Ollama
AICommonly used with
Skills using Ollama (418)
flow-deliver
Multi-AI validation, scoring, and review using available external providers (Double Diamond Deliver phase)
flow-parallel
Decompose and execute large changes, migrations, or multi-issue fixes in parallel with quality gates
flow-spec
NLSpec authoring — use when you need a structured specification from multi-AI research and consensus
octopus-architecture
System architecture and API design with multi-AI consensus — use for design reviews and new subsystems
octopus-quick
Quick execution for ad-hoc tasks without full workflow overhead — use for small, self-contained requests
octopus-research
Thorough research across multiple sources — use for complex topics needing broad synthesis
octopus-security-audit
OWASP compliance, vulnerability scanning, and adversarial red team testing — use for security reviews
octopus-ui-ux-design
Design UI/UX systems with style guides, palettes, typography, and component specs for new interfaces
skill-audit
Audit codebases for quality, consistency, and broken patterns — use for pre-release or tech debt review
skill-claw
OpenClaw instance administration — manage hosts across macOS, Ubuntu/Debian, Docker, OCI, and Proxmox
skill-code-review
Expert multi-AI code review with inline PR comments — use for thorough quality and security analysis
skill-content-pipeline
Extract patterns and anatomy from URLs — use to reverse-engineer content strategies from live pages
skill-copilot-provider
GitHub Copilot CLI as optional zero-cost provider via copilot -p programmatic mode
skill-cost-projections
Project remaining workflow cost from per-phase averages — warns on budget ceiling overruns
skill-coverage-audit
Trace codepaths in diffs, map against tests, auto-generate missing coverage — use before shipping PRs
skill-debate
Structured multi-provider AI debates between Claude and available advisors — use for critical decisions
skill-debug
Debug issues methodically — use when stuck on errors, test failures, or unexpected behavior
skill-design-lineage
Persist design documents with branch tracking, revision chains, and cross-session discovery
skill-doc-delivery
Convert markdown to DOCX, PPTX, XLSX, PDF office documents — use when you need exportable deliverables
skill-doc-sync
Post-ship doc sync across project markdown. Use when: sync docs, update docs, document changes, release notes.
skill-factory
Run a full build-and-ship pipeline from a spec — use for hands-off project generation
skill-finish-branch
Wrap up a branch — run tests, create PR, merge or discard — use when implementation is done
skill-issues
Track project blockers, bugs, and gaps across sessions — use when issues pile up or need triage
skill-parallel-agents
Decompose large tasks across parallel agents — use for migrations, multi-file refactors, or batch work
skill-resume
Pick up where you left off from a previous session — use after context resets, compaction, or new conversations
skill-rollback
Roll back to a previous checkpoint via git — use when a change went wrong and you need to revert
skill-security-framing
URL validation and content sanitization for untrusted sources — use when handling external input safely
skill-ship
Package and finalize completed work for delivery — use when a feature is done and ready to ship
skill-staged-review
Use when a PR or feature needs both specification and code-quality review
skill-status
Show where you are in the workflow and what to do next — use for progress checks and orientation
skill-tdd
Build features with tests-before-code rigor — use for new features needing test coverage
skill-verification-gate
Use when about to declare work complete, fixed, passing, or done
skill-context-detection
Auto-detect work context (Dev vs Knowledge) — use to tailor workflows based on current task type
skill-decision-support
Present options with trade-offs for informed decision-making — use when choosing between approaches
skill-deck
Generate slide deck presentations from briefs — use when you need slides, pitch decks, or visual summaries
skill-doctor
Environment diagnostics — check providers, auth, config, hooks, scheduler, and more
skill-iterative-loop
Run tasks in a loop until goals are met — use for iterative refinement, polling, or convergence
skill-knowledge-work
Switch to Knowledge Work mode for research and writing — use when task is non-code focused
skill-meta-prompt
Craft better prompts using proven optimization techniques — use when your prompt needs refinement
skill-prd
Write an AI-optimized PRD using multi-AI orchestration — use when scoping a new feature or product
skill-review-response
Use when a reviewer, CI bot, or another AI leaves feedback to address
skill-thought-partner
Brainstorm creatively with pattern spotting and paradox hunting — use for ideation and exploration
skill-visual-feedback
Process screenshot-based UI/UX feedback to fix visual issues — use when users share screenshots of bugs
perfup
Autonomous performance optimization: research, PoC, benchmark, implement, review, PR
microsoft-extensions-ai
Build provider-agnostic .NET AI integrations with `Microsoft.Extensions.AI`, `IChatClient`, embeddings, middleware, structured output, vector search, and evaluation. USE FOR: building or reviewing .NET code that uses Microsoft.Extensions.AI, Microsoft.Extensions.AI.Abstractions, IChatClient, IEmbeddingGenerator, ChatOptions, or AIFunction;. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
openhands
Delegate coding to OpenHands CLI (model-agnostic, LiteLLM).
