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CanonicAI — cited Answers corpus

get_canon

Return one canon-v1 record (constructs, relationships, open divergences, provenance, source works) for a known slug. Never fabricates content for unknown slugs; returns close-match slugs instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesCanon slug from canons/index.json.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
codeNo
slugYes
messageNo
coverageNo
guide_urlNo
constructsYes
provenanceNo
closeMatchesNo
source_worksNo
relationshipsNo
action_statementNo
open_divergencesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose a genuinely non-obvious trait: no fabricated records for unknown slugs and a close-match fallback response. It omits auth/permission needs and read-only framing, though 'Return' strongly implies a read.

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 tight sentences, front-loaded with the return payload and followed by the edge-case behavior. Every clause carries information; nothing is redundant filler.

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

Completeness4/5

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

An output schema exists so return values need not be explained, and the failure mode for bad slugs is covered. Minor gap: no pointer to where valid slugs are enumerated beyond the schema's mention of canons/index.json.

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

Parameters3/5

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

Schema description coverage is 100% and the single slug parameter is documented as coming from canons/index.json, so baseline is 3. The description adds only the constraint that the slug must be 'known' and what occurs otherwise, not new syntax or format guidance.

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?

Specific verb (Return) plus resource (one canon-v1 record) with the record's contents enumerated (constructs, relationships, open divergences, provenance, source works). The singular scope clearly separates it from list_canons and search_constructs without needing to name them.

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?

States the precondition for use ('for a known slug') and what happens outside that condition (unknown slugs yield close-match slugs, never fabricated content). It does not explicitly name list_canons as the way to discover a slug, so the alternative routing is left implicit.

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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