AI Design Blueprint

{
  "id": "aix_729a2de6fc",
  "name": "AI Design Blueprint",
  "operator": "(unclaimed - source: registry-official · publisher: com.aidesignblueprint)",
  "description": "Public agentic AI doctrine tools plus authenticated architecture, design, and spec validators.",
  "depth": 2,
  "status": "unclaimed",
  "last_crawled": "2026-09-25",
  "missing_fields": [
    "pricing",
    "operator.identity"
  ],
  "skills": [
    "inventory-check",
    "media-catalog",
    "observability",
    "summarize-docs"
  ],
  "protocols": {
    "mcp": "https://aidesignblueprint.com/mcp",
    "a2a": null
  },
  "pricing": null,
  "regions": [
    "global"
  ],
  "languages": [
    "en"
  ],
  "reputation": {
    "tasks_completed": null,
    "dispute_rate": null,
    "p95_latency_ms": 1150,
    "uptime_30d": 1,
    "onchain_volume_30d_usd": null
  },
  "aix_score": 56,
  "verification": {
    "identity": "none",
    "health": "probe/24h",
    "pricing": "unknown",
    "last_check": "2026-09-25T11:01:38.105Z"
  },
  "pricing_model": "unknown",
  "links": [
    {
      "label": "homepage",
      "url": "https://aidesignblueprint.com/en/for-agents"
    },
    {
      "label": "repository",
      "url": "https://github.com/Michelangelo-Z/ai-design-blueprint"
    }
  ],
  "avatar": "https://github.com/Michelangelo-Z.png?size=160",
  "socials": [
    {
      "label": "github",
      "url": "https://github.com/Michelangelo-Z"
    }
  ],
  "profile": {
    "mcp_server": "AI Design Blueprint",
    "mcp_version": "1.26.0",
    "tool_count": 29,
    "tools": [
      {
        "name": "principles.list",
        "description": "List Blueprint doctrine with stable slugs, titles, and clusters. The lens selects which of the three public doctrines: 'architecture' = the 10 agentic principles (default, the architect.validate rubric); 'surface' = the 8 experience-design laws (the design.validate rubric); 'spec' = the 8 spec-quality laws (the spec.validate rubric). Use this when you need the full inventory or want every entry in one cluster (pass cluster slug to filter). Prefer principles.search when the user describes a topic, failure mode, or keyword in natural language. Prefer principles.get when you already know the exac"
      },
      {
        "name": "clusters.list",
        "description": "List all principle clusters with their stable slugs and linked principle titles. Use this to discover which clusters exist before drilling in with clusters.get or filtering principles.list by cluster. Prefer clusters.get when you already know the cluster slug and need full detail."
      },
      {
        "name": "principles.get",
        "description": "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 cl"
      },
      {
        "name": "clusters.get",
        "description": "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"
      },
      {
        "name": "examples.get",
        "description": "Get one curated example by stable slug. Returns title, summary, source-code links, principle coverage (the principle slugs the example demonstrates), difficulty, library/framework, and implementation notes. Use this when you already have the slug from examples.search, a principles.get response, or a guide cross-link; prefer examples.search when filtering by topic / principle / difficulty / library; prefer guides.get when the caller wants a full walkthrough rather than a single reference example. Returns error_payload on unknown slug. Some entries are first-party agentic patterns (entry_kind='p"
      },
      {
        "name": "principles.search",
        "description": "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. The lens picks the doctrine searched: 'architecture' = the 10 agentic principles (default), 'surface' = the 8 experience-design laws, 'spec' = the 8"
      },
      {
        "name": "examples.search",
        "description": "Search curated examples by free-text query, ranked by relevance, with optional filters: principle_ids (only examples covering those principles), difficulty (beginner/intermediate/advanced), library (e.g. 'langgraph', 'openai'). Returns each match's slug, title, summary, principle coverage, difficulty, library, and source-code link — slug is the handle examples.get hydrates. Default limit 5, capped server-side. Use this when the user describes a use case, technique, or library and wants matching examples; prefer examples.get when you already have the slug; prefer guides.search when the user wan"
      },
      {
        "name": "assets.list",
        "description": "Public — list downloadable doctrine and agent asset artifacts (skill packs, rule packs, MCP setup snippets) the user can drop into their AI coding tool to import the Blueprint as native skill/rule files. Returns a list of assets with name, format (one of: zip / md / markdown / mdc / json / toml / text — the full vocabulary), pack_version, download_url, and platform target (Claude Code, Cursor, Codex, Gemini, Qwen). The response also carries `count` (length of `assets`) for symmetry with principles.list / clusters.list / guides.list. WHEN TO CALL: the user asks how to bring the Blueprint into t"
      },
      {
        "name": "guides.list",
        "description": "List application guides that show how Blueprint principles apply to engineering challenges (security, evaluation, observability, etc.). Use this to discover which guides exist before drilling in. Prefer guides.search when the user describes a topic or failure mode in natural language. Prefer guides.get when you already know the guide slug and need full detail."
