LLM Mart Basic
@llm-mart · Joined Jun 2026
Use when a user wants to record why one world won over the others, as a decision-diary entry. Not for remote, credential, publish, deploy, or irreversible changes.
Use when a current decision needs pressure-testing until the rationale is clear to a skeptic. Not for tasks requiring source or remote-system changes.
Use when an imperative program needs pre-conditions, post-conditions, and loop invariants proved automatically by SMT in Dafny or Why3, short of a tactic prover.
Use when asked to deduplicate a skill tree, fold overlapping skills, or cut the skill count: analyze, gate per family, then fold. Not for prompt-doctrine cascades: use cascade-dedup.
Use when the user asks to research a topic and produce a thorough sourced report. Not for remote, credential, publish, deploy, or irreversible changes.
Use when the user wants the finished-system contract for a piece of work: behavior, protocols, allowed, forbidden, and impossible states with a state-space proof. Not for runtime verification.
Turns a song (audio file + lyrics) into a hand-painted watercolour music video (MP4) in the style of PDoomVideo, following its pipeline end to end: measure the beat grid and time the lyrics, scaffold the p5.brush engine, design the story, characters and sets from the lyrics, pain
Paints one chapter (src/ch/cNN_name.js) of a paint-mv music video in the PDoomVideo style: watercolour-and-ink frames drawn with p5.brush, the song's own characters (designed from its lyrics) acting on the beat, camera moves and motivated transitions, each frame a pure function o
Checks and renders a paint-mv music video with its render.mjs (Puppeteer drives studio.html in headless Chrome, ffmpeg encodes): contact sheets and stills for visual checks, short clips with audio, the full parallel and resumable frame render, re-rendering a fixed time range, enc
Writes STORYBOARD.md for a paint-mv music video the way the PDoomVideo storyboard was written, with everything specific taken from the song's own lyrics: a concept with a twist that bookends the video, a cast designed from who and what the lyrics sing about, one set per chapter d
Split a bloated AGENTS.md / CLAUDE.md / README into a small always-loaded kernel plus task-routed wiki topics, loaded on demand by a zero-dependency script (`scripts/ai-context.py list|<topic>|check`) with byte budgets, so agents stop burning their context window on docs unrelate
Create polished, validated architecture, workflow, sequence, data-flow, and lifecycle/state diagrams as explorable standalone HTML with inline SVG, dark/light themes, optional trace motion, and PNG/JPEG/WebP/SVG/WebM export. Accept plain-language requirements or pasted Mermaid fl
Control Herdr, a terminal multiplexer for coding agents. Use only when the user explicitly mentions Herdr or asks to use Herdr to inspect or control panes, tabs, workspaces, commands, or another agent. Do not use merely because a task could benefit from a background terminal, del
Coordinate supervised Orca workers: threaded messages, blocking ask/reply, task dispatch, worker_done/escalation waits, task DAGs, decision gates, coordinator loops, and decomposing work across agents. Use `orca-cli` for full ownership handoffs — "hand off", "handoff", "handover"
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a websit
Full-cycle feature discovery, evaluation, and prioritization. Builds a persistent knowledge base at .feature-radar/ and runs a 6-phase workflow to recommend what to build next. Modes: full (all phases), quick (scan only), evaluate (prioritize), #N (deep-dive one). MUST use this s
Archive a completed, rejected, or covered feature into .feature-radar/archive/ with mandatory learning extraction. MUST use this skill whenever a feature reaches a terminal state — done, rejected, covered, deferred, or N/A — including casual mentions like "we shipped X". The skil
Extract reusable patterns, architectural decisions, and pitfalls from completed work into .feature-radar/specs/. Captures the "why" behind choices so future sessions build on past experience. MUST use this skill when the user reflects on what worked or didn't, wants to record a d
Record external observations, ecosystem trends, and creative inspiration into .feature-radar/references/. MUST use this skill when the user mentions something interesting from outside their project — other tools, articles, approaches, or trends — even casually ("I saw a cool thin
Discover new feature opportunities from creative brainstorming, user feedback, ecosystem trends, and cross-project research. Writes results to .feature-radar/opportunities/. MUST use this skill when the user wants to GENERATE new ideas — not evaluate existing ones — including cas
Fourteen posts of being wrong in production, compressed to checkboxes
Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds
Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.
Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.
A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.
A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.
None of the safety came from the model. It came from six boring habits.
Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.
Six hours in, one step left, everything green, and the incident that didn't happen
CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.
Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it
An API request routing a model's tool call through an approval gate to a remote MCP server
31 config keys, two audits, and why the first one was wrong in both directions
The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.
Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.
Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.
"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks
stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.
The most important rule wasn't about what I could change. It was about what I was allowed to display.
Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.
/inventory
Inventory
One-screen inventory of skills, agents, commands, MCP servers, and hooks counts.
/memory
Memory
List the file-based memory store grouped by project (auto-memory) plus the CLAUDE.md files.
/budget
Budget
Show current Claude Code spend versus a budget number
/forecast
Forecast
Quick month-end spend projection from the daily trend
/overspend
Overspend
List the most expensive sessions pushing your spend up
/open-dashboard
Open dashboard
Print the Agent Monitor dashboard URL and how to start/open it
/ping
Ping
Check Agent Monitor reachability and print UP/DOWN with latency
/status
Status
One-line Agent Monitor health + counts summary from /api/stats
/doctor
Doctor
Quick connectivity + health probe of the Agent Monitor dashboard.
/export
Export
Export Agent Monitor data (sessions/events/analytics/costs/all) as json/csv/md.
/tail-events
Tail events
Show the latest N ingested events with timestamp, event_type, and tool_name.
/anomalies
Anomalies
List current cost and token outlier sessions via z-score
/compare
Compare
Compare two sessions side-by-side with cost and workflow deltas
/insights
Insights
Surface the top 3 data-backed insights about your Claude Code usage right now
/integrations
Integrations
Read-only inventory of CCAM alerts, webhook targets, and remote sources
/platform-status
Platform status
CCAM platform status across hooks, config, updates, and MCP prerequisites
/focus-report
Focus report
One-screen focus snapshot — avg turn duration, thinking-block usage, and longest sessions.
/standup
Standup
Quick daily standup from today's Claude Code sessions — grouped by project, with cost and errors.
/whats-next
Whats next
Suggest the next action from your most recent in-progress sessions and recent errors.
/errors
Errors
List the most recent APIError events with their session and a summary
An open-source, privacy-first, self-hosted knowledge workspace where humans and AI agents work together 开源、隐私优先、自托管的知识工作空间,让人与智能体在此协作
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