ReddRadar
Topic: claude
14,433 skills in this topic.
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thesis-frontmatter-sync
同步中文毕业论文的非正文部分：摘要、附录、封面、成果、致谢、名单等，确保这些部分与正文口径一致，而不是最后临时补写。
**Trigger**: 摘要同步, frontmatter sync, 附录同步, 封面检查, 非正文维护, 毕业论文摘要.
**Use when**: 正文结构已经比较稳定，需要并行维护非正文部分，避免中英文摘要、封面字段、附录和成果列表与正文脱节。
**Skip if**: 正文主线还不稳定，或者还没有任何可交付版本。
**Network**: none.
**Guardrail**: 不把非正文拖到最后一刻；不让摘要、附录与正文口径脱节。
WILLOSCAR/research-units-pipeline-skills 377
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thesis-markdown-aligner
在 Markdown 中间层统一毕业论文的主线、术语、符号、指标、图表口径与章节边界，让整篇论文先在中间层收敛成“一篇论文”。
**Trigger**: markdown 对齐, thesis markdown align, 术语统一, 符号统一, 指标统一, 章节归并.
**Use when**: 各章已经初步重构，但整篇论文仍有术语漂移、指标口径不一致、章节边界混乱或像多篇 paper 拼接。
**Skip if**: 章节角色还没定，或当前只是在局部修一章。
**Network**: none.
**Guardrail**: 不在这里回写 tex；先收敛中间层，再进入交付层。
WILLOSCAR/research-units-pipeline-skills 377
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thesis-question-list
维护中文毕业论文的 `codex_md/question_list.md`：把本轮问题、边界、优先级、协作方案和验收口径结构化，作为整条 thesis pipeline 的控制面。
**Trigger**: 毕业论文问题清单, thesis question list, 论文修改清单, 本轮目标, 结构问题梳理, review问题整理.
**Use when**: 你已经有一批材料或上一轮 review 结果，需要明确这一轮到底修什么、不修什么，并给后续重构与编译复查提供统一入口。
**Skip if**: 当前只是在做一次性局部措辞修改，且没有形成新一轮结构/证据/编译问题。
**Network**: none.
**Guardrail**: 不在这里写正文；不把问题单写成长篇散文；每条问题必须可执行、可验收。
WILLOSCAR/research-units-pipeline-skills 377
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thesis-source-role-mapper
将中文毕业论文已有材料映射到“毕业论文角色”：把论文、模板、Overleaf 源稿、PDF、图表和实验材料按章节角色、研究问题和证据用途重新归位。
**Trigger**: 毕业论文材料映射, source role map, paper to chapter, 章节角色映射, 论文归章, 材料归位.
**Use when**: 已经完成材料盘点，需要决定各份材料在毕业论文里扮演什么角色，而不是继续按原 paper 叙事直接写。
**Skip if**: 当前只是在修一个已经稳定的单章措辞，且没有新的来源材料进入。
**Network**: none.
**Guardrail**: 不是做翻译；不是简单 `paper -> chapter` 分桶；必须显式说明“在毕业论文里的角色”。
WILLOSCAR/research-units-pipeline-skills 377
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thesis-style-polisher
对中文毕业论文做最终润色与去 AI 味：重点处理章首导言、章末小结、贡献描述、总结与展望中的模板腔、宣传腔与 AI 口癖。
**Trigger**: 论文润色, thesis style polish, 去 AI 味, 中文论文风格统一, 章首导言润色, 总结展望润色.
**Use when**: 结构、证据、数据和编译已经基本稳定，需要做最后一轮中文学位论文风格收口。
**Skip if**: 正文结构还在大改，或关键引用 / 数字 / 图表还没稳定。
**Network**: none.
**Guardrail**: 不用润色掩盖结构问题；不引入新事实；先去模板腔，再做措辞提升。
WILLOSCAR/research-units-pipeline-skills 377
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thesis-tex-writeback
把已经在 Markdown 中间层收敛的中文毕业论文内容回写到 `chapters/*.tex` 与相关交付层文件，保持结构、图表、公式、交叉引用与章节承接一致。
**Trigger**: tex 回写, thesis tex writeback, md 回 tex, 章节回写, 论文交付层同步.
**Use when**: 章节主线、术语、符号和图表计划已经在 Markdown 层基本稳定，需要进入 TeX 交付层。
**Skip if**: 结构还没稳定，或者仍在章级重构阶段。
**Network**: none.
**Guardrail**: 不在这里重新发明结构；优先把结构问题回到 Markdown 层处理；TeX 层负责交付而非重新思考。
WILLOSCAR/research-units-pipeline-skills 377
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thesis-visual-layout-planner
