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Found 8,327 Skills
Optional Stage 0 of the feature workflow — clarify vague ideas through dialogue until they are ready to enter the design phase. The role of AI is a thinking partner: dig out the real problem the user wants to solve (instead of sticking to the first solution they blurt out), actively evaluate the solution when the user brings it up, and propose better alternatives if necessary. After the discussion, output {slug}-brainstorm.md to document the results. Trigger scenarios: The user says "I have an unclear idea", "Let's brainstorm first", "The feature direction is still undecided", or the user brings a specific solution but wants to hear other ideas first. Skip this stage and proceed directly to design if the idea is already clear and the user does not want to discuss the solution further. This stage also does not handle bugs and refactoring.
Document the pitfalls encountered or good practices discovered during this work into searchable learning documents, so that both AI and humans can look them up when similar tasks arise in the future. Two tracks: The pitfall track records experiences where "things should have worked but didn't" — bugs, configuration traps, environment issues, integration failures; The knowledge track records findings that "should be the default approach going forward" — best practices, workflow improvements, reusable patterns. Trigger scenarios: Proactively prompt for input when wrapping up feature-acceptance or issue-fix, or when the user says phrases like "document knowledge", "learning", "document learnings", "record this experience". Spec documents record what was done and how it was done, while learning documents record what pitfalls were encountered / what was learned — the two complement each other and are not interchangeable.
Interact with KWeaver Knowledge Network and Decision Agent — build knowledge networks, query Schema/instances, semantic search, execute Action, Agent CRUD and conversation, Trace data analysis. Interact with Dataflow document processes — list processes, trigger runs, query run history, view step logs. Interact with Skill management module — register Skill, search in market, progressive reading, download and installation. Interact with Toolbox / Tool — create toolbox, upload OpenAPI tools, publish, start and stop. Interact with Vega observability platform — query Catalog/resources/connector types, health inspection. This skill is automatically activated when users mention intents such as "knowledge network", "knowledge graph", "query object type", "execute Action", "what Agents are there", "create Agent", "converse with Agent", "list all Agent templates", "list Agents I created", "list Agents in private space", "dataflow", "data flow", "process orchestration", "process run records", "process logs", "trigger dataflow", "view dataflow run history", "Skill", "skill package", "register Skill", "install Skill", "read SKILL.md", "toolbox", "toolbox", "upload tool", "register tool", "OpenAPI tool", "enable tool", "publish toolbox", "data source", "data view", "atomic view", "Catalog", "Vega", "health check", "inspection", "trace", "evidence chain", "data flow tracking", "data source", "how data is obtained", etc.
Mozilla Observatory integration. Manage data, records, and automate workflows. Use when the user wants to interact with Mozilla Observatory data.
Subscribe-HR integration. Manage data, records, and automate workflows. Use when the user wants to interact with Subscribe-HR data.
Cisco Meraki integration. Manage data, records, and automate workflows. Use when the user wants to interact with Cisco Meraki data.
Two-way sync between a local paper directory and an Overleaf project via the Overleaf Git bridge (Premium feature). Lets you keep ARIS audit/edit workflows on the local copy while collaborators edit in the Overleaf web UI. Token never touches the agent — user does the one-time auth via macOS Keychain. Use when user says "同步 overleaf", "overleaf sync", "推送到 overleaf", "connect overleaf", "Overleaf 桥接", "pull overleaf", "push overleaf", or wants to bridge their ARIS paper directory with an Overleaf project.
Generate deterministic publication-quality architecture, workflow, and pipeline diagrams from structured JSON (FigureSpec) into editable SVG. Use when user says "架构图", "workflow 图", "pipeline 图", "确定性矢量图", "figure spec", "draw architecture", or needs precise, editable, publication-ready vector diagrams. Preferred over AI illustration for formal architecture/workflow figures.
Analyze ARIS usage logs and propose optimizations to SKILL.md files, reviewer prompts, and workflow defaults. Outer-loop harness optimization inspired by Meta-Harness (Lee et al., 2026). Use when user says "优化技能", "meta optimize", "improve skills", "分析使用记录", or wants to optimize ARIS's own harness components based on accumulated experience.
Workflow 4: Submission rebuttal pipeline. Parses external reviews, enforces coverage and grounding, drafts a safe text-only rebuttal under venue limits, and manages follow-up rounds. Use when user says "rebuttal", "reply to reviewers", "ICML rebuttal", "OpenReview response", or wants to answer external reviews safely.
Ultra-lightweight channel for refactor processes - used when changes are obviously too small to justify the full scan → design → apply three-stage workflow. AI directly identifies 1-3 low-risk optimization points, confirms with the user once, modifies in-place using classic methods, and validates itself by running tests. No scan checklist, no design documentation, no multi-step HUMAN verification required. Trigger scenarios: When the user says "quick refactor", "small refactor", "simply optimize XX function", "modify directly", "skip all those steps", and the scope of changes is clearly limited to a single function/single component, with tests available for self-validation.
Operate, troubleshoot, and explain ERDA CI/CD workflows through erda-cli. Use when users need help running pipelines, checking status, reading logs, reviewing build history, or diagnosing delivery failures across the build and deploy path.