Use when audited OpenClaw conversations or outgoing Feishu/Slack/channel messages contain concrete business numbers such as revenue, percentages, stock prices, contract values, costs, market share, or funding and need evidence checks plus red/yellow/green audit stamps after sends.
Pre-ingestion verification for epistemic quality in RAG systems. Ensures documents are properly qualified before entering knowledge bases. Produces CGD (Clarity-Gated Documents) and validates SOT (Source of Truth) files.
Use when creating a new AepCaw security policy, including agent sandboxes, CI pipelines, development environments, HTTP service gateways, or Postgres-family database access policies.
Use when adding, removing, or updating rules in an existing AepCaw policy, modifying security permissions, HTTP service declarations, Postgres-family database rules, resource limits, or policy YAML files.
Use this skill whenever working with AEP (Agent Element Protocol) 2.8, dynAEP (main AEP event runtime), Base Node, Composer Lite, CCA / setup agent, component registry, CAW, UCB, Path A/B connect, dynAEP-TA, dynAEP-TA-P or any AEP governance feature. Triggers include 'AEP', 'dynAEP', 'dynAEP-TA', 'dynAEP-TA-P'…
Use this skill to evaluate the quality of a RAG pipeline on faithfulness, answer relevancy, context precision, context recall, and hallucination rate. Activates after a RAG system is implemented or when retrieval quality is in question. Produces a structured evaluation report with measurable results.
LLM-driven epistemic reasoning engine. Evaluates claims against evidence, outputs calibrated confidence and structured belief state (VERIFIED/CONTESTED/UNCERTAIN). v2 adds 4-way constraint system, parameterized configuration, and formula-based confidence intervals. Use when the agent needs to assess whether…
LLM-driven epistemic reasoning engine. Evaluates claims against evidence, outputs calibrated confidence and structured belief state (VERIFIED/CONTESTED/UNCERTAIN). Use when the agent needs to assess whether information is trustworthy, detect contradictions in evidence, or quantify uncertainty.
Systematically fact-check AI-generated research reports and data-heavy documents. Trigger when the user asks to verify, fact-check, validate, or audit a report or document — especially those containing financial figures, market data, or claims sourced from web searches. Not for code review or general editing.
Use when verifying that a tool or skill was actually used, checking tool installation, or generating verification receipts. Triggers on 'verify', 'truth', 'proof', 'did it actually use', 'check tool', 'tooloftruth', '/truth'. Also triggers when the agent is about to claim a tool was used — run verification first.