이메일, 캘린더, 할 일 관리, 자동화 (7.8천건)
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
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Naming and classifying organisms through binomial nomenclature, the Linnaean hierarchy, type specimens, and the rules governing taxonomic authority and revision. Covers the structure of a scientific name, the ranks from domain to subspecies, the codes (ICZN, ICN, ICNP), and the modern phylogenetic refinements that reshape the classical system. Use when the task is to place a known organism in its formal hierarchy or to reason about how names change over time.
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Reading a habitat — identifying biome, plant community, food web structure, successional stage, and the keystone species that hold the system together. Covers the elevational and latitudinal gradients that Humboldt first mapped, the structural vocabulary for describing a habitat, the core concepts of food-web and trophic analysis, and the practice of diagnosing habitat health from indicator species. Use when the task is to understand a place rather than a species.
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Conjecture generation, sequence analysis, and experimental mathematics for mathematical discovery. Covers sequence analysis (OEIS lookups, recurrence relations, generating functions), pattern detection methods (finite differences, ratio analysis, modular patterns), conjecture generation workflow, classical integer sequences (Fibonacci, Catalan, partition numbers, Bernoulli numbers), combinatorial identities, the probabilistic method (Erdos, expected value arguments, Lovasz Local Lemma), AI-assisted discovery (FunSearch, Ramanujan Machine), and confidence calibration with cautionary tales (Mertens conjecture, Polya conjecture). Use when discovering patterns, analyzing sequences, generating conjectures, or working with combinatorial identities.
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Identifying species in the field using dichotomous keys, gestalt recognition, diagnostic features, and habitat context. Covers the working identification protocol from first encounter through confidence-rated record, the vocabulary of field marks, the discipline of negative evidence, and the honest reporting of uncertain IDs. Use when the task is to name a living organism encountered in the field.
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Statics, dynamics, stress-strain analysis, materials selection, failure modes, and finite element analysis concepts for engineered structures. Covers free-body diagrams, equilibrium, internal forces (shear and moment), beam deflection, column buckling, material properties, factor of safety, fatigue, fracture mechanics, and FEA workflow. Use when analyzing loads on structures, selecting materials, predicting failure, or interpreting structural behavior.
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Ecological organization, energy flow, food webs, biodiversity, succession, and species interactions. Covers trophic structure, primary productivity, nutrient transfer efficiency, keystone and foundation species, ecosystem services, carrying capacity, disturbance regimes, primary and secondary succession, and resilience metrics. Use when analyzing how living communities are organized, how energy and matter move through ecosystems, how disturbance and recovery shape landscapes, or why biodiversity matters for ecosystem function.
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Use when the user asks "what should I work on", mentions GSD phases, ROADMAP, or .planning/ artifacts. Routes to the correct GSD command for the current project state.
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Use before you shorten, compress, or rewrite the BODY of an existing SKILL.md or agent .md — the moment you are about to cut text to reduce length. First inventory the file's operational anchors (exact code / command / API snippets, fail-closed workflow guards, and rule / threshold statements), preserve every one, then judge the rewrite by expected downstream task cost (exploration, debugging, recovery tokens) rather than by the resulting line count. A shorter skill that strips an anchor makes the agent MORE expensive per task, so length is never the objective and rewrite is not compression. Backed by Preserving Operational Anchors When Compressing Agent Instructions (arxiv 2606.09421v2). Triggers on shortening or refactoring a skill or agent body.
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Unit Circle Laboratory + sc-dev-team autonomous mission control. Provides human-in-the-loop automation layer, pipeline management, context lifecycle, stuck-state prevention. UC re-execution series and dev branch milestones. Adapted from uc-lab pattern for code plan/execute/verify/complete. Auto-activates during UC milestone work; trigger: user says 'bring up the dev team'.
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Creates context handoff documents for session continuity. Use when ending sessions, switching tasks, or handing off work.
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Deterministic git operations with state verification for skill-creator managed repos. Use when managing repos, branches, worktrees, or contribution workflows.
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Extract Gherkin scenarios from story markdown files into runnable .feature files and generate step definition stubs. Use when syncing stories to test suites.
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Universal dispatcher: run a named taffy workflow (.claude/taffy/<name>.yaml), a skill (/skill-name), or a sub-agent (@agent-name). Falls back to skills.sh registry when a skill is not found locally. Tracks all runs in .claude/state/maple.json so the maple TUI shows live progress.
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Drive development with a red-green-refactor TDD cycle, ensuring tests are written before implementation. Use when implementing any new functionality.
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Best practices for authoring clean, maintainable, and portable GNU Make Makefiles. Use when the task involves `creating or editing Makefiles`, `Makefile`, `makefile`, `*.mk`, `GNUmakefile`, `GNU Make patterns`, `build automation`, or `makefile troubleshooting`.
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Optimize Core Web Vitals (LCP, INP, CLS) for better page experience and search ranking. Use when the task involves `improve Core Web Vitals`, `fix LCP`, `reduce CLS`, `optimize INP`, `page experience optimization`, or `fix layout shifts`.
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Google Calendar management via CalendarACSet. Transforms scheduling operations into GF(3)-typed Interactions, routes to triadic queues, detects saturation for balanced-calendar-as-condensed-state.
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CatColab Petri Nets - concurrent system modeling via places (states), transitions (events), and token flow. Foundation for process algebra, workflow, and chemical reaction networks.
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Primary Python tool for 40+ bioinformatics services. Preferred for multi-database workflows: UniProt, KEGG, ChEMBL, PubChem, Reactome, QuickGO. Unified API for queries, ID mapping, pathway analysis. For direct REST control, use individual database skills (uniprot-database, kegg-database).
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Persist and retrieve repository-specific knowledge using AGENTS.md files. Use when you want to save important information about a codebase (build commands, code style, workflows) for future sessions.
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This skill should be used when agents generate placeholder tokens like "pseudo-", "mock-", "temporary", "TODO", "demo-", or similar incompleteness markers. Detects substitution patterns in agent OUTPUT and triggers mandatory user interview instead of accepting incomplete work. Activates automatically on any output containing forbidden tokens.
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Model ElevenLabs voice synthesis as an ACSet schema with Unison ability handlers for typed voice operations. Use when integrating ElevenLabs TTS into category-theoretic pipelines, building typed voice synthesis workflows, or managing multi-voice narration with GF(3) conservation.
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Interview a user to discover a concrete GTM problem or manual task, recommend the right installed Deepline skill, prebuilt Play, recipe, or tool, confirm the plan and org, then start the chosen workflow. Use only when the user explicitly invokes deepline-start.
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