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Santismm Knowledge — Harness Engineering, Agentic AI & Governance

Get an Agentic AI Knowledge Unit

get_knowledge
Read-onlyIdempotent

Get one knowledge unit by slug. Returns the full entry, or a single-locale body if locale is given. Use this once search or list_knowledge has given you a slug.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesKnowledge unit slug, e.g. 'harness-engineering'.
localeNoLanguage of the returned body. Default: en.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
bodyNo
nameNo
slugYes
tagsNo
domainYes
localeNo
statusNo
aliasesNo
api_urlYes
localesNo
relatedYes
summaryNo
updatedYes
versionYes
categoryYes
evidenceYesEvidence-First provenance: weight claims by this.
fallbackNo
featuredNo
patternsNo
knowledgeNo
frameworksNo
referencesYes
how_to_citeNoThe citation, already formed — use it verbatim.
resource_uriNo
technologiesNo
canonical_urlYes
resolved_localeNo
requested_localeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedOutput schema / 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. The description adds that the response shape changes with locale (full entry vs single-locale body), which is useful, but it does not cover failure behavior for a missing slug or any limits.

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 what the tool returns before the routing advice. No filler and no restatement of the title.

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?

Purpose, the when-to-use trigger, and the locale-conditional return are all present, and an output schema plus rich annotations cover the rest. The only real gap is that error behavior for an unknown slug is unstated.

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?

Schema coverage is 100%, so the baseline is 3, and the description goes slightly beyond it by explaining the observable consequence of `locale` — you get only a single-locale body instead of the full entry. It does not add anything on `slug` beyond the schema's example.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Get one knowledge unit by slug') and names the identifier used for lookup, so it is distinguishable from the list_/search_ siblings. It does not explicitly differentiate itself from other singular getters like get_article or get_pattern, which keeps it short of a 5.

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?

Gives an explicit usage condition: 'Use this once search or list_knowledge has given you a slug,' naming the upstream alternatives. There is no when-not guidance (e.g. what to do if you have no slug), but the required context is clear.

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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