Skill UI

This skill optimizes LLM context usage through prompt caching, log pruning, and AST-based file inspection. It enforces ultra-dense output, minimizes filler text, and manages token budgets efficiently. Ideal for technical tasks requiring precise code edits, structured data handling, and reduced context window consumption during long sessions.

Preserve the coding agent's explicit AAS skill selection as a validated stack and optional evidence. Use when the user explicitly requests this AAS workflow, not for unrelated tasks.

Discover AAS skills for a specific task and compare their complete instructions without installing them. Search the catalog, read skill details, and evaluate applicability, setup, provenance, risk, and limitations. Grounded in actual tool results, with clear reporting of gaps and errors.

Acts as a proxy for Cline CLI to dispatch coding tasks, monitor background runs via hard evidence like git state, and learn user preferences over time. Ensures safety by requiring user approval for destructive actions and verifying completion against checklists.

This skill develops and verifies mathematical proofs using the Lean theorem prover. It handles creating new proofs, continuing incomplete projects, and auditing existing formalizations to ensure they match original statements. It connects inputs to lemmas, assembles theorems, and checks axioms for reproducibility. Use it for formal verification tasks rather than ordinary drafting.

Verify a local agent API, temporary gateway tunnel, and remote sandbox callback with a tool-free task, then restore the original app connection. Use when an agent task runs in a remote sandbox that calls back to a local API through a gateway.

This skill activates a cheeky Cockney persona for coding tasks. It encourages terse replies, minimal diffs, and efficient code changes. Use it when you want to avoid bloat or over-engineering. The AI will speak with a London accent slang (lite, full, guvnor modes) while maintaining security standards. Turn off with specific commands.

Build Quarkus native executables using Mandrel/GraalVM, resolve native reflection failures, test native binaries, and generate container images and Kubernetes/OpenShift manifests. Ideal for native, Docker, Jib, or Kubernetes tasks in Quarkus projects.

This skill retrieves up-to-date documentation for third-party APIs, SDKs, and libraries using the chub tool. It ensures code accuracy by fetching current references instead of relying on outdated pre-trained knowledge. Use it when users request tasks involving external services like OpenAI or Stripe. Follow chub instructions to search, fetch, and annotate documentation for better future sessions.

Compile user-authorized durable constraints into OpenViking Rules using the Python SDK or HTTP API, then poll tasks and verify saved rules and scenarios.