wehub-resource-sync
218 lines
15 KiB
Plaintext
218 lines
15 KiB
Plaintext
# Claude Code Skills & Agent Plugins — Full Repository Description
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> A comprehensive, self-contained description of the `alirezarezvani/claude-skills` repository, written for AI agents and LLM crawlers. This file follows the [llms.txt](https://llmstxt.org) convention (`llms-full.txt` variant: the expanded, single-file version). For the concise index, see [llms.txt](https://alirezarezvani.github.io/claude-skills/llms.txt).
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- **Project:** Claude Code Skills & Agent Plugins
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- **Repository:** https://github.com/alirezarezvani/claude-skills
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- **Documentation site:** https://alirezarezvani.github.io/claude-skills/
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- **Author:** Alireza Rezvani
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- **License:** MIT (free to extract, deploy, adapt, and redistribute)
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- **Distribution:** Claude Code plugin marketplace (`.claude-plugin/marketplace.json`) and the ClawHub registry (clawhub.com)
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---
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## What this repository is
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This is a **library of skill packages** for Claude AI and Claude Code — reusable, production-ready modules that bundle domain expertise, best practices, deterministic analysis tools, and strategic frameworks. It is **not a traditional application**. It is a catalog of self-contained skill folders meant to be extracted and deployed by users into their own AI-agent workflows.
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Teams download a skill folder and use it immediately: the skill's `SKILL.md` teaches the agent the workflow, the `scripts/` provide deterministic Python CLI tools, the `references/` supply expert knowledge bases, and the `assets/` give ready-to-customize templates.
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### Headline scale (derived from the tree by `scripts/derive_counters.py`)
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| Metric | Count |
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|--------|-------|
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| Production-ready skills | 354 |
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| Marketplace plugins | 82 |
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| Top-level domains | 18 |
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| Python automation tools | 593 |
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| Reference guides | 722 |
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| Agents (cs-* + personas) | 96 |
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| Slash commands | 102 |
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Counters are generated from the actual file tree; run `python3 scripts/derive_counters.py --check` to verify the docs still match the tree.
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---
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## Cross-tool compatibility
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Skills are authored once and made portable across many AI coding agents via sync scripts in `scripts/`. Supported targets include:
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- **Claude Code** (primary) — plugins, agents, slash commands, MCP servers, hooks
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- **OpenAI Codex** — `scripts/sync-codex-skills.py`, `~/.codex/`
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- **Gemini CLI** — `scripts/sync-gemini-skills.py`
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- **Cursor** — rules-format export
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- **Hermes Agent** — `scripts/sync-hermes-skills.py`
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- **Mistral Vibe** — `scripts/sync-vibe-skills.py`, `~/.vibe/skills/`
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- **Codebuff** — `scripts/sync-codebuff-skills.py`
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- **OpenClaw**, **Aider**, **Windsurf**, **Kilo Code**, **OpenCode**, **Augment**, **Antigravity** — documented in the Multi-Tool Integrations guide.
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---
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## Design principles
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1. **Skills are products.** Each skill is deployable as a standalone package with no dependency on other skills.
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2. **Documentation-driven.** Success depends on clear, actionable `SKILL.md` docs.
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3. **Algorithm over AI.** Analysis tools use deterministic Python (standard library only) — **no LLM/ML calls inside scripts**. This keeps skills portable, fast, and reproducible.
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4. **Template-heavy.** Skills ship ready-to-use templates users customize.
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5. **Platform-specific.** Specific, actionable frameworks beat generic advice.
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### Anti-patterns the repo deliberately avoids
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- Dependencies between skills (each stays self-contained)
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- Complex build systems or test frameworks (portability first)
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- Generic advice instead of specific frameworks
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- LLM calls in scripts (defeats portability and speed)
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---
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## Skill package pattern
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Every skill follows this structure:
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```
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skill-name/
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├── SKILL.md # Master documentation: the workflow the agent follows
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├── scripts/ # Python CLI tools (stdlib-only, no LLM calls; support --help and JSON output)
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├── references/ # Expert knowledge bases (markdown), each citing 5-8 authoritative sources
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└── assets/ # User-facing templates
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```
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Knowledge flows: `references/` → informs `SKILL.md` workflows → executed via `scripts/` → applied using `assets/` templates.
