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mark-brannan

colregs-mcp

by mark-brannan

Applied applicability entries

applied_entries
Read-onlyIdempotent

Return matching COLREGS entry IDs and citations for a vessel's facts, without composing light displays. Use it to answer 'which paragraphs speak to this vessel' before evaluating display options.

Instructions

The colregs applicability entries whose conditions hold for a fact record, as {id, cite} pairs in data order, without composing displays. Use evaluate_display for the lights; this is the cheaper question "which paragraphs speak to this vessel". Same input as evaluate_display. Not for navigation. Coverage: COLREGS Part C lights only, international (high seas) text only, lights at night only (no day shapes, no sound signals, no Part B steering rules), evaluated against pre-release colregs data (0.x), whose content is still being checked. Every entry id and paragraph cite in a response is verbatim from the colregs data package; nothing is paraphrased. This tool surface is a 0.0.x preview and will change without notice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
factsYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.0.1

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint, and the description adds substantial non-obvious behavior: output ordering, verbatim provenance from the data package, coverage limitations, pre-release data status, and a stability warning that the surface may change without notice. This goes well beyond what annotations provide.

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 dense but well organized: purpose first, then the key alternative, then scope limitations, then data-provenance and stability caveats. Every sentence adds necessary information, and the most decision-relevant content is front-loaded.

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 complex nested input and no output schema, the description is unusually complete: it specifies the output shape ({id, cite} pairs in data order), the exact coverage boundaries, the source data version, the preview instability, and the fact that entries are verbatim rather than paraphrased. Nothing essential for invoking the tool correctly 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?

The single top-level facts parameter has no inline description in this tool, and schema description coverage is 0%. However, the description says 'Same input as evaluate_display', linking the agent to the sibling schema, and frames the input as a fact record. The nested schema itself documents each fact property in detail, so an agent can construct valid input despite the top-level cross-reference.

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 states a specific verb and resource: it returns COLREGS applicability entries that hold for a fact record, as {id, cite} pairs in data order. It also clearly distinguishes itself from evaluate_display by framing this as the cheaper 'which paragraphs speak to this vessel' question, so an agent can tell the tools apart.

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?

The description explicitly tells the agent when to use evaluate_display instead and what this tool is for: 'Use evaluate_display for the lights; this is the cheaper question'. It also gives hard exclusions via the coverage statement: no day shapes, no sound signals, no Part B steering rules, and not for navigation.

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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