仕事効率化のスキル

Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.

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Use for formulating, solving, debugging, and validating mixed-integer linear optimization models with open-source solvers, including variable indexing, sparse constraints, linearized costs, solver limits, MIP gaps, incumbent extraction, numerical tolerances, and deterministic output reporting.

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Permutation and sequencing integer-programming formulations with ordered local-window variables, prefix/suffix continuity, and overlap penalties. Use when assigning exams, jobs, tasks, visits, blocks, or resources to ordered positions and costs depend on adjacent pairs, sliding triples, n-grams, short-horizon pressure, or overlapping local patterns.

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Manage Gmail - send, read, search emails, manage labels and drafts. Use when user wants to interact with their Gmail account for email operations.

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Cheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms.

日本語の概要は準備中です。原文の説明を表示しています。

Parse scheduling constraints from a email text.

日本語の概要は準備中です。原文の説明を表示しています。

Set up goreleaser for Go release automation with cross-compilation and publishing.

日本語の概要は準備中です。原文の説明を表示しています。

Implement email and push notification delivery systems — transactional email, notification templates, delivery tracking, and bounce handling.

日本語の概要は準備中です。原文の説明を表示しています。

Build medical AI agents for clinical decision support, medical record summarization, diagnostic assistance, and healthcare workflow automation.

日本語の概要は準備中です。原文の説明を表示しています。

Convert technical plans into actionable development tasks with dependency graphs, effort estimates, and parallelization opportunities.

日本語の概要は準備中です。原文の説明を表示しています。

Conditional edge routing and state-based transitions for LangGraph workflows

日本語の概要は準備中です。原文の説明を表示しています。

LangGraph checkpoint and persistence configuration for stateful workflow management

日本語の概要は準備中です。原文の説明を表示しています。

Perform cross-artifact consistency and coverage analysis across constitution, specification, plan, and task artifacts to detect gaps, conflicts, and misalignments before implementation.

日本語の概要は準備中です。原文の説明を表示しています。

Human-in-the-loop integration for LangGraph workflows with approval and intervention points

日本語の概要は準備中です。原文の説明を表示しています。

Use when executing implementation plans with independent tasks in the current session. Dispatches fresh subagent per task.

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Use when you have a spec or requirements for a multi-step task, before touching code. Creates bite-sized TDD implementation plans with dependency tracking.

日本語の概要は準備中です。原文の説明を表示しています。

Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies.

日本語の概要は準備中です。原文の説明を表示しています。

Hierarchical coordination and drift detection with frequent checkpoints, shared memory coherence validation, role specialization enforcement, and short task cycles.

日本語の概要は準備中です。原文の説明を表示しています。

State capture and restore across context window compactions. Monitors usage thresholds and serializes quality, task, and spec state for seamless continuation.

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STATE.md reading, writing, and field-level updates. Provides cross-session state persistence via .planning/STATE.md with structured fields for current task, completed phases, blockers, decisions, and quick tasks.

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Personalize COG Second Brain workflow through role pack selection and vault initialization

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Discover public GitHub repositories that import defineTask from @a5c-ai/babysitter-sdk and maintain a deduplicated catalog of those repositories in docs/repo-with-babysitter-processes.md. Excludes any repo named "babysitter" (to filter out forks of this monorepo). Invoke when asked to find, discover, catalog, or refresh "repos using babysitter", "babysitter in the wild", or "who else is using babysitter".

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This skill should be used when the user asks to "fix pipelines", "fix CI", "check staging pipelines", "fix failing workflows", "fix failing actions", or wants to find and fix failing GitHub Actions workflows on the staging branch of the babysitter repo.

日本語の概要は準備中です。原文の説明を表示しています。

This skill should be used when the user asks to "find skills in the wild", "assimilate popular workflows", "discover SKILL.md files in repos", "research external skills", "find workflow patterns", "survey the skill landscape", "what skills exist out there", or wants to investigate public repositories for extractable processes, babysitter plugins, and reusable procedural insights. Searches GitHub for SKILL.md files, classifies repos by archetype, and maintains structured research under docs/reference-repos/.

日本語の概要は準備中です。原文の説明を表示しています。