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Each `SKILL.md` carries YAML frontmatter with a `name` and a `description` whose trigger phrasing (e.g. "Use when…") tells the agent when to invoke the skill.
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---
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## Repository structure
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```
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claude-skills/
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├── .claude-plugin/ # Plugin registry (marketplace.json — 82 plugins)
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├── agents/ # cs-* agents + 7 personas
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├── commands/ # Slash commands
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├── engineering-team/ # Core engineering skills
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├── engineering/ # POWERFUL-tier advanced engineering skills
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├── product-team/ # Product skills
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├── marketing-skill/ # Marketing skills (8 pods incl. AEO)
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├── marketing/ # Landing-page generator skill
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├── c-level-advisor/ # C-level advisory skills (full C-suite + founder-mode)
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├── project-management/ # PM skills + bundled Atlassian Remote MCP
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├── ra-qm-team/ # Regulatory / quality-management compliance skills
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├── compliance-os/ # Compliance audit-prep orchestrator + sub-skills
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├── business-growth/ # Customer success, sales eng, revops
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├── business-operations/ # Internal-ops skills (orchestrator + sub-skills)
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├── commercial/ # Per-deal-economics skills (orchestrator + sub-skills)
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├── finance/ # Finance skills
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├── research/ # Academic research skills (orchestrator + specialists)
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├── research-ops/ # Enterprise research operations (orchestrator + sub-skills)
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├── productivity/ # Capture, email, reflect, handoff, andreessen
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├── markdown-html/ # Markdown-to-interactive-HTML converter suite
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├── standards/ # Communication, quality, git, security standards
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├── templates/ # Reusable templates
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├── docs/ # This MkDocs Material documentation site
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└── scripts/ # Build, sync, and validation scripts
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```
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---
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## The 18 domains in detail
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### Engineering — Core (`engineering-team/`)
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Fullstack, AI/ML, DevOps, security, data, and QA skills. Includes senior-role skills (architect, backend, frontend, fullstack, DevOps, data engineer/scientist, ML, computer vision, prompt, QA, security, SecOps), cloud architects (AWS/Azure/GCP), a full security suite (adversarial reviewer, AI security, cloud security, incident response, red team, threat detection, pen testing), Playwright Pro (10 sub-skills), a Self-Improving Agent suite, Snowflake development, and Stripe integration.
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### Engineering — POWERFUL (`engineering/`)
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Advanced, higher-leverage engineering skills: agent design, RAG architecture, MCP server building, CI/CD pipelines, database/schema design, observability, SLO architecture, chaos engineering, Kubernetes operators, feature-flags, migration architecture, performance profiling, dependency auditing, and meta-skills for **authoring skills** (`write-a-skill`), token compression (`caveman`), plan interrogation (`grill-me`), and conversation continuity (`handoff`). Also hosts AgentHub, the autoresearch-agent (Karpathy file-optimization loop), the LLM Wiki, ship-gate, and a PreToolUse security-guidance hook.
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### Product (`product-team/`)
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RICE prioritization, OKRs, user stories, UX research and design, product discovery/strategy, competitive teardowns, experiment design, product analytics, SaaS scaffolding, code-to-PRD, spec-to-repo, and an Apple HIG expert.
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### Marketing (`marketing-skill/`)
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Eight pods spanning content creation, copywriting/editing, SEO, **AEO (Answer Engine Optimization)**, ASO (app-store optimization), demand generation, paid ads, CRO (conversion-rate optimization across page/form/signup/paywall/popup/onboarding), social media, email sequences, pricing strategy, launch strategy, schema markup, and campaign analytics.
