaded: purpose first, then output and persistence behavior, then margin semantics. Every sentence earns its place, with no redundant filler beyond the deliberate repetition of the read-only/no-write guarantee for emphasis.

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 an output schema exists and all parameters have schema descriptions, the description still covers the essential workflow context: what the tool returns, how to use it downstream, and the absence of side effects. Nothing an agent needs to correctly call and interpret this tool is missing.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds meaningful interpretation beyond the schema by explaining that tolerances are 'measured scores plus margin' and framing them as a ratcheting baseline rather than a verdict. This gives strategic context for margin, though it does not add additional semantics for depth, db_path, or min_nodes.

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 first sentence states a specific action ('propose a starter patterns.yaml'), the resource ('from the measured graph'), and the read-only nature. It clearly differentiates itself from sibling tools like cgis_drift by framing the output as a starting artifact to be consumed by cgis_drift.

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 gives an explicit workflow: generate the YAML, save it, review the labels, then run cgis_drift with it. It also explains the semantic role of the output ('a baseline to ratchet down, not a verdict'), which helps the agent decide when this tool is appropriate. It lacks explicit when-not-to-use guidance or named alternatives, so it stops short of a 5.

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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