Explore

Develop, debug, test, review, document, and release the premiere-pro-mcp repository. Use when changing MCP tools, schemas, server registration, CEP or UXP bridges, generated ExtendScript, authority profiles, packaging, release metadata, or compatibility claims in this repo.

Use the `tilth` CLI for code reading, outlining, search, callers, blast-radius deps, and structural diffs. Activate when the user asks to explore a repo, find a symbol, trace callers, read a file, view a diff, or analyze impact. Prefer `tilth` over `grep`/`cat`/`find`/`ls` — one invocation returns AST-aware outlines, definitions, callees, and usages.

Use when you need to store, retrieve, search, or manage documents in a local knowledge base with semantic search and hybrid (vector + full-text) retrieval. Also use when interacting with the documentation server web interface, managing uploads, or performing AI-powered document analysis. Use this instead of MCP-native tool definitions when context efficiency is a concern.

Use this when a user wants to search Daiso/다이소, compare product price candidates, nearby restaurants/cafes/음식점/카페, convenience stores/편의점, marts, Olive Young/올리브영, Megabox/메가박스, Lotte Cinema/롯데시네마, or CGV data through the Daiso project. Honor explicit no-install requests with remote MCP first; otherwise prefer the daiso CLI for direct execution, use the MCP endpoint when the host app supports remote MCP, and choose commands for products, stores, inventory/재고, compare, places, movies, showtimes, seats, health checks, and raw JSON output.

Reconcile one existing OpenSpec specification from deterministic OpenLore MCP observations. Use when a spec may be incomplete, stale, partially covered, or orphaned from current code.

Write and run real tests for a function or spec scenario after reading implementation and contract evidence. Use when asked to add, improve, or repair tests without stubs or placeholders.

Review code changes using OpenLore risk, call, coverage, and cluster evidence without editing code. Use when asked for a change review, pre-PR safety check, or merge recommendation.

Identify a high-priority refactoring target, assess its blast radius, and write .openlore/refactor-plan.md without changing code. Use when asked to plan or prioritize a refactor.

Implement a brownfield story with OpenLore orientation, risk checks, spec validation, tests, and drift detection. Use when asked to implement or continue a story in an existing codebase.

Author a new OpenSpec domain specification from deterministic OpenLore MCP evidence. Use when asked to reverse-engineer, generate, or document a specification for existing code.

Apply a confirmed .openlore/refactor-plan.md with a test gate after each change. Use when asked to execute or continue an OpenLore refactoring plan.

Debug with OpenLore structural context, an explicit root-cause hypothesis, and RED/GREEN verification. Use when a bug, failure, or regression needs diagnosis and repair.

Transform a feature idea into an annotated story using a Domain Sketch or Constrained Option Tree. Use when asked to brainstorm, explore, or shape a feature before implementation.

Run a full static OpenLore analysis and summarize architecture, call graph, refactoring issues, and duplicate code. Use when asked to analyze, map, or assess a codebase without LLM inference.

Read, search, list, and send the user's macOS Messages through the mac-messages MCP server. Use when a task needs recent texts, messages matching a phrase, a conversation or group chat list, a send-ready phone number or email for a contact, a message attachment or its contents, iMessage reachability, a new Contacts entry, a message scheduled for later, or an outgoing iMessage/SMS/RCS message.

Governance behavior for Muse agents governed by DashClaw. Teaches the governance protocol over REST: when to call guard, how to interpret allow/warn/block/require_approval, recording actions and outcomes, plan-first execution with preflight approval, and waiting for human review. Trigger on: governed agent, dashclaw governance, guard policy, approval wait, plan authorization, action recording, risk threshold.

Compile the week's maintainer-log entries + git history into ONE pasteable Reddit-ready DashClaw update. Drafts only — publishing stays human (MAINTAINER.md §4 spirit). Use when Wes asks for the weekly update, a Reddit digest, or "what happened this week".