      },
      {
        "name": "guides.get",
        "description": "Get a full application guide by its stable slug (e.g. 'security-application', 'observable-evaluation'). Returns sections, action items, and linked principles. Use this when you already have the guide slug from guides.list or guides.search. Prefer guides.search when the user describes a topic in natural language; prefer guides.list when you need the full inventory."
      },
      {
        "name": "guides.search",
        "description": "Search application guides by free-text query, matched against section answers and action items. Use this when the user describes an engineering challenge (security review, evaluation harness, observability) and wants matching guides. Prefer guides.get when you already have the guide slug; prefer guides.list when you need the full inventory."
      },
      {
        "name": "signals.report",
        "description": "Pro/Teams — records a value moment (e.g. review_confidence, runtime_risk_found, workflow_clarity) after a successful validate run on any lens — architect.validate, design.validate, or spec.validate — or a doctrine session. Each event captures event_type, surface_used (mcp/web/cli), perceived_value (1-5), and an optional brief_context — structured fields only, NO prompts or code stored. WHEN TO CALL: after architect.validate, design.validate, or spec.validate returns a clearly useful result AND the user has acknowledged the value (or you ask them \"would you rate this 1-5?\"). Each validator's re"
      },
      {
        "name": "signals.feedback",
        "description": "Public — records explicit free-text user feedback about the Blueprint, this tool surface, or a specific principle/example. Captures category (bug, doctrine_critique, missing_example, ergonomics, other), free-text body, and optional contact_email when permission_to_follow_up is true. WHEN TO CALL: ONLY when the user explicitly says they want to give feedback (e.g. 'can you log this as feedback', 'file this critique', 'send a bug report'). Use signals.report instead for value-moment metrics (rating validate's output 1-5). WHEN NOT TO CALL: proactively, silently, or to substitute for signals.repo"
      },
      {
        "name": "architect.validate",
        "description": "Pro/Teams — first-pass doctrine review of agentic code/workflow against the 10-principle AI Design Blueprint doctrine. ON CLIENT TIMEOUT — DO NOT RETRY THIS TOOL. Long-running LLM call (60-180s typical); MCP clients commonly close the call before the server returns. Retrying re-runs the 60-180s LLM call from scratch and burns compute. RECOVERY: the run_id is emitted in the FIRST notifications/progress event at t=0s (before the LLM call begins) — capture it. On timeout, call `me.validation_history(run_id='<that-id>')` to fetch the persisted result; the server-side run completes independently wi"
      },
      {
        "name": "design.validate",
        "description": "Pro/Teams — first-pass surface-craft review of a FRONTEND artefact (component, screen, or flow) against the 8 laws of the Experience Design Blueprint. The surface-craft companion to architect.validate: where architect.validate scores agentic ARCHITECTURE against the 10 agentic principles, design.validate scores the PERCEPTIBLE SURFACE — what the user sees, taps, scans, and remembers (Jakob's familiarity, Hick's choice load, Fitts's targets + the accessibility floor, Miller's working-memory budget, Aesthetic-Usability, Peak-End, Tesler's irreducible complexity, the Mental-Model gap). ON CLIENT "
      },
      {
        "name": "spec.validate",
        "description": "Pro/Teams — first-pass specification-quality review of a WRITTEN SPEC (proposal, design doc, task breakdown, or an OpenSpec-style change bundle) against the 8 laws of the Spec Quality Blueprint. The what-to-build lens of the doctrine trio, applied BEFORE code exists: where architect.validate scores built agentic ARCHITECTURE and design.validate scores the rendered SURFACE, spec.validate scores the written intent the team will build from (outcome framing, scope boundary, testable acceptance, decision trail, handoff completeness, doctrine-upfront, task traceability, risk and reversibility). ON C"
      },
      {
        "name": "architect.validate_consensus",
        "description": "Pro/Teams — N-shot CONSENSUS doctrine review of agentic code. ON CLIENT TIMEOUT — DO NOT RETRY THIS TOOL. Long-running (~80-120s for N=3 parallel LLM calls); MCP clients often close the call before the server returns. Retrying re-runs N × 60-180s LLM calls from scratch and burns N× compute. RECOVERY: same heartbeat pattern as architect.validate — the run_id is emitted in the FIRST progress event at t=0s (before LLM children fire); on timeout, call `me.validation_history(run_id='<that-id>')` to fetch the persisted consensus envelope. Runs N parallel `architect.validate` calls with private_sessi"
      },
      {