pinggy-tunnel
Zero-install localhost tunnels over SSH via Pinggy.
ollama
Deploy and serve local models with Ollama — pull and run them, then expose the OpenAI-compatible endpoint to apps and agents.
vllm
Deploy and serve LLMs with vLLM behind an OpenAI-compatible endpoint, with tool calling enabled for agent workloads.
add-ollama-provider
Route a NanoClaw agent group to a local Ollama model instead of the Anthropic API. Ollama speaks the Anthropic API natively (v1/messages), so no provider code changes are needed — just env var overrides and a model setting. Use when the user wants to run their agent locally, cut API costs, or experiment with open-weight models. See docs/ollama.md for background.
add-ollama-tool
Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.
customize
Add new capabilities or modify NanoClaw behavior. Use when user wants to add channels (Telegram, Slack, email input), change triggers, add integrations, modify the router, or make any other customizations. This is an interactive skill that asks questions to understand what the user wants.
skill-extract
Reverse-engineer design systems, tokens, and components from live products or screenshots
skill-intent-contract
Use when starting a complex or ambiguous task that risks scope drift
llm-benchmark
Use when the user wants to test, compare, or choose local Ollama models for their machine. Checks Ollama/GPU state, recommends model sizes from available VRAM, preserves existing benchmark records, pulls only approved models, runs repeatable benchmarks, restores stopped services, and writes a markdown comparison report. NOT for hosted API model evaluation or subjective chat-quality judging without local benchmark commands.
skill-native-escalation-routing
Use when choosing native or multi-LLM handling for init, review, or security requests
cherry-assistant-guide
Cherry Studio 产品知识库、源码路径索引、故障排查和页面导航。当用户询问 Cherry Studio 的功能、配置、报错、使用方法时触发。也适用于用户提到 provider、模型、知识库、Agent、MCP、OpenClaw、PDF、快捷短语等关键词的场景。
local-llm-free
Run the ComfyUI agent locally for FREE — no subscription, no API key, fully offline — using our gemma4 models fine-tuned on the comfyui-mcp tool suite via Ollama. Use when the user asks about running locally, running for free, offline use, avoiding API costs, Ollama setup, or which local model to pick.
claude-api
Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST
ide-api-deprecation-tracker
Find all @deprecated APIs in the workspace, count their callers, and extract migration guidance. Produces a prioritized report sorted by call count so you know which deprecations to tackle first.
ide-dead-code-hunter
Find unused exports, dead functions, and unreachable code across the workspace using LSP analysis. Cross-verifies detectUnusedCode with findReferences to eliminate false positives. Use to clean up technical debt or before a major refactor.
ide-debug
Full debug workflow using IDE bridge tools. Runs tests to find failures, sets conditional breakpoints, evaluates expressions in the debugger, identifies root causes, applies fixes, and verifies. Use when debugging test failures or runtime issues.
ide-explore
Deep codebase exploration using IDE bridge LSP tools. Maps architecture, traces call chains, discovers entry points, and builds a mental model of unfamiliar code. Use when onboarding to a new codebase or understanding a module.
