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Found 505 Skills
Standardized artifact creation via tk tickets. Use whenever a skill needs to persist output — research findings, plans, postmortems, reviews, design specs, decisions. Replaces all bespoke output directories (.oracle/, .plans/, etc.) with a single canonical system.
Persistent memory that survives across conversations. Automatically remembers important context (API specs, decisions, quirks, preferences) and saves session summaries. Searches past knowledge before starting new tasks. Responds naturally to phrases like "remember this", "what do you know about...", "save this session", or "what did we do last time". All local, zero network.
Create implementation plan documents with development phases, sequencing, and actionable tasks. Works through 3 phases (structure, approach, generation) following established feature development process. Use when creating plan.md documents from technical specs. Triggers on "create implementation plan", "plan this feature", "sequence the development".
Generate and prioritize US equity long-side edge research tickets from EOD observations, then export pipeline-ready candidate specs for trade-strategy-pipeline Phase I. Use when users ask to turn hypotheses/anomalies into reproducible research tickets, convert validated ideas into `strategy.yaml` + `metadata.json`, or preflight-check interface compatibility (`edge-finder-candidate/v1`) before running pipeline backtests.
Specification quality checker for spec-generator documents. Validates requirement.md, design.md, tasks.md for consistency, completeness, and quality. Detects requirement ID mismatches, missing sections, contradictions, and ambiguous expressions. English triggers: "inspect specs", "check specification quality", "validate requirements" 日本語トリガー: 「仕様書を検査」「品質チェック」「仕様を検証」「spec-inspect実行」
Daily/weekly/monthly/git log population and session context management. Use when: (1) writing daily closeout log; (2) rolling up weekly/monthly memory; (3) recording git summary; (4) starting/ending sessions; (5) creating specs or docs. NOT for: task management (use task); compound loop (use work).
REST and GraphQL API design best practices including OpenAPI specs. Use when designing APIs, documenting endpoints, or reviewing API architecture.
Create task documents for new features, updates, or fixes. Creates detailed specs in docs/task/*.md with full implementation context. Updates TASKS.md for tracking. Use when starting any new work.
React Email renderer for json-render that turns JSON specs into HTML or plain-text emails using @react-email/components and @react-email/render. Use when working with @json-render/react-email, building transactional or marketing emails from JSON, creating email catalogs, rendering AI-generated email specs, or when the user mentions react-email, HTML email, or transactional email.
Code generation utilities for json-render. Use when generating code from UI specs, building custom code exporters, traversing specs, or serializing props for @json-render/codegen.
Use when creating or iterating on a detailed per-subsystem technical design specification from a system spec, before starting OpenSpec workflow. Triggers: "design spec", "subsystem spec", "write the spec for S1", "phase breakdown", "implementation phases", "mid-level spec", "technical design". Encodes opinionated progressive phase discipline with FP progression and contract boundaries. Do NOT use for high-level system specs (use brainstorming) or for OpenSpec artifacts (use openspec directly).
Umbrella skill for agent work discipline across development, analysis, and documentation: inspect the repo before restructuring, keep durable truth in repo artifacts instead of chat memory, co-evolve specs/design/steering/user docs with code, apply sound coding patterns, verify work honestly, avoid shortcuts, work efficiently with subagents without hallucinating, and keep moving through the next concrete work item when the human is away. References cover coding patterns, AI-authored code review, and artifact co-evolution. Trigger when the user asks for workflow discipline, coding patterns, doc/artifact maintenance, code review of AI-authored code, project hygiene, execution guardrails, repo normalization, or when a task risks drifting across architecture, storage, specs, continuity, or tooling boundaries.