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### Marketing — Landing Pages (`marketing/`)
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A single-file HTML landing-page generator with multiple design styles, brand-palette validation, and GSAP animation patterns.
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### Project Management (`project-management/`)
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Jira and Confluence experts, Atlassian admin/templates, scrum master, senior PM, meeting analyzer, and team communications. Ships a bundled Atlassian Remote MCP (`.mcp.json`, SSE transport, OAuth handled by Claude Code).
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### C-Level Advisory (`c-level-advisor/`)
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A full C-suite of opinionated advisor skills (CEO, CFO, CMO, CPO, CRO, COO, CTO, CHRO, CISO, CDO, CAIO, CCO, VP Engineering, General Counsel) plus a **Founder-Mode** operating system: `/cs:office-hours`, `/cs:brief` → `/cs:boardroom` → `/cs:decide` → `/cs:execute` → `/cs:post-mortem`, plus onboarding, cross-eval, and decision-freeze commands. Includes an Executive Mentor suite and strategic frameworks (RICE, JTBD, OKR, ADKAR, Wardley mapping). Memory is Markdown-only (no database dependency).
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### Regulatory & Quality (`ra-qm-team/`)
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ISO 13485, EU MDR 2017/745, FDA, GDPR/DSGVO, ISO 27001, SOC 2, CAPA, risk management, and QMS/ISMS audit skills for regulated industries (notably medical devices).
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### Compliance OS (`compliance-os/`)
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An orchestrator plus audit-prep sub-skills for SOC 2, ISO 13485, ISO 27001, GDPR, FDA QSR, EU AI Act readiness, and ISO 42001 (AIMS).
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### Business & Growth (`business-growth/`)
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Customer success management, sales engineering, revenue operations, and contract/proposal writing.
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### Business Operations (`business-operations/`)
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Internal-ops skills for BizOps leads and COO direct reports: process mapping (BPMN + bottleneck + cycle-time), vendor management (scorecard + SLA + third-party risk), capacity planning (Erlang-C), internal comms (ADKAR + Kotter), knowledge ops (SOP/runbook hygiene), and procurement optimization. Orchestrator uses `context: fork` chaining. Every output is a recommendation routed to a named human — never an auto-decision.
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### Commercial (`commercial/`)
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Per-deal-and-packaging skills: pricing strategist (model picker + Van Westendorp PSM + packaging), deal desk (scorer + approval router + redliner), partnerships architect, channel economics, commercial policy, RFP responder (Shipley method), and commercial forecaster. Pricing outputs a model and a range (never a single number); deal outputs route to a named approver (never auto-approve).
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### Finance (`finance/`)
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Financial analysis, DCF valuation, budgeting/forecasting, business investment advisory, and SaaS-metrics coaching.
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### Research (`research/`)
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Academic/literature research: an orchestrator (hybrid router) plus specialists for recency+sentiment pulse, literature review, NIH grants, entity dossiers, patent/prior-art landscapes, course-reading syllabi, and NotebookLM browser automation.
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### Research Operations (`research-ops/`)
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The enterprise counterpart to `research/`: clinical study design (sample size, endpoints, phase-gate — estimates confirmed by a named clinical owner), R&D program finance (budget, burn/runway, CapEx-vs-OpEx routing), market research (TAM/SAM/SOM with method + assumptions, never a single number), and product research (study design, saturation planning, insight synthesis requiring recurrence across independent participants).
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### Productivity (`productivity/`)
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Capture (brain-dump-to-action), email (inbox setup + triage, drafts-only), reflect (light-prompt journaling), handoff (conversation continuity with redaction linting and session hooks), and andreessen (market-first decision engine).
