Claude Skills
The open format is called Agent Skills and works in Claude Code, Codex, Cursor and other agents — most people know it as Claude Skills.
Every Agent Skill we could find on GitHub, deduplicated by content. 86 696 files from 2 113 authors, of which 68 413 are unique — the rest is the same skill repackaged into someone else's repository. For each one: what it weighs in tokens, whether it ships runnable scripts, and which MCP servers it needs.
当用户明确要求"测试项目"、"运行 auto-test-project"或"进行项目级测试"时使用。对完整项目进行多轮 A 轮批判性测试 + B 轮质量检查，系统化发现、记录、修复问题。⚠️ 不适用：用户只是想优化功能（应直接修改）、只是询问项目问题（应直接回答）、没有明确"测试"意图。
后端开发专家。精通 Node.js/Python/Go/Rust 等后端技术栈，专注于 API 设计、数据库优化、认证授权、微服务架构和性能调优。用于后端服务开发、API 设计和系统架构。
上下文优化专家。专注于长对话中的上下文管理、token 效率和性能优化。解决 lost-in-middle、context poisoning 等问题，提升 AI 代理在复杂任务中的表现。
文档专家。专注于技术文档编写、API 文档生成、README 优化和文档维护。提供清晰的文档结构、规范的格式和用户友好的内容。
DevOps 与运维专家。精通 CI/CD、容器化、编排、基础设施即代码、监控告警和自动化部署。用于构建高效、可靠的软件交付流水线和运维系统。
Git 工作流专家。规范化版本控制，确保提交历史清晰可追溯。支持 Conventional Commits 规范、Pull Request 最佳实践、分支管理策略和自动化工作流。
Use when executing implementation plans with independent tasks - dispatches fresh subagent for each task with code review between tasks, enabling fast iteration with quality gates. Supports orchestrator, peer-to-peer, and pipeline coordination modes.
前端开发专家。用于前端应用、页面、组件、现有 UI 增量改进、已有页面视觉优化、UI/UX 改造、视觉重设计、响应式布局、表单和输入框视觉一致性、设计系统落地、React/Vue/Next.js/Nuxt、Tailwind、shadcn/ui、Radix、MUI、AntD、仪表盘、SaaS、Landing Page、移动端适配、前端性能优化、浏览器截图检查和去除 AI 味 UI。触发后应把“做好看”转化为可执行设计约束，优先复用项目现有组件与视觉语言，小步实现并尽量通过浏览器或 Playwright 做视觉反馈闭环；当用户要改进当前页面或已有界面时，默认先诊断再做局部优化，而不是从 0 重做。
当用户明确要求"优化镜像源"、"配置国内镜像"、"加速部署"、"切换镜像源"或项目涉及 Docker/Python/Node.js/Go/Java/Ruby/Rust 等需要包管理器的场景时使用。自动检测项目使用的包管理器，生成适配的国内镜像源配置，确保在国内网络环境下快速部署。⚠️ 不适用：用户只是想了解镜像源概念（应直接说明）、项目已完成部署且无需优化（应直接告知无需操作）、用户明确要求使用官方源（应尊重用户选择）。
安全专家。专注于应用安全、威胁建模、安全合规和数据保护。提供安全审查、漏洞扫描、安全配置和合规检查。用于构建安全可靠的应用系统。
Use when asked to create, review, or revise a multi-step implementation, bug-fix, or change plan before editing code, including existing plans that may use a legacy task-by-task template. Produce a problem-first plan that non-technical readers and implementers can both understand.
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes - four-phase framework (root cause investigation, pattern analysis, hypothesis testing, implementation). NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST.
Use when implementing any feature or bugfix, before writing implementation code - write the test first, watch it fail, write minimal code to pass; ensures tests actually verify behavior by requiring failure first. Enforces RED-GREEN-REFACTOR cycle with iron-law compliance.
