AI Design Blueprint Doctrine

Get Principle

principles.get

Read-onlyIdempotent

Get one doctrine entry by stable slug. The lens selects the doctrine: 'architecture' = one of the 10 agentic principles (default); 'surface' = one of the 8 experience-design laws; 'spec' = one of the 8 spec-quality laws. Returns id, title, cluster, definition, rationale, implications, and risk-if-violated (laws also carry their eponym and validator_questions). Use this when you already have the exact slug from principles.list; prefer principles.search when the user describes a topic or failure mode in natural language; prefer principles.list when you need every entry or every entry within a cluster. Returns error_payload on unknown slug for the lens.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`lens`	No	Which public doctrine the slug belongs to: 'architecture' (10 principles, default), 'surface' (8 design laws), or 'spec' (8 spec laws).	architecture
`slug`	Yes	Stable slug of the principle (e.g. 'establish-trust-through-inspectability').

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive. Description adds error behavior ('Returns error_payload on unknown slug for the lens') and lists return fields, providing useful 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-organized, starting with purpose, then lens explanation, return fields, usage guidance, and error case. It is informative without being verbose, though could be slightly more concise.

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?

For a simple lookup tool with a robust schema, output schema implied, and annotations, the description covers use cases, parameters, return values, and error handling completely, ensuring an agent can use it confidently.

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 rich descriptions. The description adds meaning by explaining lens choices ('architecture' = 10 principles, etc.) and giving a slug example, enriching understanding beyond 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 'Get one doctrine entry by stable slug', specifies the verb-resource pair, and distinguishes from siblings by mentioning principles.search and principles.list.

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 tells when to use this tool (exact slug known), when to use alternatives (principles.search for natural language, principles.list for all entries), providing clear context for decision-making.

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

A4.6/5.0

Disambiguation5/5

Each tool targets a clearly distinct purpose. For example, architect.validate vs architect.validate_consensus differ in single-shot vs consensus; handoffs.agency, handoffs.operator, and handoffs.partnership are separated by engagement type. No significant overlap.

Naming Consistency4/5

Tools follow a consistent dot-notation grouping (architect.*, clusters.*, examples.*, guides.*, handoffs.*, me.*, principles.*, signals.*, team.*) with predictable verbs (validate, list, get, search, add, etc.). Minor deviation: some underscore within names (e.g., me.add_evidence) but overall pattern holds.

Tool Count4/5

24 tools is on the higher side but justified given the broad domain spanning validation, certification, learning, handoffs, and feedback. Each tool has a clear role, and the count reflects the platform's comprehensive scope without feeling bloated.

Completeness5/5

The tool surface covers the full workflow (validate → consensus → certify), discovery (principles, clusters, examples, guides), personal progress (learning path, coaching, evidence), handoffs (support, partnership, agency), feedback, and team summaries. No obvious gaps for the stated purpose.

Resources

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