ide-monitor
Continuous IDE monitoring using bridge tools. Checks diagnostics, test results, or terminal output. Designed for use with /loop for recurring checks.
ide-quality
Multi-language code quality sweep using IDE bridge tools. Runs diagnostics across all languages, auto-fixes lint errors, organizes imports, formats code, runs tests, and optionally commits the cleanup.
ide-refactor
Safe refactoring with snapshot rollback. Creates a checkpoint, performs the refactoring using LSP rename and code actions, runs tests, and rolls back automatically if anything breaks.
ide-review
Deep PR review using IDE bridge LSP and GitHub tools. Analyzes diffs with code intelligence — follows definitions, checks references, inspects types, runs diagnostics, and posts structured review comments.
ide-type-mismatch-fix
Diagnose and fix TypeScript/language type errors using LSP diagnostics, hover, and code actions. For each type error, fetches the expected vs actual types, surfaces quickfix suggestions, and optionally applies them. Use when getDiagnostics shows type errors you want to resolve quickly.
slm-remember
Capture durable facts, decisions, constraints, and gotchas into SuperLocalMemory. Use when the user says "remember that", "save this decision", "note this constraint", or when a session produces a conclusion worth persisting across sessions. Always recall first to avoid duplicates.
forge
Forge schema-bound, sandboxed tools at runtime. Paired with the cowork `forge` persona for chat-driven use in the voice-skill bridge. Use when you would otherwise write the same Bash snippet ≥3× with different parameters, when you need precise numerical results over a dataset, or when the user wants reproducible/deterministic output written to a file.
game-dev-agent
AI agent that assists with Unity game development — sprite generation, code scaffolding, balance tuning, audio generation, in-game AI Director. Built to demonstrate AI agent engineer + game developer T-shape skill profile.
game-prototype
Unity-based mini colony-sim-style game prototype, built using game-dev-agent. Portfolio piece demonstrating AI agent + game dev T-shape skill.
goal-lock
A discipline helper for autonomous and long sessions — given the active goal in `docs/goal.md`, list the unchecked deliverable subgoals (the actual `- [ ]` items), report how many remain, and let the operator (or an autonomous worker) decide whether the next iteration should keep advancing the goal or whether the goal's `Done when` criteria are already satisfied. Does *not* alter the agent loop or override the harness — this is a transparency / discipline tool, not a runtime hook.
idol-short
아이돌/아티스트 콘텐츠 쇼츠 — produce a 60-second 9:16 vertical short ABOUT a real idol/artist (subject configured in config/subjects/<id>.yaml) through the four-team pipeline 리서치팀 → 제작팀 ⇄ 법률팀 → 출시팀. Use when the operator wants a fan-news/info short about a real artist. Because the subject is REAL PEOPLE + a trademarked group, the legal gate is the load-bearing stage — it enforces the default-safe path (synthetic narration + sourced facts + license-clean generic B-roll + on-screen text, NO member imagery / group audio / agency media) and flags any escalation. Reuses the faceless-short render core.
info-short
정보쇼츠 — produce a 60-second 9:16 vertical INFORMATIONAL/explainer short from a topic, through the four-team pipeline 리서치팀 → 제작팀 ⇄ 법률팀 → 출시팀. Use when the operator gives an evergreen educational topic (a fact, a how/why, a concept) and wants a sourced, license-clean, narrated short ready for manual upload. Reuses the faceless-short render core; adds a research stage (sourced claims) and a legal gate before release.
music-video
Generate a 60-second 9:16 vertical music video (YouTube Shorts / TikTok / Reels format) from an operator-supplied music file plus mood keywords. Use when the user provides an audio file (mp3 / wav / m4a / aac) and wants a short-form vertical video with beat-aligned cuts, mood-matched Pexels B-roll, and optional vintage post-shaders (pond ripple / breathing zoom / halation / combo). Music is the primary audio — no narration, no captions.
