- 📄 SKILL.md
oxygen-component
Generate Oxygen UI React components following best practices. Use when creating new components, data tables, cards, or UI elements with the Oxygen UI library.
Generate Oxygen UI React components following best practices. Use when creating new components, data tables, cards, or UI elements with the Oxygen UI library.
Use when user requests diagrams, flowcharts, architecture charts, or visualizations. Also use proactively when explaining systems with 3+ components, complex data flows, or relationships that benefit from visual representation. Generates .drawio XML files and exports to PNG/SVG/PDF locally using the native draw.io desktop CLI.
Systematic workflow for clustering biological samples, features, or any quantitative data matrix. Implements multiple clustering algorithms with rigorous validation, comparison, and interpretation to identify meaningful data groupings.
Use this skill when working with Salesforce Agent Script — the scripting language for authoring Agentforce agents using the Atlas Reasoning Engine. Triggers include: creating, modifying, or comprehending Agent Script agents; working with AiAuthoringBundle files or .agent files; designing topic graphs or flow control; producing or updating an Agent Spec; validating Agent Script or diagnosing compilation errors; previewing agents or debugging behavioral issues; deploying, publishing, activating, or deactivating agents; deleting or renaming agents; authoring AiEvaluationDefinition test specs or running agent tests. This skill teaches Agent Script from scratch — AI models have zero prior training data on this language. Do NOT use for Apex development, Flow building, Prompt Template authoring, Experience Cloud configuration, or general Salesforce CLI tasks unrelated to Agent Script.
Manage AWS resources via the aws CLI.
Compare evaluated runs in a retort experiment along factor dimensions. Surfaces effects of each factor, aggregates across replicates, and highlights cells that diverge qualitatively — complementing (not replacing) retort's ANOVA analysis.
Incorporate code review feedback — make code changes, commit with review trailers, update disposition table, and request re-review if needed. Mirrors plan-incorporate for code reviews.
Skill bundle for long-running Clawcolony agents. Use when joining the colony, deciding what to work on, reading mail, routing to domain skills, or starting a new session. NOT for one-shot tasks outside Clawcolony.
Post a coordination message from this bot to the shared bot2bot channel, @-mentioning the other Sutando node.
Evaluate and score agent behavior against a golden reference. Use this skill whenever the user wants to run evaluation, check pass/fail status, understand metric scores, compare sessions for regressions, validate agent behavior, or score a trace from a file or a live session. Trigger on phrases like "eval this trace", "check my agent output", "did my agent do the right thing", "compare runs", "did my agent regress", "score session X", "evaluate against golden", "run evals". Works with both local trace files and live streaming sessions. --- Evaluate agent behavior and explain what the scores mean. ## Determine the input type First, figure out what to evaluate: - **Trace file(s)** — user mentions a `.json` or `.jsonl` file path → use `evaluate_traces` - **Sessions vs golden** — user has multiple live sessions and wants regression testing → use `evaluate_sessions` - **Single live session** — user wants to score one session against a golden eval set → guide them to use `evaluate_sessions` with one session as golden ## Evaluating trace files 1. Get the file path(s). Check the extension: `.jsonl` → `trace_format: "otlp-json"` | `.json` → `"jaeger-json"` (default) 2. Ask if they have a golden eval set JSON. For `tool_trajectory_avg_score` (the default metric), an eval set is required — it provides the expected tool call sequence to compare against. If they don't have one yet, explain this and suggest starting with `hallucinations_v1`, or ask if they want to create a golden set from a reference run first. 3. Call `evaluate_traces` with the file(s), format, and eval set. 4. Present results as a score table (see Score interpretation below) and explain failures. ## Evaluating sessions (regression testing) This workflow requires the server to be running with the `--dev` flag (which enables WebSocket and session streaming). Plain `agentevals serve` will not have sessions. If you get a connection error from any tool below, tell the user: ```bash uv run agentevals serve --dev ```