当用户明确要求"优化 prompt"、"改进提示词"、"润色指令"或"将简陋 prompt 转换为最佳实践版本"时使用。基于 OpenAI 和 Anthropic 官方最佳实践，对用户提供的简陋 prompt 进行结构化优化，输出符合社区标准的高质量版本。
当 Bensz 系列 skills 在真实用户环境中因 skill 设计缺陷而出现 bug，或用户明确说“我想 report bensz skills bugs”“帮我公开上报 bensz skills 的 bug”时使用。该 skill 负责把 bug 规范化记录到 `~/.bensz-skills/bugs/`，并在用户明确要求公开报告时通过本地 `gh` 轻量上传到 `huangwb8/bensz-bugs`，全程严禁修改用户本地 Claude Code/Codex 中已安装 skills 的源代码。
当用户明确要求“压缩/瘦身/精简某个 Agent Skill 的 Markdown 文档”“在不改变功能前提下降低 skill 上下文开销”时使用。先理解目标 skill 的真实能力与安全边界，再在忽略 `tests/`、`plans/` 以及目标 skill 的 `README.md`、`CHANGELOG.md` 的前提下，压缩 `SKILL.md`、`references/*.md` 等工作型 Markdown，并把中间产物隔离到 `.bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/compact-bensz-skills/`。⚠️ 不适用：用户主要想新增功能、修复脚本逻辑、批量改代码、或只想压缩非 skill 文档。
当用户明确要求"提交 Git 改动"、"生成 commit 信息"或"创建 git commit"时使用。仅用 Git 分析改动并自动生成 conventional commit 信息（可选 emoji）；必要时建议拆分提交，默认运行本地 Git 钩子（可 --no-verify 跳过），提交后默认自动 push（可 --no-push 跳过）。
当用户明确要求“review 某个 GitHub PR”“评估某个 pull request 是否值得 merge”“帮我判断这个 PR 怎么处理”时使用。基于用户提供的 GitHub 仓库地址、PR 编号/链接和补充说明，进行只读、证据驱动的 PR 审查：理解 PR 解决的问题、评估方案优劣与局限、默认优先使用内置“好 PR”标准并在必要时联网补充、识别恶意或高风险改动，并输出是否建议 merge 的 Markdown 决策报告。⚠️ 不适用：用户要你直接修改 PR 代码、直接 merge PR、或在本地执行 PR 分支中的不可信代码。
当用户明确要求"初始化项目"、"创建项目指令文件"或"生成 AGENTS.md"时使用。完全自动化：自动检测操作系统默认语言，分析项目目录结构（支持 Python/Web/Rust/Go/Java/数据科学/文档项目等），推断项目类型和用途，一键生成规范的项目指令文档。生成结果包括：AGENTS.md（跨平台通用项目指令，Single Source of Truth）、CLAUDE.md（Claude Code 特定适配，通过 @./AGENTS.md 引用）、README.md（项目介绍与使用方法）、CHANGELOG.md（项目变更记录）、.gitignore（Git 忽略规则，安全优先），并在完整初始化时自动补齐 `docs/` 与 `docs/plans/`。
当用户明确要求"发布项目到 GitHub"、"创建 GitHub Release"或"生成 Release Notes"时使用。智能分析 tag 间历史变化，生成专业且吸引人的 Release Notes，自动创建 GitHub Release。支持首次发布、常规版本、预发布版本（alpha/beta/rc），自动识别 prerelease 标记。
当用户明确要求"并行执行同一条 Vibe Coding 指令 / 多个独立 agent 或 subagent 同时审查、想方案、优化、对比多条路线 / 多线程独立尝试"时使用。默认使用智能模式：由宿主原生 subagent 独立分析并由主 agent 汇总；智能模式和代码模式必须使用同一套 `.bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/parallel-vibe/{yyyy-mm-dd-hh-mm}/` 运行目录、`@main/plan.json`、thread `workspace/`、`RESULT.md` 与 `runner.log` 契约，区别只在底层执行机制；当用户要求脚本 runner、plan-file、resume、跨 CLI runner、退出码或无可用 subagent 时，切换到代码模式并调用 `scripts/parallel_vibe.py`。⚠️ 不适用：普通 shell 并发、单元测试并发、下载任务、要求强安全隔离或处理高度敏感数据。
当需要把本仓库 pipelines/skills 下的所有 skills 安装到系统级（默认同时安装到 Codex: ~/.codex/skills 和 Claude Code: ~/.claude/skills），以便在任意项目/对话中可被发现与调用时使用。使用 MD5 哈希进行版本控制，仅安装有更新的 skills；支持 --skill 指定单个或少量技能安装/更新、强制覆盖安装、指定单一目标安装和远程安装模式（--remote --check/--auto）。
当用户明确要求"生成技能 README"、"编写用户指南"或"更新技能文档"时使用。为 Agent Skills 编写符合最佳实践的 README.md 用户使用指南。自动分析技能结构（SKILL.md、config.yaml、scripts/），按模板生成小白友好的文档。
| Azure Cosmos DB performance optimization and best practices guidelines for NoSQL, partitioning, queries, and SDK usage. Use when writing, reviewing, or refactoring code that interacts with Azure Cosmos DB, designing data models, optimizing queries, or implementing high-performance database operations. cross-partition queries, SDK singleton, CosmosClient, container modeling, change feed, bulk operations, vector search, full-text search, hierarchical partition keys, global distribution, autoscale throughput, indexing policy. Azure SQL, Cosmos DB for PostgreSQL (vCore), Cosmos DB for MongoDB vCore, Azure DocumentDB, general SQL databases, Redis, Elasticsearch.