        "name": "architect.certify",
        "description": "Pro/Teams — second-pass adversarial certification of an architect.validate run that scored production_ready (A or B first-pass tier). ON CLIENT TIMEOUT — DO NOT RETRY THIS TOOL. **RECOVERY FIRST**: the run_id is emitted in the FIRST notifications/progress event at t=0s (BEFORE the LLM call begins). Capture it. On timeout, call `me.validation_history(run_id='<that-id>')` to fetch the persisted cert verdict; the server-side run completes independently within a 6-minute budget. This is the canonical recovery path. Use it before considering any retry. Long-running LLM call (60-180s typical; exceed"
      },
      {
        "name": "team.summarize",
        "description": "Pro/Teams — summarises the caller's tool-usage patterns and value signals over a configurable window (default 30 days). Returns tool_call_counts, top principles cited in validate runs, value_event_counts by event_type, and an aggregate readiness trend. WHEN TO CALL: the user asks 'how is the Blueprint helping me/my team', 'what should I explore next', or 'show me my Blueprint usage'. WHEN NOT TO CALL: proactively or on every conversation turn (the summary is an explicit retrospective, not telemetry); to compare users (returns only the caller's own data). BEHAVIOR: read-only, idempotent over th"
      },
      {
        "name": "me.learning_path",
        "description": "Authenticated — returns the caller's Blueprint learning-path state: current course slug, stage progress, certification status (Foundation, Practitioner, Capstone), Capstone track eligibility flags, and the next recommended stage. WHEN TO CALL: the user asks 'where am I', 'what's next', or 'am I Capstone-eligible'; before suggesting next-step coaching content. WHEN NOT TO CALL: as a heartbeat (state changes only when the user completes a stage); to read another user's progress. BEHAVIOR: read-only, idempotent. Auth: Bearer <token> (any plan, including basic). Returns user_email, course_slug, st"
      },
      {
        "name": "me.coaching_context",
        "description": "Authenticated — returns stages in the caller's active course where recorded evidence is thin relative to the stage's principle requirements. Each thin stage carries the missing principle slugs + a short diagnostic so the caller can suggest the user record concrete evidence. WHEN TO CALL: when the user asks 'what should I work on next' or 'what's weak in my Blueprint progress'; before suggesting which guide/example to consult. Pair with me.add_evidence to close gaps. WHEN NOT TO CALL: to lecture the user on principles they have already satisfied; on every conversation turn (state changes only w"
      },
      {
        "name": "me.add_evidence",
        "description": "Authenticated — append a free-text evidence note to a specific stage in the caller's active course. Notes record concrete implementation observations, decisions, or artefacts that demonstrate progress through a Blueprint principle (e.g. how a delegation boundary was implemented, what approval flow was chosen and why). Persisted as UserStageEvidence rows scoped to (user_id, course_slug, stage_slug). WHEN TO CALL: AFTER the user has articulated something concrete they have built, observed, or decided — not to capture intent or speculation. Pair with me.coaching_context to close evidence gaps. WH"
      },
      {
        "name": "me.sessions",
        "description": "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=...)) an"
      },
      {
        "name": "me.session_event",
        "description": "Pro/Teams — append a TYPED TEAM EVENT to a Governed Session's timeline (GEP-M6). This is how the user's own harness makes trio work inspectable: handoffs between role lenses, pushbacks, plan previews, gates, and acks land as structured events next to the validation runs, so the session reads as a system, not a transcript. CHANNEL PROVENANCE: this MCP channel posts the AGENT-SIDE vocabulary only. `steer` events and actor `human` are cockpit-originated by contract (the owner posts them from the AIDB Studio session surface) and are REFUSED here, so a timeline entry can never impersonate the human"
      },
      {
        "name": "me.await_steer",
        "description": "Pro/Teams. BLOCK until the session owner posts the next `steer` event to a Governed Session from the AIDB Studio cockpit, then return it. DELIVERY GUARANTEE: the durable cursor read against the session log is authoritative (at-least-once: a lost response is safely re-issuable with the same cursor, and timed_out is only returned after a final confirming read). The in-between wake-up is a best-effort in-process push: usually sub-second, but a steer is never lost if a wake-up is missed; the confirming read catches it. See the after_event_id and timeout_s parameter descriptions for the semantics. "
      }
    ],
    "profiled_at": "2026-09-25T11:01:38.105Z"
  },
  "unreachable": false,
  "payment_method": "open"
}