A deterministic thinking partner that challenges assumptions and applies mental models to sharpen decisions, solve problems, and think more clearly. Use this skill whenever a user says "help me think through X", "challenge my thinking", "what am I missing", "apply mental models to this", "play devil's advocate", "stress test this idea", "poke holes in my plan", "help me decide between X and Y", "what are the second-order effects", "I'm stuck on a decision", names any specific model (SWOT, first principles, inversion, pre-mortem, etc.), or asks for structured reasoning on any ambiguous, high-stakes, or complex problem. Also trigger when the user seems uncertain, is rationalizing, or is asking "am I thinking about this right?" Even casual phrases like "what do you think about..." on non-trivial topics should trigger this skill. --- # Thinking Partner A deterministic thinking partner that challenges assumptions and applies mental models to help users think better and clearer. Not a lecture — a sparring session. ## Core Philosophy Good thinking is an active achievement, not a default state. The goal is not to tell the user what to think, but to sharpen *how* they think by: 1. **Challenging assumptions** — Surface hidden beliefs the user is treating as facts 2. **Applying mental models** — Select and deploy the right thinking frameworks for the situation 3. **Detecting orientation capture** — Notice when thinking serves comfort instead of truth 4. **Maintaining productive tension** — Hold complexity open long enough to find real insight You are not a yes-machine. You are not an interrogator. You are a thinking partner: respectful, direct, genuinely curious, and willing to push back. ## When This Triggers - "Help me think through X" - "Challenge my thinking / assumptions" - "What am I missing?" - "Apply [any model name] to this" - "Play devil's advocate" - "Stress test this idea / plan" - "Help me decide between X and Y" - "What are the second-order effects?" - "Am I thin
Routing guide -- when to use `nansen agent` (AI research) vs direct CLI data commands. Use when deciding how to answer a user's research question with Nansen tools.
skill-sample/ ├─ SKILL.md ⭐ Required: skill entry doc (purpose / usage / examples / deps) ├─ manifest.sample.json ⭐ Recommended: machine-readable metadata (index / validation / autofill) ├─ LICENSE.sample ⭐ Recommended: license & scope (open source / restriction / commercial) ├─ scripts/ │ └─ example-run.py ✅ Runnable example script for quick verification ├─ assets/ │ ├─ example-formatting-guide.md 🧩 Output conventions: layout / structure / style │ └─ example-template.tex 🧩 Templates: quickly generate standardized output └─ references/ 🧩 Knowledge base: methods / guides / best practices ├─ example-ref-structure.md 🧩 Structure reference ├─ example-ref-analysis.md 🧩 Analysis reference └─ example-ref-visuals.md 🧩 Visual reference
More Agent Skills specs Anthropic docs: https://agentskills.io/home
├─ ⭐ Required: YAML Frontmatter (must be at top) │ ├─ ⭐ name : unique skill name, follow naming convention │ └─ ⭐ description : include trigger keywords for matching │ ├─ ✅ Optional: Frontmatter extension fields │ ├─ ✅ license : license identifier │ ├─ ✅ compatibility : runtime constraints when needed │ ├─ ✅ metadata : key-value fields (author/version/source_url...) │ └─ 🧩 allowed-tools : tool whitelist (experimental) │ └─ ✅ Recommended: Markdown body (progressive disclosure) ├─ ✅ Overview / Purpose ├─ ✅ When to use ├─ ✅ Step-by-step ├─ ✅ Inputs / Outputs ├─ ✅ Examples ├─ 🧩 Files & References ├─ 🧩 Edge cases ├─ 🧩 Troubleshooting └─ 🧩 Safety notes
Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.
We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.
Quick Start:
Import/download skills (.zip/.skill), then place locally:
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One SKILL.md can be reused across tools.
Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.
A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.
Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.
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One SKILL.md can usually be reused across tools.
Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.
Example: retrieval + writing + automation scripts as one workflow.
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