规划中文毕业论文的图表、流程图和版面节奏：先决定哪些图表支撑主线，再做草图、拼版预演与图文映射。
**Trigger**: 图表规划, figure layout, thesis visual plan, 版面预演, 图文映射, mermaid 草图.
**Use when**: 章节结构基本明确，但图表还没有系统安排，或者担心图文节奏、图表密度和版面结构失控。
**Skip if**: 论文不依赖图表支撑主线，或仍在纯结构重构早期。
**Network**: none.
**Guardrail**: 不把图表拖成最后补丁；不先排版再倒推结构；图表服务主线而不是抢主线。
WILLOSCAR/research-units-pipeline-skills 377
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thesis-workspace-init
初始化中文毕业论文工作区：检查学校模板与已有材料的放置位置，明确提示当前还缺什么，建立 `codex_md/` / `claude_md/` / `tmp_layout*/` 等中间层目录，并生成材料盘点与初始工作文件。
**Trigger**: 毕业论文初始化, thesis workspace, 中文毕业论文准备, 模板归位, 材料盘点, 初始化论文工程.
**Use when**: 你要开始一条毕业论文重构流程，手头已经有学校模板、旧 `tex`、PDF、Overleaf 源稿、bib 或图表材料，需要先把工程和中间层搭起来。
**Skip if**: 工作区已经稳定，且 `codex_md/material_index.md`、`codex_md/question_list.md`、`codex_md/00_thesis_outline.md` 都已存在并在使用。
**Network**: none.
**Guardrail**: 不改正文内容；不把 `chapters/` 当思考区；不在 repo root 散落毕业论文工件。
WILLOSCAR/research-units-pipeline-skills 377
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transition-weaver
Generate lightweight section/subsection transitions (NO NEW FACTS) to prevent “island” subsections; outputs a transition map that merging/writing can weave in.
**Trigger**: transition weaver, weave transitions, coherence, 过渡句, 承接句, 章节连贯性.
**Use when**: `outline/subsection_briefs.jsonl` exists and you want coherent flow before/after drafting (typically Stage C5).
**Skip if**: `outline/transitions.md` exists and is refined (no placeholders).
**Network**: none.
**Guardrail**: do not add new factual claims or citations; transitions may only refer to titles/RQs/bridge terms already present in briefs.
WILLOSCAR/research-units-pipeline-skills 377
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tutorial-module-writer
Write the tutorial content (`output/TUTORIAL.md`) from an approved module plan, including exercises and answer outlines.
**Trigger**: write tutorial, tutorial modules, 教程写作, TUTORIAL.md.
**Use when**: tutorial pipeline 的写作阶段（C3），且 `DECISIONS.md` 已记录 HUMAN 对 scope/running example 的批准（C2）。
**Skip if**: module plan 未完成/未批准（先跑 `module-planner`/`exercise-builder` 并通过 Approve C2）。
**Network**: none.
**Guardrail**: 只写已批准范围；保持 running example 一致；每模块包含练习与答案要点。
WILLOSCAR/research-units-pipeline-skills 377
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tutorial-spec
Define tutorial scope, target audience, prerequisites, learning objectives, and a running example; output a tutorial spec for downstream planning.
**Trigger**: tutorial spec, scope, audience, prerequisites, learning objectives, running example, 教程规格.
**Use when**: tutorial pipeline 的起点（C1），需要先锁定教学目标与边界，再进入 concept graph / module planning。
**Skip if**: 你不是在做教程产出（或已经有明确且不允许改动的 tutorial spec）。
**Network**: none.
**Guardrail**: 结构化 spec 优先；避免提前写长教程 prose（prose 在 C3）。
WILLOSCAR/research-units-pipeline-skills 377
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unit-executor
Execute exactly one runnable unit from `UNITS.csv` (first TODO whose dependencies are DONE), then update unit status and artifacts.
**Trigger**: unit executor, run one unit, next unit, step-by-step pipeline, 逐条执行, UNITS.csv.
**Use when**: 需要严格“一次只做一个 unit”（可审计、可中断），并遵守 checkpoints/HUMAN 阻塞逻辑。
**Skip if**: 要端到端自动跑（用 `research-pipeline-runner`）或 workspace 不存在。
**Network**: none.
**Guardrail**: 只执行一个 unit；满足验收且输出存在才可标 `DONE`；遇到 HUMAN checkpoint 必须停下。
WILLOSCAR/research-units-pipeline-skills 377
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unit-planner
Instantiate or update a workspace `UNITS.csv` from a selected pipeline and units template (deps/checkpoints/acceptance).
**Trigger**: unit planner, generate UNITS.csv, execution contract, units template, 生成工作单元.
**Use when**: 初始化/更新执行合同：从 pipeline 选择生成 `UNITS.csv`，或 scope 扩展需要新增 units/依赖。
**Skip if**: `UNITS.csv` 已正确反映当前 scope（无需重写）。
**Network**: none.
**Guardrail**: 保持 CSV 合法；scope 增长时新增 units；只在满足验收后标 `DONE`。
WILLOSCAR/research-units-pipeline-skills 377
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workspace-init
Initialize a new workspace by copying the standard artifact template (STATUS.md, CHECKPOINTS.md, UNITS.csv, DECISIONS.md + folders).