Detect Frappe project type, installed apps, version, and tooling. Use as the first step when working on any Frappe/ERPNext codebase to understand the project structure before making changes.
Production-grade architectural patterns for building enterprise Frappe apps like CRM, Helpdesk, and HRMS. Use when designing complex multi-entity systems with workflows, SLAs, and integrations.
Build REST and RPC APIs in Frappe including whitelisted methods, authentication, and permission handling. Use when creating custom endpoints, integrating with external systems, or exposing business logic via API.
Customize Frappe Desk UI with form scripts, list view scripts, report scripts, dialogs, and client-side JavaScript APIs. Use when building interactive Desk experiences, adding custom buttons, or scripting form behavior.
Create and modify Frappe DocTypes including schema design, controllers, child tables, and customization. Use when building data models, adding fields, or implementing document lifecycle logic.
Scaffold and architect custom Frappe apps including app structure, hooks, background jobs, service layers, and production hardening. Use when creating new apps, setting up app architecture, or implementing cross-cutting patterns like caching, logging, and error handling.
Use Frappe Manager (FM) for Docker-based development and testing environments. Use when setting up local dev, running isolated tests, or managing agent-driven Frappe development workflows.
Build modern Vue 3 frontend apps using Frappe UI with components, data fetching, and portal pages. Use when creating custom frontends, SPAs, or portal interfaces for Frappe applications.
Create reports in Frappe including Report Builder, Query Reports (SQL), and Script Reports (Python + JS). Use when building data analysis views, dashboards, or custom reporting features.
Route to the appropriate Frappe skill based on task type. Use as the entry point when working on Frappe projects to determine which specialized skill to apply.
Write and run tests for Frappe apps including unit tests, integration tests, and UI tests. Use when adding test coverage, debugging test failures, or setting up CI for Frappe projects.
Build public-facing web forms for data collection without Desk access. Use when creating customer submission forms, feedback forms, or self-service portals with Frappe Web Forms.
UI/UX patterns and guidelines derived from official Frappe apps (CRM, Helpdesk, HRMS). Use when designing interfaces for custom Frappe applications to ensure consistency with the ecosystem.
Phase 1 ORCHESTRATOR of a movie/comic — turn a fuzzy story idea into the Authored Source of Truth (a schema-valid comic.json + its locked asset library) by driving the detailed author skills in order (intent → style → outline → storyboard → assets → blueprints → prompts → comic.json), each gated by comic-cross-layer-gate, so comic-director (Phase 2/3) can bake + cross-model-verify it. You don't hand-write comic.json; this is the workflow your agent runs to author it. Use when the user says "做个漫画/电影", "from this idea make a comic", "author the comic.json", "run the comic pipeline".
