Claude Code Skills · page 78

Complete workflow for submitting code changes — create branch, commit, open PR, check CI, fix failures, and merge.

Release a new version of Chorus — bump version, update CHANGELOG, commit, tag, and create GitHub release.

Optional divergent-then-convergent dialogue for fuzzy ideas. Invoked from the idea skill as a prelude to structured elaboration; produces one ElaborationRound of decision-point Q&A and returns control. Never writes files, never posts comments, never resolves elaboration.

Chorus AI Agent collaboration platform — overview, common tools, setup, and routing to stage-specific skills.

Chorus Development workflow — claim tasks, report work, manage sessions, and integrate with Claude Code Agent Teams.

Chorus Idea workflow — claim ideas, run elaboration rounds, and prepare for proposal creation.

Opt-in OpenSpec-mode authoring for Chorus PM workflows in Claude Code. Detects the local `openspec` CLI, scaffolds `openspec/changes/<slug>/` on disk, and mirrors Markdown files into Chorus document drafts via the `chorus-api.sh` wrapper. Required reading for the proposal, develop, and yolo skills whenever the user has the `openspec` CLI installed.

Adversarial read-only review of a submitted Chorus proposal — document completeness, task granularity, AC↔requirement coverage, and the dependency DAG. Invoke after a proposal is submitted; ends with a VERDICT comment.

Chorus Proposal workflow — create proposals with document and task drafts, manage dependency DAG, validate and submit for review.

Quick Task workflow — skip Idea→Proposal, create tasks directly, execute, and verify.

Chorus Review workflow — approve/reject proposals, verify tasks, and manage project governance.

Adversarial verification of a submitted Chorus task against its AC and proposal documents — read the code, verify each criterion, run tests. Invoke after a task is submitted for verify; ends with a VERDICT comment.

Full-auto AI-DLC pipeline — from prompt to done. Automates the entire Idea -> Proposal -> Execute -> Verify lifecycle.

Read-only Chorus proposal reviewer. Fetches a proposal via MCP, audits PRD/task drafts against the originating Idea, and posts a structured VERDICT comment. Invoke by mounting this skill into a default sub-agent via spawn_agent(agent_type="default", items=[{ type: "skill", path: "chorus:chorus-proposal-reviewer", ... }, { type: "text", text: "Review proposal <uuid>. Max review rounds: 3." }]).

Read-only Chorus task reviewer. Fetches a task plus its acceptance criteria plus originating proposal documents via MCP, independently verifies the implementation, and posts a structured VERDICT comment. Invoke by mounting this skill into a default sub-agent via spawn_agent(agent_type="default", items=[{ type: "skill", path: "chorus:chorus-task-reviewer", ... }, { type: "text", text: "Review task <uuid>. Max review rounds: 3." }]).

Optional divergent-then-convergent dialogue for fuzzy ideas. Invoked from the idea skill as a prelude to structured elaboration; produces one ElaborationRound of decision-point Q&A and returns control. Never writes files, never posts comments, never resolves elaboration.

Chorus Development workflow — claim tasks, report work, self-check acceptance criteria, and submit for verification.

Chorus Idea workflow — claim ideas, run elaboration rounds, and prepare for proposal creation.

Chorus Proposal workflow — create proposals with document and task drafts, manage dependency DAG, validate and submit for review.

Read-only adversarial Chorus proposal reviewer — audits PRD/task drafts against the originating Idea and posts a single structured VERDICT comment.

Quick Task workflow — skip Idea→Proposal, create tasks directly, execute, and verify.

Chorus Review workflow — approve/reject proposals, verify tasks, and manage project governance.

Read-only adversarial Chorus task reviewer — independently verifies an implementation against its acceptance criteria and posts a single structured VERDICT comment.

Full-auto AI-DLC pipeline — drive a single prompt from Idea through Proposal, Execution, and Verification to Done.

Use when manually verifying a Chorus frontend change in a real browser — finding local login credentials, driving the running dev server with the Playwright MCP, logging in, navigating to a page, and capturing snapshots/screenshots for e2e acceptance.