The single command that gets a DashClaw change ON MAIN AND LIVE — it resolves everything blocking production, never defers, and never hands back a checklist. Lands feature branches on main (rebase, gate, merge, push so Vercel deploys), bumps the unified platform+SDK version, and realigns every *description* of the system with the live code: README, PROJECT_DETAILS, SDK READMEs, /docs, generated artifacts (API inventory, OpenAPI, download bundles), plugins/skills/hooks/MCP, marketing/landing pages, the drift-prone hardcoded counts (routes, SDK methods, MCP tools/resources, guard policies) and stale freshness date-stamps. The one step it can't finish itself is the credential-gated SDK publish (`npm run release:sdks`). Use whenever the user wants to ship, land, or finish a change — get it on main, make it live, cut a release, bump the version, refresh all the docs, make everything accurate, fix wrong counts or old dates. Not for building or debugging the feature itself.

Debug DashClaw errors, signal issues, and misconfigurations

Set up a DashClaw instance, install the CLI tool, and configure Claude Code hooks

Register any agent (including this one) as a governed agent on a DashClaw instance

Human-in-the-loop approval workflows for governed agent actions

Integrate DashClaw SDK into any agent using the 4-step governance loop

Create and test DashClaw guard policies for agent governance

Set up compliance exports, drift detection, evaluations, scoring, and learning analytics

Contribute to the DashClaw codebase — architecture, scaffolding, tests, CI

Governance behavior for AI agents governed by DashClaw. Teaches the governance protocol: when to call guard (risk thresholds), how to interpret decisions (allow/warn/block/require_approval), when to record actions, how to wait for approvals, and session lifecycle management. Loads org-specific policies and capabilities from MCP resources at session start. Use with @dashclaw/mcp-server. Trigger on: governed agent, dashclaw governance, guard policy, approval wait, governed capability, risk threshold, action recording, session lifecycle.

Sync delta specs from a change to main specs. Use when the user wants to update main specs with changes from a delta spec, without archiving the change.

Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.

Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.

Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.

Implement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks.

Tells an agent what changed on a server since it last looked - plus status, Docker, backups, Proxmox. Every tool is classed read, write or destructive, so an agent can tell a look from a change before it makes the call.

Expert AI agent skill for interacting with, configuring, and troubleshooting the Search Console MCP server (GSC, Bing, GA4, and PageSpeed).

Use for marketing, social, replies, product copy, launch copy, and writing in the user's voice when their Emulo writing profile should guide the task. Do not use for unrelated execution or UI/UX design alone.

Use for execution, debugging, verification, planning, and shipping when the user's Emulo working profile should guide the task. Do not use for design/UI/UX work, marketing or social writing, or Emulo setup/mining.

Use when a brief has to become a film. Turns a one line ask into a Claude Design prompt written in the animations-v3 engine's own language, plus the built piece.jsx and a contact sheet to look at before anyone renders. Covers reference roles, the kit, the storyboard gate, the motion floor, and the verification commands. Do not use for backend work, UI design, or marketing copy alone.

Use only when the user explicitly asks to run, set up, update, re-mine, or deepen Emulo from real local AI coding-session history.

Use for UI, UX, visual hierarchy, frontend-design judgment, references, redesigns, and design critique when the user's Emulo taste should guide the task. Do not use for unrelated execution or marketing/social writing alone.

Use when the user keeps re-explaining the same preferences to a coding agent across chats (design taste, video style, review rules, how work should be verified, "as I said", "I told you"), or asks how to make Claude Code, Codex, Copilot CLI or OpenCode stop forgetting how they work. Runs the free local emulo --coach report over their own past sessions to show what they repeat, with dated receipts, then offers to build a reviewed you.md profile. Not for shared team memory, project documentation, or a single forgotten fact.

Only reach for external web search when the local corpus comes back empty or clearly insufficient. Forces the agent to try knowledge-rag first, then explicitly document why it needed to escalate. Prevents wasted API cost, latency, and (in air-gapped deployments) accidental network calls.

When the user reports a bug, error message, stack trace, unexpected behavior, or "why is this broken" question, search the corpus first for prior occurrences, known fixes, or related runbooks. Prevents re-solving problems the team already solved. Trigger on any error signature, exception name, stack trace snippet, or "why does X fail" query.

Three-step multi-tool workflow — search the corpus, fetch the most relevant document in full, then find similar documents. Use when a single search_knowledge hit is not enough because the user asked a "how does X work end to end" or "explain the pattern" or "give me the full picture" question. Prevents shallow answers on complex topics.

