Smart commit with Conventional Commits: groups logical changes, infers type + scope from file paths, and generates messages in `<type>(<scope>): <description>` format.
Iterative quality gate hardening loop — run the gate, parse failures, fix each failing category with a fresh-context delegate, re-run until all gates pass or diminishing returns are hit.
Relentless quality loop: alternate between a fresh-context implementer and a fresh-context reviewer until only diminishing-return issues remain. The reviewer is advisory-only (no state changes). The implementer starts fresh each cycle, unanchored from prior attempts. Terminates when max severity ≤ 3 for two consecutive cycles or the severity trend is flat.
Compact the current conversation into a handoff document for a fresh agent to pick up next session. Includes current phase, workspace state, memory state, and suggested skills.
Investigate a question against primary sources (official docs, arXiv papers, Semantic Scholar, source code, specs, first-party APIs) using the web_search tool. Writes structured findings as a Markdown file. Use when the user wants a topic researched, docs gathered, API facts investigated, or reading legwork delegated. Maps to P1 Explore phase.
Meta-cognitive improvement loop: reflect on errors, learn patterns, codify guardrails. The skill that rewrites skills. Always loaded.
Contract-first API design: schema-first (OpenAPI/gRPC/GraphQL), backward compatibility, consistent error responses, idempotency, cursor pagination, versioning. Use when designing or evolving an HTTP, gRPC, or GraphQL API.
Computational biology guardrails: stable API retrieval from biological databases, biological validity constraints (amino acid / DNA alphabets), synthesis constraints (GC content, repeats), and data provenance. Use for protein design, DNA/RNA analysis, molecular dynamics.