Final ship-time review of an Idea's aggregate code change — the whole feature across all its tasks, not one task. Read the integrated code, check cross-task integration / architecture / security / regression / coverage, run tests. Invoke after the last task of an idea-rooted proposal is verified; ends with a VERDICT comment on the Idea.

Read-only Chorus code-review gateway — the final ship-time review of an Idea''s aggregate code change (the whole feature across all its tasks, not one task). Fetches the Idea, its approved proposals, documents, and tasks via MCP, reviews the aggregate implementation, and posts a structured VERDICT comment on the Idea. Invoke by mounting this skill into a default sub-agent via spawn_agent(agent_type="default", items=[{ type: "skill", path: "chorus:chorus-code-reviewer", ... }, { type: "text", text: "Review the code for idea <uuid>. Round: N." }]).

Read-only adversarial Chorus code-review gateway — independently reviews an Idea's aggregate code change (the whole feature across all its tasks) and posts a single structured VERDICT comment on the Idea.

free4chat Agent media plane (Go runtime, in-process Pion) architecture quick reference and staged debugging discipline — multi-MID attribution, signaling direction self-inspection, lazy OnTrack, daemon/env traps. Use when debugging Meeting Notes audio, Voice Reply, image/text attachments, unresponsive agents, or non-flowing RTP.

free4chat local full-stack E2E loop — single wrangler instance, Turnstile bypass switches, curl/MCP validation sequences, split-brain DO and daemon env traps. Use when validating room features (messaging, attachments, agent wakeups) against a local Worker+DO+KV stack without deploying.

Strict provenance-first SOP for real deployed Free4Chat Meeting Notes, Voice Reply, Pion, Cloudflare SFU, and browser-media experiments.

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Evaluate proposals - feasibility, engineering payoff, risk.

System design - module boundaries, API contracts, ADRs.

Python server code, APIs, async, strict typing.

CI failures - read error, minimal fix, verify.

DevOps - Docker, CI/CD, cloud infra, monitoring.

Documentation - README, API docs, ADRs, tutorials.

React / Next.js UI, state, accessibility.

Planning - decompose goals, create tasks via task server.

ML - training, inference, embeddings, evaluation.

LLM prompts - design, evaluate, tune instructions.

Test writing - pytest suites, edge cases, regressions.

Git merge conflicts - resolve without losing intent.

Retrieval - vector DBs, embeddings, hybrid search, reranking.

Code review - correctness, tests, merge-readiness.

Ideation - generate bold feature proposals.

Cross-cell coordination - resolve conflicts, decide pivots.

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AWS API Gateway for REST and HTTP API management. Use when creating APIs, configuring integrations, setting up authorization, managing stages, implementing rate limiting, or troubleshooting API issues.

AWS Bedrock foundation models for generative AI. Use when invoking foundation models, building AI applications, creating embeddings, configuring model access, or implementing RAG patterns.

AWS CloudFormation infrastructure as code for stack management. Use when writing templates, deploying stacks, managing drift, troubleshooting deployments, or organizing infrastructure with nested stacks.

AWS CloudWatch monitoring for logs, metrics, alarms, and dashboards. Use when setting up monitoring, creating alarms, querying logs with Insights, configuring metric filters, building dashboards, or troubleshooting application issues.

AWS Cognito user authentication and authorization service. Use when setting up user pools, configuring identity pools, implementing OAuth flows, managing user attributes, or integrating with social identity providers.

AWS DynamoDB NoSQL database for scalable data storage. Use when designing table schemas, writing queries, configuring indexes, managing capacity, implementing single-table design, or troubleshooting performance issues.

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AWS ECS container orchestration for running Docker containers. Use when deploying containerized applications, configuring task definitions, setting up services, managing clusters, or troubleshooting container issues.

AWS EKS Kubernetes management for clusters, node groups, and workloads. Use when creating clusters, configuring IRSA, managing node groups, deploying applications, or integrating with AWS services.

AWS EventBridge serverless event bus for event-driven architectures. Use when creating rules, configuring event patterns, setting up scheduled events, integrating with SaaS, or building cross-account event routing.

AWS Identity and Access Management for users, roles, policies, and permissions. Use when creating IAM policies, configuring cross-account access, setting up service roles, troubleshooting permission errors, or managing access control.