Phase 2/3 of a movie — bake + cross-model-verify a movie from an authored comic.json. Per frame: render the content-SVG blueprint, bake via the agent mcp__codex__codex sidecar, gate with a 3-reviewer cross-model panel (narrative [currently the codex CLI] ‖ Gemini visual ‖ Codex visual, deterministic fuse), keep/retry/assemble, write the wiki trace, project to the viewer. The movie-side twin of method-figure's render half. (Author the comic.json first with the comic-author skill.)
Phase-1 (S4) of a comic movie — PRODUCE the canonical reusable references the whole spiral conditions on. Per asset it bakes ONE canonical 1:1 white-bg identity ref via the agent mcp__codex__codex sidecar bake (Codex native image_gen — conditioned, never hand-pasted) OR, for a deterministic motif (clock/chart/stamp/star-map), emits a single-source parametric SVG from a python generator (asset_lib.py). Hashes + base64-encodes the bake into the asset node's output_ref (all 6 fields or it's a schema violation), versions every ref _v{NNN} with a supersedes self-edge, and runs a single-source collision gate. GENERATES ONLY — it NEVER self-locks/approves (that is the cross-model asset-review-loop's job, a different model family). Identity is BRING-YOUR-OWN; the ARIS chibi duo is only the worked example.
The authoring-side DIEGETIC continuity AUDIT — it produces the world-state evidence that comic-cross-layer-gate `--gate continuity` adjudicates against the storyboard's MOTIF STATE TABLE (motif_ledger). It checks each baked panel STRICTLY against the pre-committed table row, then emits a continuity review-node the gate fuses (it does NOT own a bake-time KEEP). Gemini auto-gemini-3 is the per-panel FACT extractor (one analyzeFile per panel image, fact-only); Claude is the deterministic JUDGE against the table row + the global invariants (DDL countdown monotonic never-rewind, bounce S02 = the film's ONLY MAX, the two metric columns never co-mingle, the non-adjacent MIRROR LOCKS). CAST-AWARE: a panel simply NOT containing a character is design, NEVER a drift penalty (absence≠drift). On a same-panel miss it requests `retry_panel`; a cross-frame motif break is routed into the page assembly_gate's drift set (seed-anchored comic panels are independent — no cross-panel rollback). Use when the user says "查连续性", "continuity audit", "连戏检查", "world-state drift", "motif table check", "对一下分镜表", or a panel has been baked and you need to verify it realized its motif-table row.
Phase-1 (S7 of the comic-author suite) — turn ONE locked panel_spec into a deterministic content-SVG blueprint that becomes the bake condition (reference #1 of the agent mcp__codex__codex sidecar bake), by WRITING A PYTHON GENERATOR (never raw SVG in chat — LLMs botch coordinates). The HEADLINE comic-pivot rule: the image bakes NO bubbles at all — draw only characters + scene + leave negative-space SAFE ZONES; HTML/CSS owns the entire bubble. Every panel gets a content_svg (a figure OR a layout blueprint); a baked figure-panel must declare expected_literals verbatim. Single-source collision check is mandatory. Gated by comic-cross-layer-gate --gate blueprint. Use when the storyboard is locked and you need each panel's deterministic generation condition; do NOT use to bake the panel (that is comic-director) or to write the verdict-stamp/curve assets (that is comic-asset-ref-generator).
Phase-1 (S5) UPSTREAM ref-asset gate — the bounded cross-model adversarial loop that LOCKS one reusable identity-locked asset (character sheet / location plate / prop cutout / text-panel / logo-free symbol) BEFORE it can be composited into any panel. This is NOT the panel_gate (composed-output) or the assembly_gate (cross-panel) — it gates the refs that FEED both, so identity drift is caught at the source, not downstream. Two layers: (1) a MANDATORY static single-source collision check (check_asset_collisions.py — 'one visual dialect, never two', enforced by tool) + zero-text/literal build-asserts; (2) a per-round 3-reviewer panel (Claude narrative ‖ Gemini visual ‖ Codex synth) that blind-scores 5 dims and LOCKS only at 准×3 unanimity (prior_lock_count>=3 approvals in the SAME round) — else regenerate (route to comic-asset-ref-generator) or, at MAX_REVIEW_ROUNDS, escalate the asset REQUIREMENT back to outline/storyboard. Hard IP veto. Use when you say 'lock this character ref', 'asset gate', 'ref review', 'is this sheet reusable', '锁角色 ref', before any metered panel bake.
