LLM Mart Basic
@llm-mart · Joined Jun 2026
Official Feature-Sliced Design (FSD) v2.1 skill for applying the methodology to frontend projects. Use when the task involves organizing project structure with FSD layers, deciding where code belongs, placing static assets (images, icons, fonts, PDFs), grouping closely related sl
Compare two versions of an LLM-directed document - an original (teacher) and a candidate (student) - across a transfer set and return a per-case behavioural-equivalence verdict plus an efficiency signal. A transform-agnostic library capability other skills compose to gate a trans
Assess a codebase's readiness for AI agent contributors using the layered contract model, and generate a complexity hotspot SVG treemap (size = LOC, hue = cyclomatic complexity, saturation = recent git churn). TRIGGER when the user types /assess, asks for an AI-readiness review,
Renders the /assess report from the deterministic run-context.json and the layer scorecard - the scorecard, the verbatim cross-layer findings, lying signals, and the mandatory Top 3 Actions. TRIGGER when the /assess orchestrator reaches the report-writing step; not a standalone u
The /assess end-of-run offers - open a PR with the report, track the Top 3 Actions in the user's issue tracker, freeze the assessment into a CI gate, and file tool feedback. TRIGGER when the /assess orchestrator reaches the end-of-run offers; not a standalone user command.
Detect and remove the telltale signs of AI-generated 'slop' from any written text - articles, reports, emails, essays, bios, marketing copy, documentation, encyclopedia entries, or anything meant to read as if a thoughtful human wrote it. Apply silently as a quality gate before f
Read-only org repo state report. Reuses ghsync's repo discovery (teams union org-repo-list) but, instead of cloning, queries each repo's remote GitHub state - open PRs, CI on the default branch, open security alerts (Dependabot / code-scanning / secret-scanning), and branch prote
Bulk clone and keep in sync every GitHub repo you can access across an org or personal account. For an org it unions the repos reachable through the teams you belong to with the org's repo list (so direct-collaborator and public repos count even with no team membership); for a pe
Structured multi-perspective analysis using Six Thinking Hats with professional lens team members. TRIGGER when the user types /huddle, asks to run a huddle, wants a panel/board/team to analyze a decision, asks for multi-perspective analysis, debate, or red-team/blue-team review,
Run a list of work units to completion with an Agent Team: derive a dependency DAG and hot-file map, spawn one ephemeral teammate per unit (or combined group), drive each PR through pr-review-merge, smart-merge in waves, recover from crashes, and run a retrospective. Source-agnos
Drive a single pull request to merge-ready across all five criteria (sync, CI, inline comments, conversation, threads), then smart-merge it. Source-agnostic library skill invoked by the /tm, /issues, /fix-pr, and /fix-develop commands and by marathon teammates. TRIGGER when a com
Make an LLM-directed document smaller while preserving what it does. Two modes: a local span-level core->pointer pass, and an A/B-validated distill loop that produces the smallest document that behaves the same as the original. Point at core knowledge the model already holds (a c
Phase-1 (S4) of a comic movie — PRODUCE the canonical reusable references the whole spiral conditions on. Per asset it bakes ONE canonical 1:1 white-bg identity ref via the agent mcp__codex__codex sidecar bake (Codex native image_gen — conditioned, never hand-pasted) OR, for a de
Phase-1 (S5) UPSTREAM ref-asset gate — the bounded cross-model adversarial loop that LOCKS one reusable identity-locked asset (character sheet / location plate / prop cutout / text-panel / logo-free symbol) BEFORE it can be composited into any panel. This is NOT the panel_gate (c
Phase 1 ORCHESTRATOR of a movie/comic — turn a fuzzy story idea into the Authored Source of Truth (a schema-valid comic.json + its locked asset library) by driving the detailed author skills in order (intent → style → outline → storyboard → assets → blueprints → prompts → comic.j
Phase-1 comic-author step (post-final eval) — a DOUBLE-BLIND A/B of two FINAL whole comics: our cross-model-audited progressive render (the comic-author + comic-director output) vs a naive single-shot baseline. A single sealed coin-flip hides which is which; two cross-model revie
Phase-1 (S7 of the comic-author suite) — turn ONE locked panel_spec into a deterministic content-SVG blueprint that becomes the bake condition (reference #1 of the agent mcp__codex__codex sidecar bake), by WRITING A PYTHON GENERATOR (never raw SVG in chat — LLMs botch coordinates
The authoring-side DIEGETIC continuity AUDIT — it produces the world-state evidence that comic-cross-layer-gate `--gate continuity` adjudicates against the storyboard's MOTIF STATE TABLE (motif_ledger). It checks each baked panel STRICTLY against the pre-committed table row, then
The ONE parameterized score-fuser for EVERY comic-author authoring gate — `--gate intent|outline|asset|storyboard|blueprint|continuity|p0_proof|compile`. A single fuser (not a per-layer split) prevents drift. It NEVER re-runs a reviewer; it collects the reviewer score-nodes alrea
Phase 2/3 of a movie — bake + cross-model-verify a movie from an authored comic.json. Per frame: render the content-SVG blueprint, bake via the agent mcp__codex__codex sidecar, gate with a 3-reviewer cross-model panel (narrative [currently the codex CLI] ‖ Gemini visual ‖ Codex v
Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.
Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.
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.
/show-ticket
Show ticket
Display comprehensive ticket information including history, actions, and related entities
/sla-dashboard
Sla dashboard
View SLA status across tickets, including approaching breaches and at-risk tickets
/update-ticket
Update ticket
Update fields on an existing HaloPSA ticket including status, priority, and assignment
/create-deal
Create deal
Create a new deal in HubSpot with company association
/log-activity
Log activity
Log a note or create a task on a HubSpot contact, company, or deal
/lookup-company
Lookup company
Find a HubSpot company by name or domain and show associated contacts and deals
/pipeline-summary
Pipeline summary
Summarize the HubSpot deal pipeline - deals per stage, total value, and expected close dates
/search-contacts
Search contacts
Search HubSpot contacts by name, email, or company
/search-deals
Search deals
Search HubSpot deals by name, stage, or company
/find-company
Find company
Find a company in Hudu by name
/get-password
Get password
Retrieve a password from Hudu (with security logging)
/lookup-asset
Lookup asset
Find an asset in Hudu by name, hostname, serial number, or IP address
/search-articles
Search articles
Search Hudu knowledge base articles by keyword or phrase
/agent-inventory
Agent inventory
List and filter Huntress agents across organizations
/billing-report
Billing report
Generate a Huntress billing summary for a period
/incident-triage
Incident triage
Triage open Huntress incidents by severity
/investigate-incident
Investigate incident
Deep dive investigation into a specific Huntress incident with remediations
/org-health
Org health
Organization health check covering agents, incidents, and escalations
/resolve-escalation
Resolve escalation
Review and resolve a Huntress escalation
/compliance-report
Compliance report
Generate an ImmyBot software-compliance scorecard for a tenant or the whole fleet
Make any song you can imagine
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