LLM Mart Basic
@llm-mart · Joined Jun 2026
Easter egg command - about oh-my-opencode. Triggers: omomomo, about, easter egg.
QA opencode itself, per case: verify the CLI/terminal (opencode run, db, serve, export), prove a specific plugin hook/action/event fired via the SSE event stream, smoke-test the TUI under tmux, and investigate sessions in opencode's SQLite DB by id, title/name, or message text. S
Nuclear-grade 16-agent pre-publish release gate. Runs /get-unpublished-changes to detect all changes since last npm release, spawns up to 10 ultrabrain agents for deep per-change analysis, invokes /review-work (5 agents) for holistic review, and 1 oracle for overall release synth
Publish oh-my-opencode to npm by triggering the GitHub Actions publish workflow and verifying its artifacts. Ship-only: never runs pre-publish-review or re-reviews merged code unless the user explicitly asks. Argument: <patch|minor|major|explicit-semver>. Triggers: publish, relea
Remove unused code from this project with ultrawork mode, LSP-verified safety, atomic commits. Triggers: remove dead code, dead code, cleanup, remove unused.
Team Mode security research skill. Orchestrates 3 vulnerability hunters and 2 PoC engineers to audit a codebase in parallel, prove exploitability, classify root causes, and calibrate severity by actual exploitability. Use for security review, vulnerability research, exploitabilit
QA the omo Senpi adapter (packages/omo-senpi, packages/senpi-task) against the REAL senpi binary in strict isolation, and write every artifact to the one canonical evidence path .omo/evidence/omo-senpi-adapter/<slug>/. The live drivers under packages/omo-senpi/scripts/qa/ create
Thorough, file-cited technical debt audit across 9 dimensions using AST-grep (tree-sitter), grep, language-native tooling, and optionally CodeGraph knowledge graph. Produces TECH_DEBT_AUDIT.md with severity, effort estimates, and prioritized fixes. Use when asked for codebase hea
Full PR lifecycle in a fresh task-owned git worktree: implement via the ulw-loop skill with mandatory evidence-bound manual QA → reviewer-readable English PR → verification loop (CI + Cubic, where Cubic is skipped only when its quota is exhausted) → merge by default → worktree cl
Read-only GitHub triage for issues AND PRs. 1 item = 1 background task (category: quick). Analyzes all open items and writes evidence-backed reports to /tmp/{datetime}/. Every claim requires a GitHub permalink as proof. NEVER takes any action on GitHub - no comments, no merges, n
Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insig
Nuclear-grade 16-agent pre-publish release gate. Runs /get-unpublished-changes to detect all changes since last npm release, spawns up to 10 ultrabrain agents for deep per-change analysis, invokes /review-work (5 agents) for holistic review, and 1 oracle for overall release synth
Full PR lifecycle in a fresh task-owned git worktree: implement via the ulw-loop skill with mandatory evidence-bound manual QA → reviewer-readable English PR → verification loop (CI + Cubic, where Cubic is skipped only when its quota is exhausted) → merge by default → worktree cl
Store a dag definition once and re-run it in one or two lines, instead of pasting the full definition JSON into every eval cell. MUST USE whenever the user wants to save a DAG for reuse, run a previously saved/named DAG, schedule the same graph repeatedly (nightly/weekly audits,
Explains any senpi tip in depth - startup tips, working tips, and any Tip: line shown in the TUI (including the Fable-5-refusal fallback tip). Use when the user asks about a Tip: line, says give-me-tips, asks what a tip means, how a tipped feature works, or which tips they can se
Adversarial multi-agent planning skill for omo-senpi. Self-orchestrates a 5-member hostile team (categories unspecified-low, unspecified-high, deep, ultrabrain, artistry) via the native lead team tools for ruthless cross-critique debate, distills only the insights that survive th
Run a dependency graph of child agents in one call with the native dag tool. Use when the user asks for mass-ulw, a DAG of tasks, fan-out/fan-in work, or multi-agent execution where some tasks must wait on others.
Onboarding tour for first-time omo users
Binding ultrawork mode directive for omo-senpi. When a prompt contains ultrawork or ulw, the omo input hook injects the full directive as a hidden custom message (customType omo-ultrawork:directive, display false) ahead of the user's text, which is left untouched; a prompt queued
Goal-like loop that uses ultrawork mode to decompose work into systematic, evidence-bound steps.
An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.
Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.
Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.
Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.
Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.
Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.
A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.
Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.
Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.
AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.
AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.
A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.
One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.
"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.
A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.
The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.
Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.
Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.
A green PR, a controller reporting success, and not one line of the new code running
/lineage-discovery
Lineage discovery
Discover testnet↔mainnet subnet lineage from repo configs and open a PR for review (pass --dry-run to report only)
/capture
capture
Triage raw inbox notes into reviewed repository destinations without deleting their sources.
/clean-ai-writing
clean-ai-writing
Audit and rewrite content to remove AI writing patterns
/content-shipped
content-shipped
Log a completed piece of content to content/log.md after the user confirms it was published.
/dream-apply
dream-apply
Validate a dream artifact, review each proposal, and apply only individually accepted changes.
/dream
dream
Run a curator pass against the validated memory directory and produce a proposal artifact.
/end
end
End a session — log what happened, update state and the decision log, propose memory updates, and check for uncommitted or unpushed work
/find-context
find-context
Find relevant context files by topic. Use when you need to load files for a topic without a slash command, or when a task spans multiple domains.
/migrate-gemini
migrate-gemini
Inventory and migrate selected Gemini CLI workflows with dry-run review and parity checks.
/mine-gemini-workflows
mine-gemini-workflows
Find repeated workflows in selected Gemini CLI sessions and draft portable skills after review.
/reconcile
reconcile
Scan multi-session drift and offer individually reviewed fixes only after explicit approval.
/recover
recover
Scan orphaned worktrees and stale branches, then offer explicit approval-gated cleanup.
/setup
setup
Guided onboarding or import for durable workspace context
/start
start
Start a session — load state files, flag staleness, and give a briefing on current priorities, deadlines, and blockers
/today
today
Create a morning heartbeat from repository state and update the local heartbeat log.
/update
update
Mid-session checkpoint — append progress to today's session log and update state files if a priority shifted, without ending the session
/distribution-audit
distribution-audit
Maintainer-only. Find every file that would newly ship to adopters, classify each one against the written distribution-boundary categories, default to withhold on no clean match, and ask the maintainer only where the taxonomy does not settle it. Drives the release CLI, which refuses to produce a manifest until every shipping file has an answer.
/gaia-audit
gaia-audit
Audit memory, wiki, and auto-loaded files for duplication, conflicting instructions, and stale content. The default path researches, then asks you a single Apply / Discuss / Decline question; on Apply it applies the report, files any out-of-scope problem as a tech-debt issue, then commits, opens a PR, and merges it on a main-branch run like /update-deps. Pass --apply to re-run the apply-and-publish stage against the most recent report.
/gaia-debt
gaia-debt
Fix the tech-debt backlog, a single issue or a recommended related batch, highest severity then oldest first, on a fresh isolated branch through the audit gate, closing the issue(s) on merge. Pass `list` to see the ordered backlog, `why <issue-number>` to explain the recommendation, or a bare `<issue-number>` to fix that issue directly.
/gaia-fitness
gaia-fitness
Health-check and auto-heal this project's Claude integration, triage, heal, verify, and report an F-to-A+ grade.
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