The ONE parameterized score-fuser for EVERY comic-author authoring gate — `--gate intent|outline|asset|storyboard|blueprint|continuity|p0_proof|compile`. A single fuser (not a per-layer split) prevents drift. It NEVER re-runs a reviewer; it collects the reviewer score-nodes already on the wiki (via `reviews` edges), fuses them deterministically (min-fuse per dim, max for inverted dims, SKIP missing dims — never substitute 0), then a Codex xhigh adjudicator (NO model pin — follows the local codex config) that sees ONLY structured inputs (scores + tags + raw artifact PATHS + verbatim source context + verbatim rubric — NEVER reviewer prose) makes an asymmetric call (threshold HARD-vetoes "advance"; Codex SOFT-vetoes everything else). The `--gate p0_proof` mode is the zero-credit pre-production proof: a text-only cross-model adversarial review of the pipeline's CODE + IR-CONTRACT + ENGINE state-machine that MUST clear all blockers in BOTH non-author families and then MINT the digest-bound decision:p0_proof certificate via scripts/run_p0_proof.py BEFORE a single metered image-generation credit is spent. Use when a sibling step (intent-parser, outline-creator, asset-review-loop, storyboard-creator, blueprint-author, continuity-audit, json-compiler) defers its acquittal to "the gate", or the user says "过 gate", "cross-layer gate", "审这一层", "p0 proof", "证明流水线再花钱".
Phase-1 comic-author step (post-final eval) — a DOUBLE-BLIND A/B of two FINAL whole comics: our cross-model-audited progressive render (the comic-author + comic-director output) vs a naive single-shot baseline. A single sealed coin-flip hides which is which; two cross-model reviewers (Codex + Gemini) score both on a fixed rubric reading only a SHARED blind spec (intent + ART_BIBLE); only AFTER both reviews land do we unseal, re-label, and write a Chinese comparison.md + the A/B verdict nodes. editability/traceability is the structural wedge that can win even when the baseline looks prettier. Use when the user says "和 baseline 比", "blind comparison", "A/B 评测", "对比 baseline", "盲评", "whole-comic vs one-shot", or a finished comic needs a baseline-relative honest verdict. NOT an authoring skill and NOT the per-panel panel_gate / assembly_gate — those run DURING production; this runs AFTER, on two complete works.
Phase-1 Layer-0 of the comic-author suite — turn ANY raw idea / a locked video skeleton / an audience note into ONE schema-valid intent_spec node that fixes the logline (an editorial climax), the tagline, and the named DUAL-IDENTITY design constraint the whole comic optimizes against. Codex-as-parser (raw bytes + schema, never Claude's gloss) + reviewer-independence + banned-vocab lint + confidence-gated under_review routing + a HARD user-approval gate. It NEVER invents panels, assets, or storyboard detail, and NEVER silently defaults — every assumption becomes an uncertainties[] entry. Use it whenever a comic starts from a fuzzy brief and you need a locked, auditable premise before outlining.
