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SkillsMP는 bryancostanich/Cercano에서 47개의 skill을 수집했습니다. skill을 열어 소스와 세부 정보를 확인하세요.
수집된 skill 47개 중 40개를 표시합니다.
Deep multi-source research tool that identifies authoritative sources, systematically searches, analyzes and ranks findings, chases cited references, and compiles a structured report with executive summary, contradiction detection, gap analysis, and follow-up…
원문 언어: 영어
Generate doc comments for exported Go symbols using local AI and write them directly to the file. The host never sees the file contents — Cercano handles the entire read-think-write cycle locally.
원문 언어: 영어
Compute the expected result before running any simulation or sweep.
원문 언어: 영어
Stop and weigh real options before coding a structural decision.
원문 언어: 영어
Reduce, observe, reason, predict, probe, then fix — no guessing.
원문 언어: 영어
Match the test tier to the size of the change.
원문 언어: 영어
Isolate every feature branch in its own worktree; never share the root workspace.
원문 언어: 영어
Query or update Cercano's runtime configuration without restarting the server. Use action 'get' to list available local models. Use action 'set' to switch the active local runtime or model, change the Ollama endpoint URL, or change the cloud provider and…
원문 언어: 영어
View Cercano usage statistics and cloud token savings. Shows total requests, tokens processed locally, cloud tokens reported by the host, percentage kept local, and breakdowns by tool, model, and day.
원문 언어: 영어
Deep multi-source research tool that identifies authoritative sources, systematically searches, analyzes and ranks findings, chases cited references, and compiles a structured report with executive summary, contradiction detection, gap analysis, and follow-up…
원문 언어: 영어
Generate doc comments for exported Go symbols using local AI and write them directly to the file. The host never sees the file contents — Cercano handles the entire read-think-write cycle locally.
원문 언어: 영어
Query or update Cercano's runtime configuration without restarting the server. Use action 'get' to list available local models. Use action 'set' to switch the active local runtime or model, change the Ollama endpoint URL, or change the cloud provider and…
원문 언어: 영어
Use when the user wants to check or change Cercano's runtime configuration — switch the local runtime or model, change the Ollama endpoint URL, or change the cloud provider and model. No server restart needed.
원문 언어: 영어
Classify or triage text using local AI via Cercano. Returns a category, confidence level, and brief reasoning. Use this for quick local triage of errors, logs, code quality issues, bug reports, or any content that needs categorization without sending it to…
원문 언어: 영어
Explain code or text using local AI via Cercano. Returns a clear explanation of what the code does, its key interfaces, and data flow. Use this to understand unfamiliar code, complex algorithms, or dense documentation locally before deciding what context to…
원문 언어: 영어
Extract specific information from text using local AI via Cercano. Returns only the relevant sections matching your query. Use this to pull function signatures, error messages, config values, API endpoints, or other targeted information from large text…
원문 언어: 영어
Fetch a URL and extract readable text content locally. Returns full extracted text (not a summary) — HTML is stripped to clean plain text.
원문 언어: 영어
Initialize Cercano for a project by scanning the repo and building a context file. Makes all Cercano tools project-aware with domain-specific knowledge. Run this once per project for dramatically better local AI responses.
원문 언어: 영어
Run prompts against local AI models via Cercano and Ollama. Use this for local inference — faster, private, and zero cost. Handles chat-style queries and agentic code generation with automatic validation. Offload summarization, explanation, code writing, and…
원문 언어: 영어
List AI models available on the Ollama instance connected to Cercano. Returns model names, sizes, and modification dates. Use this to discover what local models are available before choosing one for inference or switching the active model.
원문 언어: 영어
Research a question using DuckDuckGo search and local AI analysis. Crafts search queries, fetches top results, and synthesizes a sourced answer — all locally.
원문 언어: 영어
Submit cloud token usage data to Cercano (opt-in). This sends data, not a report — use cercano_stats to view usage. Helps track cloud tokens alongside local inference for accurate local-vs-cloud comparison.
원문 언어: 영어
Summarize text or files using local AI via Cercano without sending content to the cloud. Supports brief, medium, and detailed summary lengths.
원문 언어: 영어
Use when the user needs to categorize, triage, or classify text — error severity, code quality, bug reports, log entries. Quick local classification without cloud round-trip.
원문 언어: 영어
Use when the user needs thorough, multi-source research with ranked findings, citations, and synthesis. Use this for literature reviews, competitive analysis, technical deep-dives, or any research that needs more than a quick answer. Prefer this over…
원문 언어: 영어
Use when the user wants to generate or update doc comments for Go code. Handles the entire read-think-write cycle locally — the host never sees the file contents. Supports dry_run mode to preview.
원문 언어: 영어
Use when the user asks to explain unfamiliar code, complex algorithms, or dense documentation. Processes the explanation locally before deciding what context to send to the cloud. Prefer this for initial code understanding.
원문 언어: 영어
Use when the user needs to pull specific information from large text — function signatures, error messages, config values, API endpoints. Extracts locally instead of reading entire files into cloud context.
원문 언어: 영어
Use when the user asks to fetch, read, or open a specific URL. Use this INSTEAD of WebFetch to read web pages locally without sending content to the cloud. DO NOT TRIGGER when: user asks a research question without a specific URL (use cercano-research…
원문 언어: 영어
Use when setting up Cercano for a new project. Scans the repo to build a project context file that makes all Cercano tools project-aware. Run this once per project for better local AI responses.
원문 언어: 영어
Use when the user wants to run a prompt against a local AI model via Ollama. Handles both chat-style queries and agentic code generation with validation. Use this to offload work to local inference — faster, private, zero cost.
원문 언어: 영어
Use when the user wants to see what AI models are available on their Ollama instance. Returns model names, sizes, and modification dates.
원문 언어: 영어
Use when the user asks to research, look up, investigate, find information, or learn about any topic. Use this INSTEAD of WebSearch or WebFetch for general research questions. ALWAYS prefer this tool for web research. DO NOT TRIGGER when: user provides a…
원문 언어: 영어
Use when the user asks about Cercano usage, token savings, or local vs cloud inference stats. Shows total requests, tokens processed locally, and breakdowns by tool, model, and day.
원문 언어: 영어
Use when the user wants to submit cloud token usage data to Cercano for tracking. This sends data, not a report — use cercano_stats to view usage. Opt-in telemetry for local-vs-cloud comparison.
원문 언어: 영어
Use when the user needs to summarize large text, files, logs, or diffs. ALWAYS prefer this over reading large files directly into cloud context. Processes content locally and returns a concise summary.
원문 언어: 영어
Fetch a URL and extract readable text content locally. Returns full extracted text (not a summary) — HTML is stripped to clean plain text.
원문 언어: 영어
Research a question using DuckDuckGo search and local AI analysis. Crafts search queries, fetches top results, and synthesizes a sourced answer — all locally.
원문 언어: 영어
View Cercano usage statistics and cloud token savings. Shows total requests, tokens processed locally, cloud tokens reported by the host, percentage kept local, and breakdowns by tool, model, and day.
원문 언어: 영어
Summarize text or files using local AI via Cercano without sending content to the cloud. Supports brief, medium, and detailed summary lengths.
원문 언어: 영어