Skill UI

A discovery guide for scientific research and analysis skills, covering methods, data provenance, and evidence validation for reproducible results.

Analyze a repository to generate recommended Claude Code settings.json permissions for read-only commands. Detects tech stack, build tools, and monorepo structure to build an evidence-based allow list. Use when setting up a new project, auditing existing settings, or determining which bash commands to allow.

Drives a coding task end-to-end against explicit acceptance criteria: minimal implementation, local tests, PR review loop, dev deploy and runtime verification, then evidence-based completion reporting.

Resume interrupted project work from saved handoffs and current checkout evidence, reconciling completed tasks, pending changes, and user constraints without inventing success or resetting a dirty working tree.

This skill applies a rigorous, evidence-first discipline to coding tasks, inspired by Fable-like best practices. It guides agents through a structured workflow: inspecting the workspace, tracking goals and findings, grounding all conclusions in verifiable evidence, and executing thorough verification gates before declaring completion. Ideal for complex development, debugging, or adapting cross-model prompt guidance into robust, verifiable project rules.

Resume interrupted project work by reconciling a saved handoff with current repository evidence: separate completed work, pending edits, superseded assumptions and blockers, then state the next verifiable action within existing authorization.

This skill helps write or revise marketing copy by applying psychological mechanisms to create desire and drive action. It focuses on audience awareness, motivations, and credible proof to overcome generic messaging. Use it for ads, landing pages, or sales messages that need stronger emotional and behavioral triggers. It involves analyzing the target human's psychographic profile and using evidence-based frameworks to engineer belief and action.

A rigorous protocol for Chinese-canonical structural diagnosis of complex systems, organizations, or public disputes. It mandates separating facts, evidence, scale, and responsibility through a multi-stage internal reasoning process, ensuring deep structural integrity and comprehensive review before drawing conclusions.

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.

This技能 is used when analyzing complex propositions, debating, or reviewing arguments within the CrossFrame Suite. It helps users deconstruct claims into testable arguments, identifying hidden premises, strongest counterarguments, evidence requirements, and conditions for withdrawal, ensuring conclusions are robust and non-judgmental.

A specialized writing tool for generating Chinese critical essays, public commentaries, and concept essays based on the CrossFrame framework. It structures analysis, concept mapping, and evidence boundaries before drafting high-quality, long-form articles.

This skill provides a highly rigorous framework for analyzing complex public issues, platform governance, and institutional compliance. It is designed to structure evidence boundaries, assess procedural justice, and track public commitments by synthesizing source ledgers and multiple data points. It is intended as a specialized sub-routine triggered by the main CrossFrame suite, not for standalone use. Key focus areas include source verification, identifying weak signals, and mitigating AI compliance performance risks.