Phase-1 (S9, the FINAL comic-author step) — assemble the LOCKED storyboard + locked per-panel blueprints into ONE schema-valid `comic.json` (the comic-ir/1.0 contract boundary handed to comic-director / run_comic.py). Project the page_order + each panel's condition{} + render fields into `pages[]` + keyed `panels{}` per schemas/comic.schema.json; author ONLY authored fields and leave image_path/active_attempt_id/wiki_node_id EMPTY for the engine. THE step where page-count integrity is reconciled and the orphan-panel class of bug is caught (a panel defined in panels{} that no page references — ship that and the finale silently vanishes) — caught by an INLINE whole-comic reconcile this skill runs (page_refs vs panels{} keys vs the storyboard page_order), because the deterministic scripts are per-page and the schema leaves condition/content_svg OPTIONAL. Gated by comic-cross-layer-gate --gate compile (the DETERMINISTIC gate: both run_comic.py --dry-run AND cli/validate_wiki.py must exit 0). Use when the user says '编译 comic.json', 'compile the comic', 'assemble comic.json', '出 comic.json', or the storyboard + all blueprints are locked and you need the single IR to hand to Phase 2/3. Do NOT use to author the page order (that is comic-storyboard-creator) or to bake panels (that is comic-director).
Phase-1 step of comic-author — the DETERMINISTIC compiler (搬运工原則) that turns ONE gate-approved panel_spec + its status:locked blueprint into the EXACT fixed-section bake string for the spiral engine via the shipped scripts/build_prompt.py (+ the canonical scripts/_validate.py vetoes). No Codex call in the happy path; it only emits, the engine bakes. Composes style_prefix + condition_string, injects the active failure_mode repair note on retry, and hard-REJECTS banned vocab (camera/lens/lighting/quality padding). Routes html_bubbles[] to the JSON viewer overlay, NEVER into the bake string (no baked bubbles unless the panel is text_mode:baked). Refuses unless the upstream blueprint is status==locked (the cross-layer gate's hand-off token) and every ref is a REAL locked asset path. Use when a panel_spec is locked and you need its prompt_bundle, just before comic-director's panel_gate.
Phase-1 (S2) of the comic-author suite — compile the project's ART_BIBLE.md into an EXECUTABLE convergence target, not aesthetic prose. The bible is the ONE visual dialect read verbatim into every bake prompt AND into every visual reviewer's rubric (`style_consistency`/`identity_consistency` literally = 'conforms to this file'). A `bootstrap` parses the bible into immutable per-dimension `style_anchor` wiki nodes (palette / line / shading / two-world warm-vs-cyber lighting / identity-lock / per-world STYLE_PREFIX / text-mode / forbidden / by-design exceptions); a deterministic `validate` lints candidate authoring text against the FORBIDDEN list + identity-lock + world-mismatch; an append-only `update` Gemini-harvests recurring drift from KEEP panels into by-design exceptions. Auto-bootstrap if the bible is missing; otherwise LEAVE LOCKED. Locked anchors are immutable — pivoting the style = a fresh project, never an in-place edit.
Phase-1 Layer-2 of a comic — turn a LOCKED skeleton (intent_spec + the pre-locked beat/shot list) into an approved outline_spec: a 6-column beat table that binds every ARIS capability to a STORY COST, plus the continuity-motif contract the storyboard layer will be held to. NOT free creation — editorial adaptation of a pre-locked skeleton via 3 parallel lenses → cross-model (Codex) synthesis → a density/restructure pass → a USER-approval HARD GATE. Cross-model synthesis is part of authoring here, not post-review. Author the comic.json downstream with comic-storyboard-creator + comic-blueprint-author; this skill only produces the outline + motif contract.
Phase-1 comic-author step — turn a LOCKED, user-approved outline into the page-first storyboard that IS the authoring source of truth: a fixed page order BEFORE any prose, the MOTIF STATE TABLE (the master per-panel continuity ledger), a fixed 9-field per-panel spec, and one deduped canonical asset contract. Decompose beats→pages→panels, 抽卡 K page/panel-order lineages by feasibility, then fill every panel one unit at a time. Writes a storyboard_spec + a motif_ledger (read by comic-continuity-audit) + N panel_spec nodes. Use when the user says "做分镜", "storyboard", "排页", "panel spec", "分镜稿", or the outline layer is locked and approved and you need the per-panel authoring layer the thin comic-author SOP defers to. Two-stage under the N1 contract: a PROVISIONAL structural gate pass on draft assets now, the FINAL asset-resolution validation after the asset layer locks.
