AI Design Blueprint Doctrine

My Governed Sessions

me.sessions

Read-onlyIdempotent

Pro/Teams — list or inspect the authenticated user's Governed Sessions (GEP-M2): durable, owner-scoped containers that group validation runs across lenses (architect.validate → 'architecture', design.validate → 'surface', spec.validate → 'spec') into one timeline for one piece of work. Two modes: (1) No arguments returns every session (id, title, status, repo_url, spec_ref, team_agents, run_count, validators = the lenses seen), newest first. (2) session_id=<id> returns that session plus its run timeline (light rows; fetch full results per run via me.validation_history(run_id=...)) and, for team sessions, events = the typed team-event log posted via me.session_event. Attach new runs by passing session_id to architect.validate, design.validate, or spec.validate. Sessions are created and managed in the web app at /app/sessions. Read-only. Auth: Bearer . Pro or Teams plan required.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`session_id`	No	Session id to inspect (returns the session + its run timeline). Owner-scoped: ids you don't own answer 'Session not found.'. Omit to list all your sessions.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.9/5.0

Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds context: read-only nature, authentication ('Bearer <token>'), plan requirement ('Pro or Teams'), owner-scoping with error message for non-owned IDs, and the non-destructive effect. No contradiction with 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 thorough but somewhat lengthy. However, it is well-structured with a clear front-loaded purpose, logical flow from general to specific, and every sentence adds value. Slight reduction possible but still effective.

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 simple input (one optional parameter) and presence of output schema and annotations, the description comprehensively covers the tool's purpose, modes, output fields (list and detail), relationship to sibling tools, and creation workflow. No gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers the session_id parameter fully (100% coverage). The description expands on this by explaining the behavioral difference when omitted vs. provided, including the extra detail (run timeline, events) and owner-scoping behavior, providing valuable context 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 verb ('list or inspect') and the resource ('the authenticated user's Governed Sessions'). It defines sessions as 'durable, owner-scoped containers' and distinguishes from sibling tools by explaining how to use me.validation_history for full results and me.session_event for team events, ensuring no ambiguity.

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?

Explicit guidance on two modes (no arguments vs. session_id) and when to use each. It directs users to me.validation_history for full run results and me.session_event for team event log, and indicates that sessions are created via the web app, covering both when-to-use and when-not-to-use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All AI Design Blueprint Doctrine tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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

Need Help?