news-short
뉴스쇼츠 — produce a 60-second 9:16 vertical NEWS recap short from a current event, through the four-team pipeline 리서치팀 → 제작팀 ⇄ 법률팀 → 출시팀. Use when the operator wants a timely, recency-gated, defamation-screened news short. Like info-short but with a freshness requirement (newest source within N days), multi-source corroboration, an "as of <date>" stamp, and a stricter legal gate (defamation / named-living-person / attribution). Reuses the faceless-short render core.
ide-coverage
Test coverage heatmap from lcov or JSON coverage data. Finds coverage reports, parses line coverage per file, and renders a color-coded file-tree heatmap as HTML. Opens in the system browser.
ide-deps
Dependency graph for a file or symbol. Calls getCallHierarchy and findReferences, builds a directed graph, and renders an interactive HTML force-directed graph. Opens in the system browser.
ide-diagnostics-board
Diagnostic dashboard across the workspace. Calls getDiagnostics, groups results by severity and file, and renders a sortable color-coded HTML table. Opens in the system browser.
cockpit-release
Cut a new Cockpit release end-to-end — bump version, tag, publish to npm, write user-facing release notes, refresh the website, and verify everything went live.
telemetry
Unified pipeline telemetry — collects per-stage performance metrics (CPU, memory, I/O) and diagnostic events into structured reports (JSON, text).
template-academic-paper
Template-native manuscript planning, outline, drafting, revision, formatting, citation check, and AI-use disclosure routing. USE WHEN the user asks to write, outline, revise, format, or prepare a paper inside the Research Project Template.
template-academic-paper-reviewer
Read-only manuscript review, methodology review, re-review, and calibration workflow for template projects. USE WHEN the user asks for peer review, referee-style critique, methods/statistics review, or verification that revisions addressed prior comments.
template-academic-pipeline
Research-to-publication orchestrator for template projects: research, write, verify, review, revise, reproduce, validate, and finalize. USE WHEN the user wants the whole paper workflow or enters midstream with an existing paper or reviewer comments.
template-agentic-use
Agentic-use and skill-routing workflow for the Research Project Template. USE WHEN discovering relevant skills, making template easier for agents to navigate, auditing docs/prompts skill coverage, checking .cursor/skill_manifest.json, evaluating external skills, reviewing external agentic operating models such as Steward OS, AutoResearch CLI, LEANN, or Agent Skills for Context Engineering, or improving agent onboarding/routing without changing project behavior.
template-code-development
Standards-compliant code for the Research Project Template — infrastructure or project src/, thin orchestrators, type hints, no mocks. USE WHEN implementing an algorithm, utility, analysis method, optimizer, new module in projects/*/src or infrastructure/, or user says add code following template architecture — even without docs/prompts. Not for end-to-end feature spanning manuscript + pipeline (use template-feature-addition).
template-comprehensive-assessment
Full checkout audit for the Research Project Template — tests, architecture, docs, manuscript, pipeline. USE WHEN user asks for comprehensive assessment, full repo review, health check across projects, audit everything, or pre-merge sanity sweep for template exemplars — even without naming docs/prompts or a skill. Not for single failing stage only.
template-deep-research
Template-native research intake, literature search, source verification, synthesis, fact-checking, and systematic-review planning. USE WHEN the user asks to research a topic, build a literature corpus, fact-check claims, prepare a PRISMA-style review, or clarify a research question before manuscript work.
template-manuscript-claim-verification
Triple-pass verification of every manuscript claim against code, data, refs, and renderer; repair prose while staying renderable. USE WHEN pre-submission, pre-Zenodo, pre-arXiv, abstract numbers disagree with CSV, citations do not support sentences, or user asks to triple-check / verify every claim — even without docs/prompts. Not for casual PDF summary.
template-manuscript-creation
Scaffold a research manuscript and project layout from a research brief — sections, config.yaml, src/, scripts/, tests. USE WHEN starting a new paper, new projects/ tree, manuscript from topic description, or aligning with template_code_project exemplar — even without copy-paste prompts.
