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Santismm Knowledge — Harness Engineering, Agentic AI & Governance

Get an Agentic Reference Architecture

get_architecture
Read-onlyIdempotent

Get one reference architecture by slug (includes the request flow, reference scenario, KPIs, cost & scaling, and the patterns/knowledge it composes). Use this once search or list_architectures has given you a slug.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesArchitecture slug, e.g. 'customer-service-agent'.
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
technologiesNo
canonical_urlYes
resolved_localeNo
requested_localeNo

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already indicate readOnly, idempotent, and non-destructive behavior, so the description's job is lighter. It adds useful context about response contents and the prerequisite of having a slug. No contradictions or hidden side effects are hinted at.

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 concise sentences front-load the core action and resource, then provide the key usage precondition. Every word earns its place; no redundant phrasing or 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?

Given the output schema exists, strong annotations, and a clear precondition for use, the description is complete for correct invocation. The agent knows what to call, when to call it, and what the response contains.

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%, so the schema fully documents both `slug` and `locale`. The description reinforces that `slug` is the lookup key, but adds no parameter semantics beyond the schema.

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 a specific verb and resource: 'Get one reference architecture by slug', and enumerates the contents of the response. It clearly distinguishes itself from sibling list/search tools by specifying the slug-based lookup.

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 the tool: after `search` or `list_architectures` has returned a slug. This gives the agent a clear workflow and prevents premature invocation. No alternative tool is needed once a slug is known.

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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TDQS

A4.4/5.0
Disambiguation5/5

Every tool targets a distinct operation and identifier: search is the entry point, list_* returns browsing summaries, get_* returns a single unit, get_related traverses the graph, and get_overview maps the corpus. Even the similar get_homeric_* trio is cleanly separated by episode/place/route.

Naming Consistency5/5

All names follow snake_case verb_noun: get_* for singular retrieval, list_* for enumeration, plus search. get_related and get_overview are the only deviations but remain predictable read operations.

Tool Count4/5

21 tools is above the typical 3-15 range, but the count is justified by the number of distinct corpora and the consistent list/get pairing for each; there are no redundant tools, so it is only slightly heavy.

Completeness5/5

The server offers a complete read-side lifecycle for this knowledge corpus: overview, search, list, get, and graph traversal. For a read-only knowledge server, there are no obvious dead ends; coverage of claims, patterns, architectures, governance, handbook and Homeric atlas is thorough.