Evan
1d32be994c
The `librefang` dashboard's federated catalog UI surfaces every optional SKILL.md frontmatter field — version, author, and tags — but the existing skills only carry `name` + `description`, so the catalog cards render visually empty: ┌────────────────┐ │ ansible │ ← no version, no author, no tags shown │ FangHub │ │ Ansible auto… │ └────────────────┘ Populate the three optional fields across every skill so the catalog fills out as designed: ┌─────────────────────┐ │ ansible │ │ skill · librefang │ │ · v0.1.0 │ │ Ansible auto… │ │ [devops][automation]│ │ [infra] │ └─────────────────────┘ Choices - author = `librefang`. Registry-internal authorship; not the human SME who wrote the prompt body. Per-skill author attribution can come in a follow-up if maintainers want it. - version = `0.1.0` baseline. Future content updates bump per-skill. - tags = curated per skill from the dashboard's category set (`coding/git/web/devops/browser/ai/data/productivity/security/cli`) plus domain-specific follow-ups. First tag is the primary category. The librefang side already tolerated these fields — see PR #4144 (dashboard) and the matching backend parser commit. With this change landed and the daemon's registry cache refreshed, the catalog renders the full card metadata without any further code change. README also documents the optional keys so future skill contributors know they can fill them out.
213 lines
10 KiB
Markdown
213 lines
10 KiB
Markdown
# Skills Registry
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Skills are reusable expertise modules that can be attached to any agent. Each skill carries a system prompt that injects domain knowledge, best practices, and behavioral guidelines into an agent's context at conversation time. Skills are composable — a single agent can load multiple skills simultaneously.
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## File Format
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A skill lives in its own subdirectory. The only required file is `SKILL.md`. An optional `skill.toml` provides structured metadata when `[runtime]`, `[input]` schema, or explicit versioning is needed.
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```
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skills/
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├── rust-expert/
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│ └── SKILL.md # required: frontmatter + prompt body
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├── meeting-agenda/
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│ ├── SKILL.md # required: frontmatter + prompt body
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│ └── skill.toml # optional: runtime type, input schema, version
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└── code-runner/
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├── SKILL.md # overview (prompt body unused for script skills)
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├── skill.toml # runtime = python, entry = main.py
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└── main.py
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```
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### SKILL.md format
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```markdown
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---
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name: rust-expert
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description: "Rust programming expert for ownership, lifetimes, async/await, traits, and unsafe code"
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version: 0.1.0
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author: librefang
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tags: [coding, language]
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---
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# Rust Programming Expertise
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You are an expert Rust developer with deep understanding of the ownership system...
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```
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The frontmatter must contain `name` and `description`. The other keys are
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optional and the registry parser tolerates their absence:
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- `version` (default `null`) — semver string. Bump per content update.
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- `author` (default `null`) — owner of the prompt body. Use `librefang`
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for first-party skills under this registry.
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- `tags` (default `[]`) — inline YAML list. The dashboard's catalog
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surfaces these as filter chips and as visible tags on each skill
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card. Standard buckets: `coding`, `git`, `web`, `devops`, `browser`,
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`ai`, `data`, `productivity`, `security`, `cli`. Add domain-specific
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follow-ups freely (e.g. `[devops, kubernetes, k8s]`).
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The Markdown body after the closing `---` becomes the injected prompt.
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### skill.toml format (optional)
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Only required when you need `[runtime]`, `[input]` schema, or structured metadata beyond what frontmatter supports:
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```toml
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[skill]
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name = "meeting-agenda"
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version = "0.1.0"
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description = "Generate a structured meeting agenda from a topic and duration."
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tags = ["meeting", "productivity"]
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[runtime]
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type = "promptonly" # promptonly | python | node | shell
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[input]
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topic = { type = "string", description = "The meeting topic", required = true }
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duration_minutes = { type = "string", description = "Duration in minutes", required = true }
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```
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If both files exist, `skill.name` and `skill.description` in `skill.toml` must match the frontmatter in `SKILL.md`. The validator enforces this to prevent drift.
