Productivity skills

Produces human-sounding text that avoids detectable AI writing patterns. Activates on any writing task — tweets, emails, articles, bios, captions, reports, copy, messages, LinkedIn posts, cover letters, README files, or any content where the output must not read as AI-generated. Enforces banned vocabulary, structural variety, punctuation discipline, accuracy rules, and voice calibration. Use when the user says "write," "draft," "rewrite," "make this sound human," "anti-slop," "not AI," or any variation of wanting authentic-sounding output.

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Create and manage todo tracking documents for features, bugs, and multi-step tasks. Use when starting new work that benefits from a persistent record of decisions, progress, and context.

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Set a tracking document as the source of truth for the current feature or task. Use when starting work on a feature, bug fix, or multi-step task that benefits from a persistent record of decisions, discoveries, and progress. Keeps the document updated as work proceeds.

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Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like "make me a GIF of X doing Y for Slack."

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清理文本样本中的电子邮件。当用户提到清理邮件、删除邮箱、去除邮件地址、清理个人信息等需求时使用此skill。 即使用户没有明确说出"邮件"，只要任务涉及从文本中删除或替换邮箱地址，就应该使用此skill。

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用于 Workflow Planning 阶段的占位算子。当前 Skill 库不存在满足用户需求的业务 Skill 时，使用本算子保持 DAG 数据流完整，等待后续生成真实 Skill 后替换。

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Train or fine-tune SentenceTransformer bi-encoders, CrossEncoder rerankers, or SparseEncoder models, including losses, negatives, evaluation, distillation, LoRA, and Matryoshka. Use for sentence-transformers training tasks.

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Find and compare recommended Hugging Face models for a task using benchmarks, model size, and device constraints. Use for model selection questions; use huggingface-local-models for GGUF setup and hf-cli for Hub operations.

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Run evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Use for backend selection, local GPU evals, and choosing between vLLM / Transformers / accelerate. Not for HF Jobs orchestration, model-card PRs, .eval_results publication, or community-evals automation.

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Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.

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Run the speckit preparation phases end-to-end — specify, plan, critique, tasks — making all decisions autonomously. Stops before implementation.

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Run the full speckit workflow end-to-end — specify, plan, critique, tasks, implement, review — making all decisions autonomously. Stops before extract; run that manually.

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Generate an actionable, dependency-ordered tasks.md for the feature based on available design artifacts.

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Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.

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Run the speckit implementation phase chunk-by-chunk in clean-context subagents, then review, then produce a final report. Picks up from an existing tasks.md.

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Execute the implementation plan by processing and executing all tasks defined in tasks.md

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Convert existing tasks into actionable, dependency-ordered GitHub issues for the feature based on available design artifacts.

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Goal-based workflow orchestration - routes tasks to specialist agents based on user goals

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TDD workflow for migrations - orchestrate agents, zero main context growth

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Orchestrator-only workflow for migrating/rewriting codebases with full TDD and agent delegation

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Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.

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Dynamic model selection based on task complexity scoring. Replaces static model mappings with a weighted signal system that picks Opus, Sonnet, or Haiku-class speed per task. Works with agent-assignment-matrix.md.

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Use this skill when writing new features, fixing bugs, or refactoring code. Enforces test-driven development with 80%+ coverage including unit, integration, and E2E tests.

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Agent reputation scoring, performance tier system, trust calibration, and task affinity matching

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