Results for “exist”

Plan a unit using backwards design from desired outcomes through assessment evidence to learning activities. Use when starting a new unit or redesigning an existing one from standards.

Orchestrates bounded, governed iteration loops over existing agent commands and offices, with explicit stopping conditions, checkpoints, and honest terminal states.

Creates comprehensive technical documentation from existing codebases. Analyzes architecture, design patterns, and implementation details to produce long-form technical manuals and ebooks. Use PROACTIVELY for system documentation, architecture guides, or technical deep-dives.

Analyzes production code to find gaps in existing tests by reasoning about hypothetical mutations and checking whether tests would catch them.

Creates and maintains concise AGENTS.md and CLAUDE.md project instruction files for AI coding agents, keeping them under 60 lines and referencing existing documentation.

Analyze existing code files to generate a project-specific coding standards document, with options for templates, README insertion, and inconsistency detection.

Generate interior design visualizations by redesigning existing rooms or creating new concepts with specific styles, colors, and furniture.

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

Generates or updates a governance skill card for an existing agent skill directory by analyzing source signals, building a grounded JSON context, and rendering a deterministic markdown card.

Refine existing images through conversational edits using Nano Banana 2, covering color grading, composition, element changes, style transfer, and cleanup with iterative refinement.

Extracts a language-agnostic ghost package (spec, tests, install and verify docs) from an existing repository, preserving behavior via tests.yaml and evidence bundles.

Provides an adaptive methodology for adding machine learning models to existing codebases, covering problem framing, data readiness, architectural decoupling, and baseline model integration.

Authors or reviews Know/Understand/Do charts for competency-based learning targets across developmental bands. Handles seven input types from raw curriculum documents to existing LT sets. Routes to upstream skills when stronger inputs are available.

Design a document set for a document-based lesson — selecting and sequencing sources for analytical tension around a central question. Use when assembling sources for a new lesson or when an existing set produces flat responses.

Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when user wants to stress-test a plan against their project's language and documented decisions.

AI coding agents fail in consistent, predictable ways. They fabricate npm packages that don't exist. They catch errors and continue silently. They add features you never asked for. They lose context mid-session and forget what they were doing.

Use when choosing or configuring MCP servers for research work, when a literature, reference manager, or scholarly search server needs a trust check before installation, or when an existing research tool stack needs a data flow and permission audit.

Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when user wants to stress-test a plan against their project's language and documented decisions.

Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when user wants to stress-test a plan against their project's language and documented decisions.

Use when creating a new skill under .agents/skills/, editing an existing one, or deciding whether a technique deserves to become a skill at all - covers SKILL.md structure, the description field, and how to keep a skill discoverable and token-efficient.

Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when user wants to stress-test a plan against their project's language and documented decisions.

Publishes a local Markdown file to a user-specified Confluence location, creating a new page or updating an existing one through the Atlassian MCP server. Use when the user wants to post, publish, push, or sync a Markdown file to a Confluence space or page. Requires a configured Atlassian MCP server. Does not write or generate the Markdown itself — point it at an existing file, or use project-documentation-to-confluence for the document-then-publish flow, or plan-a-feature-to-confluence for the plan-then-publish flow. Does not publish to Jira — use work-items-to-jira.

Builds detailed voice profiles for characters, narrators, brands, or AI agents, covering diction, syntax, rhythm, worldview, signature patterns, and failure modes, and can reverse-engineer profiles from writing samples or audit existing ones.

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

Use when a human asks to connect to or enter Agent Internet or AI Internet, get their agent online, or open Agent Internet Browser, Bot Browser, a Bot page, a Bot homepage, a domain alias, a chain pin, a MetaApp, a MetaFile, or a map through the existing local Browser entrypoint, including opening a resource in a new Browser tab; also use when the human wants to find or discover on-chain MetaApps by topic, tag, publisher, or time range — such as "what on-chain mini-games exist", "apps published in the last 30 days", or "open the on-chain buzz app" — list the remixes of a known app, read what an app does, or remix and republish an existing MetaApp; also use when the human wants to find or discover on-chain users or Bots by name, personality, skill, or recency — such as "view Alice's bot page", "find cheerful users to chat with", or "find a bot that can translate" — or read an identity's full on-chain profile.