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### Markdown to HTML (`markdown-html/`)
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A converter suite operationalizing Thariq Shihipar's thesis that markdown collapses past ~100 lines and HTML restores density/clarity/shareability. Ships an orchestrator (doctype router), a design-system onboarding wizard (WCAG-AA-validated brand palette), and three converters: `md-document` (long-form → single-file HTML with TOC/search/code-copy/scrollspy), `md-review` (code-review markdown → 2-column diff + severity annotations), and `md-slides` (markdown deck → single-file HTML presentation with keyboard nav, presenter mode, and print-to-PDF). Output is single-file HTML (Google Fonts + Prism.js CDN the only permitted externals).
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---
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## Agents and slash commands
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- **Agents (`agents/`):** 96 total, mostly `cs-*` prefixed personas (e.g. `cs-ceo-advisor`, `cs-senior-engineer`, `cs-aeo`, domain orchestrators) plus 7 general personas. Agents orchestrate skills and carry a distinct operating voice.
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- **Slash commands (`commands/`):** 102 total, including `/prd`, `/rice`, `/okr`, `/tdd`, `/changelog`, `/slo-design`, `/chaos-experiment`, `/plugin-audit`, `/seo-auditor`, and the `/cs:*` family (office-hours, boardroom, bizops, commercial, research-ops, markdown-html routers, and per-skill commands).
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---
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## Plugin distribution
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Plugins are registered in `.claude-plugin/marketplace.json` (82 plugins) across these categories: development (34), leadership (9), research (9), productivity (6), marketing (5), compliance (4), product (4), finance (2), and one each of project-management, business-growth, design, knowledge, operations, commercial, research-ops, documentation, and engineering.
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### plugin.json rules (for anyone extending the library)
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- Required fields: `name`, `description`, `version`, `author`, `homepage`, `repository`, `license`, `skills`.
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- Two approved extension fields: `source` (provenance for megaprompt-derived skills) and `attribution` (credit for MIT-licensed external derivations).
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- Skill paths are relative to the plugin root and start with `./`. Canonical forms: single-skill = `["./"]`; `skills/` subdir = `"./skills"`; multi-skill domain = explicit `["./sub1", "./sub2", ...]`.
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- Validation: `scripts/check_plugin_json.py --all` runs in CI on every PR.
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---
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## Git and contribution workflow
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- **Branch strategy:** feature → dev → main. **All PRs target `dev`, never `main`.** `main` receives only periodic `dev → main` promotion PRs from the maintainer.
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- **Conventional commits** are enforced (e.g. `feat(agents): …`, `fix(tool): …`, `docs(workflow): …`).
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- **Branch protection:** `main` requires PR approval; direct pushes are blocked.
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### ClawHub publishing constraints
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- The `cs-` prefix is used only on the ClawHub registry when a slug conflicts with another publisher — repo folder names and local skill names are never renamed.
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- No paid/commercial service dependencies; free-tier APIs and bring-your-own-key patterns are acceptable.
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- Rate limit: 5 new skills per hour.
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- Package versions match the repo release version.
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---
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## How an agent should use this repository
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1. **Find a matching skill** by browsing the [Skills Overview](https://alirezarezvani.github.io/claude-skills/skills/) or a domain index, matching the task to a skill's `description` trigger.
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2. **Read the skill's `SKILL.md`** to learn the workflow.
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3. **Run the skill's Python tools** (`scripts/*.py`, stdlib-only, all support `--help` and most support JSON output) for deterministic analysis.
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4. **Consult `references/`** for the expert knowledge underpinning the workflow.
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5. **Apply the `assets/` templates** to produce the deliverable.
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To install as a plugin, add the marketplace and install the relevant plugin via Claude Code; see [Getting Started](https://alirezarezvani.github.io/claude-skills/getting-started/) and [Multi-Tool Integrations](https://alirezarezvani.github.io/claude-skills/integrations/) for non-Claude tools.
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---
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*Generated to make the repository accessible to AI agents. Counters reflect `scripts/derive_counters.py` at the time of writing; the repository evolves — the GitHub repository and documentation site are the authoritative sources.*
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