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## Installing and Using Skills
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```bash
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# List all available skills in the registry
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librefang catalog skills
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# Attach a skill to an agent
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librefang skill attach <agent-name> rust-expert
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# Attach multiple skills
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librefang skill attach <agent-name> rust-expert security-audit
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# Detach a skill
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librefang skill detach <agent-name> rust-expert
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# Test a skill locally with sample input
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librefang skill test ./skills/meeting-agenda \
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--input '{"topic": "Q1 planning", "duration_minutes": "30"}'
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```
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## All Skills (61 total)
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### Programming Languages
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| Name | Description |
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|------|-------------|
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| css-expert | CSS expert for flexbox, grid, animations, responsive design, and modern layout techniques |
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| golang-expert | Go programming expert for goroutines, channels, interfaces, modules, and concurrency patterns |
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| python-expert | Python expert for stdlib, packaging, type hints, async/await, and performance optimization |
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| rust-expert | Rust programming expert for ownership, lifetimes, async/await, traits, and unsafe code |
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| typescript-expert | TypeScript expert for type system, generics, utility types, and strict mode patterns |
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| wasm-expert | WebAssembly expert for WASI, component model, Rust/C compilation, and browser integration |
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### Web Frameworks and APIs
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| Name | Description |
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|------|-------------|
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| graphql-expert | GraphQL expert for schema design, resolvers, subscriptions, and performance optimization |
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| nextjs-expert | Next.js expert for App Router, SSR/SSG, API routes, middleware, and deployment |
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| oauth-expert | OAuth 2.0 and OpenID Connect expert for authorization flows, PKCE, and token management |
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| openapi-expert | OpenAPI/Swagger expert for API specification design, validation, and code generation |
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| react-expert | React expert for hooks, state management, Server Components, and performance optimization |
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### Databases
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| Name | Description |
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|------|-------------|
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| elasticsearch | Elasticsearch expert for queries, mappings, aggregations, index management, and cluster operations |
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| mongodb | MongoDB operations expert for queries, aggregation pipelines, indexes, and schema design |
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| postgres-expert | PostgreSQL expert for query optimization, indexing, extensions, and database administration |
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| redis-expert | Redis expert for data structures, caching patterns, Lua scripting, and cluster operations |
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| sql-analyst | SQL query expert for optimization, schema design, and data analysis |
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| sqlite-expert | SQLite expert for WAL mode, query optimization, embedded patterns, and advanced features |
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| vector-db | Vector database expert for embeddings, similarity search, RAG patterns, and indexing strategies |
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### Cloud and Infrastructure
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| Name | Description |
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|------|-------------|
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| ansible | Ansible automation expert for playbooks, roles, inventories, and infrastructure management |
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| aws | AWS cloud services expert for EC2, S3, Lambda, IAM, and AWS CLI |
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| azure | Microsoft Azure expert for az CLI, AKS, App Service, and cloud infrastructure |
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| docker | Docker expert for containers, Compose, Dockerfiles, and debugging |
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| gcp | Google Cloud Platform expert for gcloud CLI, GKE, Cloud Run, and managed services |
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| helm | Helm chart expert for Kubernetes package management, templating, and dependency management |
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| kubernetes | Kubernetes operations expert for kubectl, pods, deployments, and debugging |
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| nginx | Nginx configuration expert for reverse proxy, load balancing, TLS, and performance tuning |
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| terraform | Terraform IaC expert for providers, modules, state management, and planning |
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### DevOps and CI/CD
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| Name | Description |
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|------|-------------|
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| ci-cd | CI/CD pipeline expert for GitHub Actions, GitLab CI, Jenkins, and deployment automation |
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| git-expert | Git operations expert for branching, rebasing, conflicts, and workflows |
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| github | GitHub operations expert for PRs, issues, code review, Actions, and gh CLI |
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| linux-networking | Linux networking expert for iptables, nftables, routing, DNS, and network troubleshooting |
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| prometheus | Prometheus monitoring expert for PromQL, alerting rules, Grafana dashboards, and observability |
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| sentry | Sentry error tracking and debugging specialist |
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| shell-scripting | Shell scripting expert for Bash, POSIX compliance, error handling, and automation |
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| sysadmin | System administration expert for Linux, macOS, Windows, services, and monitoring |
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### Security
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| Name | Description |
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|------|-------------|
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| compliance | Compliance expert for SOC 2, GDPR, HIPAA, PCI-DSS, and security frameworks |
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| crypto-expert | Cryptography expert for TLS, symmetric/asymmetric encryption, hashing, and key management |
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| security-audit | Security audit expert for OWASP Top 10, CVE analysis, code review, and penetration testing methodology |
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### AI and Machine Learning
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| Name | Description |
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|------|-------------|
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| llm-finetuning | LLM fine-tuning expert for LoRA, QLoRA, dataset preparation, and training optimization |
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| ml-engineer | Machine learning engineer expert for PyTorch, scikit-learn, model evaluation, and MLOps |
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| prompt-engineer | Prompt engineering expert for chain-of-thought, few-shot learning, evaluation, and LLM optimization |
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| web-search | Web search and research specialist for finding and synthesizing information |
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### Productivity Tools
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| Name | Description |
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|------|-------------|
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| confluence | Confluence wiki expert for page structure, spaces, macros, and content organization |
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| figma-expert | Figma design expert for components, auto-layout, design systems, and developer handoff |
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| jira | Jira project management expert for issues, sprints, workflows, and reporting |
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| linear-tools | Linear project management expert for issues, cycles, projects, and workflow automation |
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| notion | Notion workspace management and content creation specialist |
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| pdf-reader | PDF content extraction and analysis specialist |
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| slack-tools | Slack workspace management and automation specialist |
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### Writing and Communication
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| Name | Description |
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|------|-------------|
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| email-writer | Professional email writing expert for tone, structure, clarity, and business communication |
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| presentation | Presentation expert for slide structure, storytelling, visual design, and audience engagement |
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| technical-writer | Technical writing expert for API docs, READMEs, ADRs, and developer documentation |
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| writing-coach | Writing improvement specialist for grammar, style, clarity, and structure |
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### Engineering Practice
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| Name | Description |
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|------|-------------|
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| api-tester | API testing expert for curl, REST, GraphQL, authentication, and debugging |
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| code-reviewer | Code review specialist focused on patterns, bugs, security, and performance |
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| data-analyst | Data analysis expert for statistics, visualization, pandas, and exploration |
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| data-pipeline | Data pipeline expert for ETL, Apache Spark, Airflow, dbt, and data quality |
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| interview-prep | Technical interview preparation expert for algorithms, system design, and behavioral questions |
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| project-manager | Project management expert for Agile, estimation, risk management, and stakeholder communication |
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| regex-expert | Regular expression expert for crafting, debugging, and explaining patterns |
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## Adding a New Skill
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1. Create `skills/<name>/SKILL.md` with frontmatter (`name`, `description`, plus optional `version`, `author`, `tags`) and the prompt body.
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2. If you need `[runtime]`, `[input]`, or structured metadata, add `skills/<name>/skill.toml`.
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3. Add implementation files (`main.py`, etc.) when `runtime` is not `promptonly`.
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4. Run `python scripts/validate.py`.
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5. Submit a PR.
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See [CONTRIBUTING.md](../CONTRIBUTING.md) for the full guide.
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