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Santismm Knowledge — Harness Engineering, Agentic AI & Governance

List Agentic AI Knowledge Units

list_knowledge
Read-onlyIdempotent

List all knowledge units (concepts on agentic & enterprise AI) with slug, category, title, summary and Evidence-First provenance. Use this to browse the domain; use search when you have a question rather than a slug.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
localeNoLanguage of the returned body. Default: en.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
resultsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedOutput schema / properties / results / items / properties / how_to_cite
      Added value: +{
      +  "description": "The citation, already formed — use it verbatim.",
      +  "type": "string"
      +}
  2. First observed

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered without the description. The description adds the field list of what comes back, but says nothing about result volume, pagination, or ordering for an unbounded 'list all' operation. Adequate given the annotation coverage, but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the action and scope, with the routing hint second — no wasted preamble. The final clause is mildly muddled rather than bloated, keeping it just short of ideal.

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?

With a full output schema and rich annotations, the description need not explain return values or safety, and it correctly focuses on purpose and sibling routing. It is nearly complete; the only gap is whether the 'all' listing is paginated or bounded, which an agent invoking it might want to know.

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 a single optional `locale` parameter with 100% schema description coverage and a documented enum plus default, so the schema already carries the semantics. The description adds no parameter-level detail (e.g., whether locale affects only the body or also titles), so 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?

States a specific verb ('List') and resource ('knowledge units'), defines the domain ('concepts on agentic & enterprise AI'), and enumerates the returned fields. It explicitly distinguishes itself from the sibling `search`, so an agent can tell the two apart without opening either schema.

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?

It names the alternative (`search`) and the condition that selects it ('when you have a question'), which is clear routing guidance. The trailing qualifier 'rather than a slug' is slightly confusing, since listing takes no slug parameter and slug-based retrieval is what `get_knowledge` does, leaving a small ambiguity about the browse-vs-fetch boundary.

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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