AWS Lambda serverless functions for event-driven compute. Use when creating functions, configuring triggers, debugging invocations, optimizing cold starts, setting up event source mappings, or managing layers.

AWS RDS relational database service for managed databases. Use when provisioning databases, configuring backups, managing replicas, troubleshooting connectivity, or optimizing performance.

AWS S3 object storage for bucket management, object operations, and access control. Use when creating buckets, uploading files, configuring lifecycle policies, setting up static websites, managing permissions, or implementing cross-region replication.

AWS Secrets Manager for secure secret storage and rotation. Use when storing credentials, configuring automatic rotation, managing secret versions, retrieving secrets in applications, or integrating with RDS.

AWS SNS notification service for pub/sub messaging. Use when creating topics, managing subscriptions, configuring message filtering, sending notifications, or setting up mobile push.

AWS SQS message queue service for decoupled architectures. Use when creating queues, configuring dead-letter queues, managing visibility timeouts, implementing FIFO ordering, or integrating with Lambda.

AWS Step Functions workflow orchestration with state machines. Use when designing workflows, implementing error handling, configuring parallel execution, integrating with AWS services, or debugging executions.

Call Fetch.ai Agentverse agents by address. Search the Agentverse marketplace, browse a curated catalog of top agents (Tavily Search, ASI1-Mini, DALL-E 3, Technical Analysis, Asset Signal, Translator, Statistics, Github), and send ChatMessages to any agent. Use when working with Fetch.ai, Agentverse, uAgents, decentralized AI agents, or when the user wants to discover or message an agent on the Fetch.ai network.

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Agent-browser usage guide. Read this before running any agent-browser commands. Covers the snapshot-and-ref workflow, navigating pages, interacting with elements (click, fill, type, select), extracting text and data, taking screenshots, managing tabs, handling forms and auth, waiting for content, running multiple browser sessions in parallel, and troubleshooting common failures. Use when the user asks to interact with a website, fill a form, click something, extract data, take a screenshot, log into a site, test a web app, or automate any browser task.

Automate Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify, etc.) using agent-browser via Chrome DevTools Protocol. Use when the user needs to interact with an Electron app, automate a desktop app, connect to a running app, control a native app, or test an Electron application. Triggers include "automate Slack app", "control VS Code", "interact with Discord app", "test this Electron app", "connect to desktop app", or any task requiring automation of a native Electron application.

Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.

Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as `reportlab`, `pdfplumber`, and `pypdf` for generation and extraction.

Use this skill any time a .pptx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates, layouts, speaker notes, or comments. Trigger whenever the user mentions \"deck,\" \"slides,\" \"presentation,\" or references a .pptx filename, regardless of what they plan to do with the content afterward. If a .pptx file needs to be opened, created, or touched, use this skill.

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

This skill should be used when user asks to "query Azure resources", "list storage accounts", "manage Key Vault secrets", "work with Cosmos DB", "check AKS clusters", "use Azure MCP", or interact with any Azure service.

This skill should be used when user encounters "Tavily MCP error", "Tavily API key invalid", "web search not working", "Tavily failed", or needs help configuring Tavily integration.

Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.

This skill should be used when user asks to "deploy with Dokploy", "use Dokploy Cloud", "manage self-hosted Dokploy", "deploy Docker Compose on Dokploy", "manage Dokploy databases", "configure Dokploy domains", or "look up Dokploy CLI commands".

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.

Use for new frontend applications, dashboards, games, creative websites, hero sections, and visually driven UI from scratch, or when the user explicitly asks for a redesign/restyle/modernization. Builds from high-taste image-generated concept design with faithful implementation and browser testing.

This skill should be used when user asks about "GCloud logs", "Cloud Logging queries", "Google Cloud metrics", "GCP observability", "trace analysis", or "debugging production issues on GCP".

This skill should be used when user asks to "clean gone branches", "remove deleted local branches", "prune branches removed from remote", or explicitly invokes "clean-gone-branches".

This skill should be used when user asks to "commit these changes", "write commit message", "stage and commit", "create a commit", "commit staged files", or explicitly invokes "commit-staged".

This skill should be used when user asks to "create a PR", "make a pull request", "open PR for this branch", "submit changes as PR", "push and create PR", or explicitly invokes "create-pr".