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Get an AI Governance Unit

get_governance
Read-onlyIdempotent

Fetch a detailed AI governance unit by slug, covering scope, key requirements, implementable controls, a checklist, and common pitfalls. Use it after obtaining the slug from search or list.

Instructions

Get one AI governance unit by slug (includes scope, key requirements, implementable controls, a checklist and common pitfalls). Use this once search or list_governance has given you a slug.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesGovernance unit slug, e.g. 'eu-ai-act'.
localeNoLanguage of the returned body. Default: en.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
bodyNo
nameNo
slugNo
tagsNo
domainNo
localeNo
statusNo
api_urlNo
localesNo
relatedNo
summaryNo
updatedNo
versionNo
categoryNo
evidenceNoEvidence-First provenance: weight claims by this.
fallbackNo
featuredNo
patternsNo
knowledgeNo
frameworksNo
referencesNo
technologiesNo
canonical_urlNo
resolved_localeNo
requested_localeNo
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive traits. The description adds useful context by detailing what the returned governance unit contains, but does not go beyond that (e.g., no error behavior or rate limits). Still, the added content composition is valuable.

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, front-loaded with the action and resource, no fluff. Every word contributes to clarity or usage guidance.

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?

With only 2 parameters, an existing output schema, and strong annotations, the description covers what the tool does, what it returns, and when to use it. This is complete for an agent to select and invoke correctly.

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%, with both `slug` and `locale` clearly explained. The description adds minimal extra parameter context beyond the phrase 'by slug', which is already in the schema. Baseline 3 is appropriate.

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 clearly states the tool gets a single AI governance unit by slug, listing the included contents (scope, key requirements, controls, checklist, pitfalls). This distinguishes it from siblings like list_governance (which lists all units) and search (which finds slugs).

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?

Explicitly says to use this after `search` or `list_governance` has provided a slug, providing clear sequencing and implicit alternatives. This tells the agent exactly when to invoke this tool versus other list/search tools.

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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