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lemonharness
lemonharness contient 22 skills collectées depuis jmkelly, avec une couverture métier par dépôt et des pages de détail sur le site.
Skills dans ce dépôt
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.
Database engineering: schema migrations (expand-migrate-contract), N+1 prevention, indexing discipline, connection pooling, transaction boundaries, and data integrity constraints. Use for SQL/NoSQL tasks involving persistence, ORMs, or data modelling.
Engineering guardrails for every task: TDD (red-green-refactor), simplicity (KISS/YAGNI), complexity thresholds, and code review readiness checks. Always loaded.
Failure-handling patterns for distributed systems: timeouts on every external call, retry with exponential backoff, circuit breakers, bulkheads, and graceful degradation. Use for microservices, reliability-critical components, or any system with network deps.
Distinctive visual UI design: research the subject's own visual vernacular, build a token system (color, type, layout, signature), critique against defaults, then code. Use when building or reshaping a user-facing UI where templated defaults won't do.
Game development rules: formal rule encoding, immutable state transitions, bounded AI search (minimax/MCTS), and independent win/draw/loss verification. Use for board games, card games, turn-based strategies, or any game with defined rules.
Cross-cutting execution guardrails for all tasks: workspace discipline, verification closures, quality gates, and data integrity rules. Always loaded as the base skill.
ML reproducibility and artifact discipline: train/val/test separation, random seed recording, metric validation against task goals, checkpoint management. Use for any ML, DL, or data science task.
Production observability: structured logging (JSON, trace context), RED metrics (rate/errors/duration) per endpoint, USE metrics for infrastructure, distributed tracing, health checks, SLOs and burn-rate alerting. Use for any service-oriented or production-deployed system.
Secure-by-default engineering: OWASP Top 10 prevention, input validation (allowlist, canonicalize, reject), auth (short-lived tokens, least privilege), secrets management, dependency hygiene, output encoding, security headers. Use for any task involving user input, network access, or data storage.
Disaster response and systems recovery: controlled execution paths, backup-first discipline, build/runtime probes, and checkpoint-based rollback. Use for debugging crashes, data recovery, failover scenarios, or infrastructure repair.
Testing pyramid strategy: property-based over example-based, contract testing at boundaries, mutation coverage, fuzzing for unstructured inputs. Use when correctness and regression resistance matter.
Computer vision and media processing: CLI interface stability, coordinate alignment (row-major vs column-major), shape consistency after transformations, and output validation. Use for image processing, video analysis, object detection, segmentation.
Reference for writing and editing skills well — the vocabulary and principles (predictability, information hierarchy, leading words, completion criteria, progressive disclosure) that make a skill predictable and low-load. Use when creating a new skill, reviewing an existing one, or pruning a skill that has grown stale.
Dual-representation memory and learning system for code agents. Implements event-sourced experience logging, pattern distillation, pre-action governance, and risk-sensitive retrieval.