Generate a publication-grade method / architecture / pipeline / workflow figure (a paper or README 'Figure 1') as an AUDITABLE object, not a one-shot prompt. A deterministic JSON blueprint LOCKS the content; an image model (gpt-image-2, baked by the agent via mcp__codex__codex — Codex GPT-5.5 xhigh, sandbox workspace-write) bakes the aesthetic from a labeled-condition render + the project's real identity refs; a cross-model panel (Gemini + Codex) blind-transcribes the result and a script hard-diffs it against the blueprint; the loop regenerates until Gemini AND Codex approve and the diff is empty — then the calling agent (Claude) gives the structural sign-off. NOT for statistical plots (use a plotting tool) or photo scenes.
End-to-end Pipeline A in ONE slash-command — turn a fuzzy story idea into a cross-model-audited, image-based movie + a clickable viewer. Chains comic-author (Phase 1 — intent→style→outline draft→provisional storyboard→assets→final locks→blueprints→prompts→comic.json) → the zero-credit p0_proof spending gate (agent fan-out + run_p0_proof.py mints the digest-bound certificate) → comic-director (Phase 2/3 — the agent-sidecar bake spiral, page by page → HTML viewer). Two hard HUMAN gates (intent + outline) pause for approval; everything else is agent-driven + cross-model gated. This is the slash-command entry, like ARIS's /research-pipeline — an AGENT workflow, NOT a shell binary. Use when the user says "/movie-pipeline '…'", "做个电影/漫画 end-to-end", "from this idea make the whole movie", "long-horizon image-based movie generation".
Create, tighten, or review runnable /goal contracts for coding agents such as Codex, Claude Code, Cursor, and similar agent tools. Use when the user asks to write, make, generate, improve, productize, or critique a goal prompt, rescue contract, GOAL.md-style task, done-when contract, verification prompt, stop-rule prompt, or when they want to convert a vague engineering request, issue, PR, CI failure, bug report, plan, or backlog item into one measurable coding-agent task. Prefer source-backed goal patterns when available, use seed patterns only as raw reusable shapes, and output the goal contract or review rather than implementing the underlying code task.
Use when the user asks for journal recommendation, 选刊, 投稿期刊筛选, 期刊匹配, 适合投稿的期刊, 投哪个期刊, or wants 3-5 suitable journals for a manuscript based on an abstract, discipline, CAS/JCR ranking, impact factor, Aims & Scope, review speed, OA/APC, and publication-risk checks.
Expert Go backend engineer skill. Use when writing Go services, APIs, microservices, CLI tools, or libraries. Covers architecture, concurrency, testing, database patterns, gRPC, REST APIs, error handling, and Go best practices.
AI/Fintech and ERP content creation specialist for the Middle East and GCC region. Use when creating blog posts, landing pages, case studies, whitepapers, email campaigns, social media content, or marketing copy for Enterprise Financial Planning (EFP), ERP, AI-powered financial solutions, e-invoicing, or fintech products targeting GCC markets (Saudi Arabia, UAE, Qatar, Kuwait, Bahrain, Oman). Covers content strategy, localized messaging, regulatory context, and industry-specific terminology.
Brand identity and design system expert. Use when creating or enforcing brand consistency across UI, content, marketing materials, or code. Covers logo usage, typography, color systems, voice and tone, component design tokens, and brand governance. Activate when building new pages, writing copy, or reviewing designs for brand compliance.
ArgoCD and Helm expert skill. Use when deploying applications with ArgoCD, creating or reviewing Helm charts, designing GitOps workflows, managing ApplicationSets, multi-cluster deployments, progressive delivery with Argo Rollouts, troubleshooting sync issues, secrets management (SOPS, External Secrets Operator), and Kubernetes manifest management. Covers ArgoCD 3.x and Helm 3.x best practices.
Google Cloud Platform expert skill. Use when designing, deploying, or managing infrastructure on GCP including GKE, Cloud Run, Cloud SQL, Pub/Sub, BigQuery, Cloud Storage, IAM, networking, Terraform, and CI/CD pipelines. Covers architecture, cost optimization, security, and reliability.
Claude Skills — questions
Answers built from the skills we actually parsed.