Skill UI

This skill enables independent auditing of AI agent, gateway, or automation workflow runs. It reconstructs events from traces, checkpoints, and tool calls to verify success claims without trusting self-reports. Users establish contracts, build claim ledgers, normalize evidence, rank witnesses, and assign verdicts like proven or contradicted. It ensures integrity in multi-step automation and separates autonomous success from human-assisted outcomes.

Condense a long agent conversation at a verified phase boundary by writing a durable checkpoint that preserves constraints, evidence, decisions, artifacts and the next action, so a fresh context can resume the same task without repeating work or losing state.

Runs AFP 100-point or AUSTRAC safe-harbour identity checks across a document set (passport, licence, medicare, bank statement) and reports points attained plus exactly which evidence is missing, so onboarding teams can request only the absent documents.

This specialized skill guides the creation of long-form structural critical essays and detailed academic dossiers, primarily for Chinese academic contexts. It utilizes the CrossFrame methodology to first establish a foundational structure, define evidence boundaries, and identify key mechanisms, before applying a critical matrix. The output is highly structured, ensuring depth, rigorous source checking, and comprehensive critical analysis suitable for complex intellectual work.

A specialized quality gate skill designed to review complex, multi-source outputs generated by the CrossFrame framework. It rigorously checks reasoning fidelity, evidence boundaries, source anchors, and structural continuity. Use this when advanced verification of logical rigor and source integrity is required, ensuring outputs meet strict internal protocols and avoid common structural failures.

Turns articles, books, PDFs, and web pages into evidence-first reading reports. Five modes (quick, deep, map, feynman, book) separate claims, evidence, data, assumptions, counterarguments, and limitations, with knowledge maps, confidence tags, and Feynman recall checks.

Compare claims from one or more AI answers, verify their citations against public primary sources, and produce an evidence-linked fact-check report without installing a bundled browser runtime.

Fact-Check-X orchestrates multi-party answer collection, knowledge comparison, and authoritative verification to generate auditable reports. It coordinates sibling skills without embedding business logic, ensuring structured evidence tracking and stage-based deliverables for AI output validation.

This skill maps engineering changes (code diffs, architecture designs, IaC) to specific financial compliance controls, such as PCI-DSS v4.0 and MAS TRM. It generates an auditable report detailing compliance gaps, required evidence, and concrete remediation steps, helping teams catch violations before formal audits.