When performing code review on a PR, diff, snippet, or "look at this change" request, first consult the corpus for related ADRs, coding standards, prior patterns, and similar files. Grounds review comments in the team's actual decisions instead of generic best practices. Trigger on any review-style request — "review", "look at", "any issues with", "does this make sense".

After making a non-obvious architectural decision, solving a novel bug, agreeing on a coding standard, or reaching a conclusion worth remembering, index it back into the knowledge base so the next occurrence is one search away. Uses add_document or add_from_url. Closes the feedback loop that makes a RAG-backed team compound over time.

Measure retrieval quality using evaluate_retrieval (MRR@5 and Recall@5) and get_index_stats. Use after ingestion, a model or configuration change, or a reported search regression. Compare representative questions against a recorded baseline.

At the start of every new session or when the topic shifts significantly, probe the knowledge base to learn what is indexed. Calls get_index_stats + list_categories + a couple of exploratory search_knowledge queries. Prevents the agent from operating blind or making wrong assumptions about what the corpus contains.

Every technical claim drawn from the local corpus must ship with a source citation formatted as path:line or path:section. Trigger whenever the response quotes, paraphrases, or acts on knowledge that came from a search_knowledge or get_document call. Makes answers auditable and lets the user jump to source in one click.

Before answering any technical question, code request, architecture decision, or factual claim, call search_knowledge to check the local corpus. Trigger on any query that could be answered with prior work, indexed docs, ADRs, runbooks, or team context. Prevents hallucination and forces reliance on the indexed knowledge base.

For any security-related task — threat triage, incident response, MITRE ATT&CK mapping, CVE lookup, exploit analysis, defensive control validation, red/blue/purple team work — always consult the local corpus first. Assumes the RAG is loaded with security content (cybersecurity preset, MITRE data, threat reports, runbooks). Prevents wasted external threat-intel calls and grounds recommendations in the team's actual playbooks.

Pre-implementation edge-case and scenario explorer for gflow-cli. Decomposes a proposed feature or change across 13 structured dimensions specific to gflow-cli's failure surfaces (WAF/reCAPTCHA, Playwright selectors, auth token lifecycle, batch resume, data layer safety, cross-platform paths). Produces a severity-ranked scenario table to feed into the PLAN spec and the test matrix before EXECUTE begins.

Use when a pr-council-review (PR or branch mode) result needs independent corroboration from a different model family before trusting a GREEN verdict — high-stakes, security-sensitive, or architecturally significant reviews where same-model-family Claude subagents might share a blind spot. Also use when the user asks for "external", "second opinion", "cross-model", or names codex/antigravity (`agy`) or another external CLI coding agent alongside a review.

Answer questions about the user's own bank accounts and money using the bank MCP tools (list_accounts, get_balances, get_transactions, watches). Use whenever the user asks about balances, spending, income, subscriptions, whether a payment arrived, or wants a monthly review. Encodes the account map and categorisation rules so answers are consistent.

Refine an existing Kiln asset through bounded source reads, exact revision edits, and targeted image feedback. Use for repairs, variants, or proportion changes.

Check a Kiln asset's geometry, views, export fidelity, and behavior in its destination project. Use for delivery review, loading, materials, animation, collision, or runtime defects.

Compose existing assets into an exported scene or interactive proving environment, with deliberate placement, terrain, materials, integration checks and runtime qualification.

Run requested Kiln asset batches or compare coding-agent harnesses and models in isolated workspaces. Use for repeatable trials, source-reference workflow checks, and distinguishing provider, tool, and asset-quality failures.

Create a procedural 3D asset with Kiln JavaScript, review useful camera views, refine saved source, and export a GLB.

Create, inspect, revise and deliver editable 3D assets through Kiln's connected hosted service, or reopen assets saved in that account. Use for hosted Kiln work; keep an existing local Kiln workspace on its local workflow unless the user chooses hosted storage.

Configure and verify Kiln in an existing project or a new asset workspace for the selected coding agent. Use before authoring when the project has no working kiln_workspace server or needs another agent integration; engine development stays in the engine checkout.