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aidesignblueprint

AI Design Blueprint Doctrine

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by aidesignblueprint
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Python
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principles.search

Read-onlyIdempotent

Search blueprint principles by free-text query to find design guidance for specific challenges, failure modes, or keywords. Returns ranked matches with title, cluster, definition, rationale, and heuristics.

Instructions

Search Blueprint principles by free-text query and return the closest matches ranked by relevance. Use this to find principles related to a specific design challenge, failure mode, or keyword (e.g. 'reversibility', 'approval flow', 'delegation boundary'). Returns principle title, cluster, definition, rationale, and implementation heuristics. Prefer this over principles.list when you have a specific topic in mind rather than wanting all principles. NOTE: search currently covers the 10 agentic principles only; for the 8 experience-design laws or the 8 spec-quality laws use principles.list(lens='surface') / principles.list(lens='spec') until search spans all three lenses.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return. Capped at server maximum.
queryYesFree-text search query matched against principle title, definition, rationale, and cluster.

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": "search_principlesDictOutput",
+  "type": "object"
+}
  2. Changed1 schema field changedv1.1.0
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "title": "search_principlesDictOutput",
-  "type": "object"
-}New value: +null
  3. First observedv1.0.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds the behavioral context that search is currently limited to agentic principles only, which is valuable beyond what annotations provide. No contradictions.

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?

The description is concise, front-loads the purpose, and uses only necessary sentences. It is well-structured with clear sections for usage guidance and a note about limitations.

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 presence of an output schema, the description does not need to detail return values. It covers the tool's purpose, usage context, limitations, and fallback options completely, making it self-sufficient for an agent.

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% with descriptions for both parameters. The description adds meaning by explaining the search scope (matches against title, definition, rationale, cluster) and providing example queries, which enhances understanding 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 clearly states the tool searches Blueprint principles by free-text query and returns closest matches ranked by relevance. It provides concrete examples like 'reversibility' and distinguishes from the sibling tool principles.list, making the purpose specific and unambiguous.

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?

The description explicitly advises when to use this tool over principles.list: 'Prefer this over principles.list when you have a specific topic in mind.' It also notes a current limitation (covers only 10 agentic principles) and offers fallback using principles.list with lens parameters for other principle sets.

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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