io.github.cdeust/ai-architect-mcp-spec
MCPB · AI-ARCHITECT-MCP-SPEC.MCPB · SCANNED AUG 3
PRD verification and host-driven generation with multi-judge consensus across 17 MCP tools.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score →
Supply Chain Security13
- Malware scan not yet available for this package.Unverified
- CVE data not yet available for this package.Unverified
- No install/post-install scripts declared.Pass
- Dependency-health data not yet available.Unverified
Provenance & Transparency45
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 0 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability0
- Schema quality not yet verified: we do not have a sandbox capture of the MCP schema this version of the package serves yet.Unverified
Stability & Change Management0
- Stability not yet verified: we do not have a sandbox capture of the MCP schema this version of the package serves yet.Unverified
Tool Coverage0
- Tool coverage not yet verified: we do not have a sandbox capture of the tool definitions this version of the package serves yet.Unverified
Capabilities0
- Protocol version not yet verified: we do not have a sandbox capture of the MCP handshake this version of the package performs yet.Unverified
Unverified: 4 categories
Categories scored 0 because our sandbox run of this package has not given us the schema these checks need to read. That is a gap on our side rather than a finding about the package, and we only credit what we can confirm, so the score stands at 0 until the capture succeeds. We are working through the fleet, so this normally clears without any action from you. How we score packages →
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mcpb · ai-architect-mcp-spec.mcpb
Download bundleEvery change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 3 Aug 26 13
First indexed and scored.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 3 Aug 2026 · Analysed mcpb/https://github.com/cdeust/ai-architect-mcp-spec/releases/download/v0.7.0/[email protected]
Provenance none
Ecosystem: mcpb · Outcome: none
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.
check_health ~18
Check system health — verify all components are accessible
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
conclude_verification ~363
Aggregate JudgeVerdict[] from spawned subagents into a VerificationReport (consensus + dissent). IMPORTANT: omitting claim_types when a reliability repository is open suppresses observation flushing for this batch — the calibration data will be missing for these runs (one-sided censoring).
| Name | Type | Req | Description |
|---|---|---|---|
| claim_types | object | — | Map of claim_id → claim_type. When provided, enables per-(judge × claim_type) reliability lookup. Omit to fall back to per-agent scalar priors. Source: derive from plan_section_verification / plan_do… |
| claims | array | — | OPTIONAL. Pass the Claim objects from the corresponding plan_section_verification / plan_document_verification response if you want oracle-based ground truth (breaks Curie A2 annotator-circularity fo… |
| consensus_strategy | string | — | — |
| run_id | string | — | Pipeline run_id — required for calibrated Bayesian reliability weights (CC-3 control-arm seam uses this to partition treatment vs control runs). When absent, falls back to Beta(7,3) prior for all jud… |
| scope | string | — | — |
| section_type | string | — | — |
| verdicts | array | yes | — |
No output schema declared.
No examples provided.
coordinate_context_budget ~84
Calculate token budget allocation for PRD generation. Returns per-section retrieval limits for Cortex recall, generation budgets, and section-specific query templates. Call this BEFORE starting section generation.
| Name | Type | Req | Description |
|---|---|---|---|
| completed_sections | array | — | Section types already generated |
| context_window_size | integer | — | Total context window size in tokens |
| prd_context | string | yes | The PRD context type |
No output schema declared.
No examples provided.
get_config ~14
Get the full skill configuration
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_pipeline_state ~189
Read the current pipeline state by run_id. format:'summary' (default) returns the lightweight envelope; format:'full' returns the whole state, bounded to the Claude Code 100,000-char MCP response budget by shedding least-relevant detail first (observable __bounded markers; full grounding re-fetchable via format:'grounding'); format:'grounding' returns the codebase_grounding (+ prd_validation when it fits) blobs format:'full' sheds first; format:'validation' returns prd_validation alone (the blob format:'grounding' sheds when the pair overshoots); format:'action' returns the UNBOUNDED last action emitted for this run (including full spawn_subagents prompts) — the recovery path when a start_pipeline/submit_action_result response carries a __bounded marker on its action.
| Name | Type | Req | Description |
|---|---|---|---|
| format | string | — | — |
| run_id | string | yes | — |
No output schema declared.
No examples provided.
get_prd_context_info ~33
Get configuration for a specific PRD context type
| Name | Type | Req | Description |
|---|---|---|---|
| context | string | yes | The PRD context type |
No output schema declared.
No examples provided.
get_quality_history ~33
Get historical PRD quality scores from the evidence repository
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | — | Maximum number of records to return |
No output schema declared.
No examples provided.
get_strategy_effectiveness ~40
Get strategy performance data — actual vs expected improvement, compliance rate
| Name | Type | Req | Description |
|---|---|---|---|
| min_executions | integer | — | Minimum executions required to include a strategy |
No output schema declared.
No examples provided.
list_available_strategies ~19
List thinking strategies available to the pipeline.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
map_failure_to_retrieval ~58
When validate_prd_section returns violations, call this to get corrective Cortex recall queries. Closes the validation→retrieval feedback loop so retries use better context.
| Name | Type | Req | Description |
|---|---|---|---|
| violations | array | yes | Violations from validate_prd_section |
No output schema declared.
No examples provided.
plan_document_verification ~50
Same as plan_section_verification but across all sections of a document.
| Name | Type | Req | Description |
|---|---|---|---|
| codebase_excerpts | array | — | — |
| memory_excerpts | array | — | — |
| sections | array | yes | — |
No output schema declared.
No examples provided.
plan_section_verification ~69
Extract claims from a PRD section and select judges. Returns JudgeRequest[] the host must execute via Agent tool in parallel.
| Name | Type | Req | Description |
|---|---|---|---|
| codebase_excerpts | array | — | — |
| content | string | yes | — |
| memory_excerpts | array | — | — |
| section_type | string | yes | — |
No output schema declared.
No examples provided.
read_skill_config ~21
Read the SKILL.md content that drives PRD generation
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
start_pipeline ~121
Initialize a new PRD pipeline run. Returns run_id and the first NextAction the host must execute.
| Name | Type | Req | Description |
|---|---|---|---|
| codebase_path | string | — | Absolute path to the codebase. Triggers index_codebase via automatised-pipeline. |
| feature_description | string | yes | What the PRD is about — passed to all prompts |
| skip_preflight | boolean | — | If true, skip the preflight step that probes Cortex (and ai-architect when codebase_path is set). Default false. Use only when you accept degraded section generation without persistent memory recall. |
No output schema declared.
No examples provided.
submit_action_result ~37
Feed an ActionResult to the pipeline runner; receive the next NextAction.
| Name | Type | Req | Description |
|---|---|---|---|
| result | — | yes | — |
| run_id | string | yes | — |
No output schema declared.
No examples provided.
validate_prd_document ~53
Run full document validation including cross-section checks (SP arithmetic, AC numbering, FR-AC coverage, test traceability). Returns comprehensive validation report.
| Name | Type | Req | Description |
|---|---|---|---|
| sections | array | yes | Array of PRD sections to validate |
No output schema declared.
No examples provided.
validate_prd_section ~68
Run deterministic Hard Output Rules validation on a single PRD section. Returns violations found — zero LLM calls, pure regex/parsing.
| Name | Type | Req | Description |
|---|---|---|---|
| content | string | yes | The markdown content of the PRD section |
| section_type | string | yes | The type of PRD section being validated |
No output schema declared.
No examples provided.