template-manuscript-cross-references
Audit or author registry-driven manuscript cross-refs — labels.yaml, [[FIG:]], [[THMREF:]], [[VAR:]] tokens. USE WHEN fixing figure/equation/theorem numbering, orphan registry keys, hard-coded "Theorem 7.3" in prose, or [[MISSING:]] injection failures — even for Pandoc projects that also use a YAML registry.
template-pipeline-debugging
Systematic pipeline DAG failure triage for the Research Project Template. USE WHEN ./run.sh or execute_pipeline.py fails, a stage stalls (setup, tests, analysis, render, validate, LLM, copy), pytest/coverage gate fails mid-pipeline, PDF render or validate breaks, Project Analysis finishes too fast with no figures, or user says pipeline debug, stage failed, resume checkpoint, core-only triage — even without naming this skill or docs/prompts.
template-reproducibility-audit
Deterministic reproducibility audit — fixed seeds, regenerate-from-clean, double-run diff before Zenodo/arXiv/release. USE WHEN outputs drift between runs, "worked on my machine", need regenerate-from-clean proof, or pre-release reproducibility check — even without naming docs/prompts.
template-startup
Full installation and validation workflow for a fresh clone of the Research Project Template. Installs dependencies, runs pre-commit hooks, executes the core pipeline against template_code_project, validates outputs, and reports a structured PASS / FAIL for each checkpoint. USE WHEN the user says "start", "set up the repo", "install and validate", "does everything work", "first time setup", or any variant of bootstrapping a fresh or unknown checkout.
template-workflows
Router and workflow hub for the Research Project Template — code, tests, manuscripts, pipeline, validation, docs, and reproducibility. USE WHEN the user wants to audit the repo, debug ./run.sh or execute_pipeline.py, add a feature, write tests, scaffold a manuscript, verify claims, fix cross-references, run validation gates, refactor, or prepare a Zenodo release, discover relevant template skills, improve agent routing, review external agentic operating models or retrieval references such as Steward OS, AutoResearch CLI, or LEANN, research a topic, write/review/revise a paper, or run a research-to-publication workflow — even if they never say "prompt", "skill", or docs/prompts. Also USE WHEN intent is ambiguous ("something wrong with my manuscript", "full health check", "fix the pipeline") — pick ONE child skill from the routing table and follow it. Do NOT use for generic homework, unrelated app security scans, or casual PDF summarization.
claude-api
Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST
clearfront-osint
Clearfront OSINT is a free, open-source tool that scans a digital footprint. Use it when someone wants to know what is public about an email, username, phone number, name, domain or IP: their own exposure, breached or infostealer-leaked credentials, accounts reused across sites, data broker and people-search listings, GPS in a photo, or authorized recon on a target they are cleared to assess. It checks Have I Been Pwned, Hudson Rock, Shodan, Censys, VirusTotal, crt.sh, the Wayback Machine, GreyNoise and thousands of username sites, then reports each finding with its source, confidence and severity. Runs locally.
sales-amical
Amical platform help — open-source, local-first AI dictation app with Whisper STT, context-aware formatting, Ollama/OpenRouter LLM, MCP voice commands, and 100+ language support (MIT license). Use when setting up Amical on macOS or Windows for the first time, choosing between Whisper model sizes for accuracy vs speed, configuring Ollama for fully offline text formatting, context-aware formatting not adapting to the active application, microphone not switching or audio input issues, custom vocabulary not recognizing industry terminology, comparing Amical to Wispr Flow or Superwhisper for privacy-first dictation, or setting up voice commands with MCP integrations. Do NOT use for picking between meeting note-takers generally (use /sales-note-taker) or reviewing a single call for coaching (use /sales-call-review).
adr_gate
ADR Gate — evaluates after non-trivial tasks whether an ADR is warranted; writes to Corvin-ADR repo when yes, names the skip reason when no, requires three-level analysis (conceptual/structural/implementation), and generates E2E tests for every new structural invariant so LDD has a loss signal.
Showing top 100 of 418 skills using Ollama by quality score.
See all 418 skills via search →Integration detected automatically from skill content. Some results may be false positives.