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aidesignblueprint

AI Design Blueprint Doctrine

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by aidesignblueprint
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Python
Remote

clusters.get

Read-onlyIdempotent

Retrieve a principle cluster by its stable slug. Returns the cluster definition, shared rationale, and member principles with slugs and titles.

Instructions

Get one principle cluster by stable slug. Returns the cluster definition, shared rationale, and the full set of member principles (slug + title) so the caller can pivot into principles.get without a second list call. WHEN TO CALL: the user has already named a specific cluster (e.g. 'delegation', 'visibility', 'trust', 'orchestration') OR you have a slug from a prior clusters.list / principles.list response and need its full definition + member principles. The response embeds member principle slugs + titles already, so DO NOT loop principles.get over each member to get a cluster overview — read the response. WHEN NOT TO CALL: the user is describing a topic, failure mode, or keyword in natural language (call principles.search instead); the user wants to discover which clusters exist (call clusters.list); the user wants the definition of one specific principle (call principles.get directly). Idempotent + cacheable per slug. Returns 404-shaped error_payload on unknown slug — the slug must match exactly the value emitted by clusters.list, with no normalization.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesStable slug of the principle cluster (e.g. 'delegation', 'visibility', 'trust', 'orchestration').

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv1.2.0
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "title": "get_clusterDictOutput",
+  "type": "object"
+}
  2. Changed1 schema field changedv1.1.1
    • changedInput schema / properties / slug / description
      Previous value: -"Stable slug of the principle cluster (e.g. 'delegation-and-scope')."New value: +"Stable slug of the principle cluster (e.g. 'delegation', 'visibility', 'trust', 'orchestration')."
  3. Changed1 schema field changedv1.1.0
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "title": "get_clusterDictOutput",
-  "type": "object"
-}New value: +null
  4. First observedv1.0.0

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds that it is cacheable per slug and returns a 404 error on unknown slug requiring exact match, providing context beyond annotations.

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?

The description is well-structured with sections and contains no filler. Each sentence adds value, though it's slightly longer than necessary.

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 an output schema present, it does not need to explain return values. The description covers purpose, usage guidelines, error behavior, and exact matching requirements, making it complete for this tool.

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% and the description clarifies that the slug must be a 'stable slug' and match exactly the value from clusters.list, adding useful nuance beyond the schema description alone.

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 ('Get') and resource ('principle cluster by stable slug'), and explains the return payload, distinguishing it from siblings like principles.get, clusters.list, and principles.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 call (user named a specific cluster, have slug from prior responses), when not to call (natural language topic -> principles.search; cluster discovery -> clusters.list; specific principle -> principles.get), and includes a warning against unnecessary loops.

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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