**Trigger**: workspace init, initialize workspace, workspace template, 初始化 workspace.
**Use when**: 启动任何 pipeline run（必须先有 workspace 工件与目录骨架）。
**Skip if**: workspace 已初始化且不希望覆盖既有文件（除非显式 `--overwrite`）。
**Network**: none.
**Guardrail**: 不要修改 `.codex/skills/workspace-init/assets/` 模板；默认不覆盖已有文件。
WILLOSCAR/research-units-pipeline-skills 377
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writer-context-pack
Build per-H3 writer context packs (NO PROSE): merge briefs + evidence packs + anchor facts + allowed citations into a single deterministic JSONL, so drafting is less hollow and less brittle.
**Trigger**: writer context pack, context pack, drafting pack, paragraph plan pack, 写作上下文包.
**Use when**: `outline/subsection_briefs.jsonl` + `outline/evidence_drafts.jsonl` + `outline/anchor_sheet.jsonl` exist and you want to make C5 drafting easier/more consistent.
**Skip if**: upstream evidence is missing or scaffolded (fix `paper-notes` / `evidence-binder` / `evidence-draft` / `anchor-sheet` first).
**Network**: none.
**Guardrail**: NO PROSE; do not invent facts/citations; only use citation keys present in `citations/ref.bib`.
WILLOSCAR/research-units-pipeline-skills 377
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writer-selfloop
Writing self-loop for surveys: run the strict section-quality gate, then rewrite only the failing `sections/*.md` files until the report is PASS.
**Trigger**: writer self-loop, writing loop, quality gate loop, rewrite failing sections, 自循环, 反复改到 PASS.
**Use when**: per-section files exist but C5 is FAIL/BLOCKED (thin sections, missing leads/front matter, citation-scope violations, generator voice).
**Skip if**: you are still pre-C2 (NO PROSE), or evidence packs are incomplete (fix C3/C4 first).
**Network**: none.
**Guardrail**: do not invent facts; only use citation keys present in `citations/ref.bib`; keep citations in-scope per `outline/evidence_bindings.jsonl`; do not add/remove citation keys during rewrites.
WILLOSCAR/research-units-pipeline-skills 377
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agent-browser
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
petekp/claude-code-setup 20
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agent-changelog
Compile an agent-optimized changelog by cross-referencing git history with plans and documentation. Use when asked to "update changelog", "compile history", "document project evolution", or proactively after major milestones, architectural changes, or when stale/deprecated information is detected that could confuse coding agents.
petekp/claude-code-setup 20
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agent-native-architecture
Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.
petekp/claude-code-setup 20
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agent-telemetry
Make application behavior visible to coding agents by exposing structured logs and telemetry. Use when asked to "add telemetry", "make logs accessible to agents", "add observability", "debug with logs", or when an agent needs to understand runtime behavior but has no way to query logs. Also use when debugging is difficult because there are no structured logs, when agent docs (CLAUDE.md, AGENTS.md) lack instructions for querying application logs, or when setting up logging infrastructure for a new or existing web application.
petekp/claude-code-setup 20
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agentation
Add Agentation visual feedback toolbar to a Next.js project
petekp/claude-code-setup 20
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ai-sdk
Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, embed, or tools, (2) Want to build AI agents, chatbots, RAG systems, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, Google, etc.), streaming, tool calling, structured output, or embeddings, (4) Use React hooks like useChat or useCompletion. Triggers on: "AI SDK", "Vercel AI SDK", "generateText", "streamText", "add AI to my app", "build an agent", "tool calling", "structured output", "useChat".
petekp/claude-code-setup 20
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architecture-exploration
Explore and compare architectural options before committing to a large technical direction. Use when the user wants to evaluate different architectures, compare approaches, choose between competing designs, rethink a subsystem, or understand tradeoffs before a major refactor or migration. Also use for prompts like "explore the architecture", "what are our options", "compare approaches", "what design should we choose", "audit and recommend an improved architecture", or "help me think through a large architectural change" even if the user does not mention a formal architecture review.
petekp/claude-code-setup 20
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architecture-scaffold
Build a compilable type-level skeleton from a high-level architecture spec before writing any implementation logic. Use when you have an architectural assessment, design doc, or restructuring plan and need to prove the new architecture is sound before migrating code. Also use when asked to "scaffold the new architecture", "create type stubs", "build the shell", "flesh out this spec", "skeleton the modules", or any request to turn architectural intent into verified structure. This skill follows the "Human Builds the Shell" paradigm: types are hard constraints that the compiler enforces, so if the skeleton compiles, the architecture is structurally sound. Especially valuable for large refactors where you don't trust agents to maintain coherence.
petekp/claude-code-setup 20