Reuse a running Chrome session for browser automation via Playwriter CLI + MCP. Use when the task depends on the browser the user already has open — existing logins, cookies, extensions, passkey-friendly flows, or live-tab continuity. Route repeatable fresh-browser or CI-style checks to `browser-harness` instead.

Create or update reusable skills for this agent. Use this skill ONLY when the user asks to create a new skill, edit an existing skill, improve a SKILL.md, or capture a repeated workflow as a reusable skill. Do not use this skill for one-off tasks.

Rank a topic's user-flow branches by proof priority (value × risk × frequency) right after user-flow-map, ordering the branches, gating variation breadth, and promoting or pruning flows so state-model and ux-variations grow the tree in proof order — writes only existing flow-tree ordering fields, no schema change.

Refactor ACF Composer blocks — evolve blocks along 4 axes: rendering model, field composition, block variants $styles, InnerBlocks adoption; legacy block migration, ACF Composer v2 to v3, block phase classification, atomic vs container, block evolution report, get_block_wrapper_attributes, $styles, $innerBlocks, refactor without breaking existing content, block refactoring report

Build or refactor CLI tools designed for AI agent consumption: non-interactive, flag-driven, idempotent, with --json output and --dry-run preview. Use when creating a new script the agent will call, adding agent-friendly flags to an existing tool, or debugging why an agent keeps failing to use your CLI.

Extend or continue an existing video clip on RunComfy via the `runcomfy` CLI. Routes to Google Veo 3-1's `extend-video` and `fast/extend-video` endpoints — pick the source video plus a prompt describing what should happen next, and the model produces a clip that continues the original with consistent motion, lighting, and subject identity. Use when the user has a short Veo clip and wants it longer, or wants a chained narrative built shot-by-shot from a single seed clip. Triggers on "extend video", "continue video", "longer video", "video extend", "make this clip longer", "Veo extend", "chain video shots", "video continuation", or any explicit ask to take an existing video and add more frames after it.

Extend or continue an existing video clip on RunComfy via the `runcomfy` CLI. Routes to Google Veo 3-1's `extend-video` and `fast/extend-video` endpoints — pick the source video plus a prompt describing what should happen next, and the model produces a clip that continues the original with consistent motion, lighting, and subject identity. Use when the user has a short Veo clip and wants it longer, or wants a chained narrative built shot-by-shot from a single seed clip. Triggers on "extend video", "continue video", "longer video", "video extend", "make this clip longer", "Veo extend", "chain video shots", "video continuation", or any explicit ask to take an existing video and add more frames after it.

Extend or continue an existing video clip on RunComfy via the `runcomfy` CLI. Routes to Google Veo 3-1's `extend-video` and `fast/extend-video` endpoints — pick the source video plus a prompt describing what should happen next, and the model produces a clip that continues the original with consistent motion, lighting, and subject identity. Use when the user has a short Veo clip and wants it longer, or wants a chained narrative built shot-by-shot from a single seed clip. Triggers on "extend video", "continue video", "longer video", "video extend", "make this clip longer", "Veo extend", "chain video shots", "video continuation", or any explicit ask to take an existing video and add more frames after it.

Builds a feature specification from scratch with plan-a-feature and publishes it to a user-specified Confluence location, posting the spec as a parent page and each companion artifact (decision log, team findings, technical notes) as a child page beneath it. Use when the user wants a new feature planned, designed, scoped, or specified AND posted to a Confluence space or page. Requires a configured Atlassian MCP server. Does not plan to local files only — use plan-a-feature. Does not publish an arbitrary existing markdown file — use markdown-to-confluence. Does not refine or stress-test an existing plan — use iterative-plan-review. Does not document already-built features to Confluence — use project-documentation-to-confluence.