Santismm Knowledge — Harness Engineering, Agentic AI & Governance

List AI Governance Units

list_governance

Read-onlyIdempotent

List all AI governance units (regulations, standards, frameworks, playbooks — EU AI Act, ISO 42001, NIST AI RMF, agentic checklist) with id, slug, category, name and summary. Use this to browse the regulations and standards; use search for an obligation or control.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_governance"
  }
}

Input Schema

Name	Required	Description	Default
`locale`	No	Language of the returned body. Default: en.

Output Schema

Name	Required	Description	Default
`count`	Yes
`results`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 17, 2026
- addedOutput schema / properties / results / items / properties / how_to_cite
```
Added value: +{
+  "description": "The citation, already formed — use it verbatim.",
+  "type": "string"
+}
```
First observedSep 6, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, closed-world behavior, so safety semantics are covered. The description adds that this returns a list with specific fields and that a locale affects the returned body, which is useful context beyond the annotations, though it doesn't discuss ordering or pagination.

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-loading the resource and scope followed by routing guidance. No filler.

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?

For a simple list operation with full annotations, an output schema, and a fully documented parameter, nothing needed for correct invocation is missing. The description covers scope, fields, and alternative routing.

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?

There is only one optional parameter, locale, and its schema already documents the enum and default with 100% coverage. The description adds no parameter details, so the baseline 3 applies.

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 uses the specific verb 'list' with the resource 'AI governance units', enumerates the concrete categories and standards covered (EU AI Act, ISO 42001, NIST AI RMF), and states the returned fields. It is clearly distinguishable from siblings like get_governance and search.

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 states when to use this tool ('browse the regulations and standards') and names the alternative with its corresponding use case ('use search for an obligation or control'). This is a textbook when-to-use-vs-alternative statement.

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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