LLM Mart Basic
@llm-mart · Joined Jun 2026
Analyze franchise expansion plans, model new market entry, score site selection candidates, map territory density, assess cannibalization risk, and build multi-year growth scenarios.
Audit ML experiment tracking infrastructure for reproducibility gaps, parameter logging completeness, metric capture, artifact management, and pipeline orchestration. Covers MLflow, Weights and Biases, DVC, Sacred, Neptune, Hydra configs, model registries, and produces a reproduc
Optimize mining extraction operations by analyzing ore grade control, processing plant throughput, metallurgical recovery rates, energy consumption, and water balance.
Audit commercial building energy performance including HVAC optimization, ENERGY STAR scoring, utility cost analysis, demand response readiness, and sustainability compliance.
Analyze fleet maintenance programs for preventive maintenance scheduling effectiveness, parts inventory forecasting, vehicle downtime minimization, total cost of ownership modeling, and telematics integration.
Analyze fleet safety programs including driver behavior scoring, accident trend analysis, CSA BASIC score monitoring, DOT audit readiness, Hours of Service compliance, and drug and alcohol testing programs.
Manage the full Freedom of Information Act (FOIA) and state public records request lifecycle — intake form generation, agency-specific portal routing (FOIA.gov, FBI eFOIA, USCIS, FOIAonline successor portals).
Analyze food supply chain systems for waste reduction opportunities including shelf life prediction models, FIFO and FEFO inventory rotation enforcement, demand forecasting accuracy and bias, donation logistics workflows, cold chain temperature monitoring, and sustainability repo
Benchmark franchise locations by comparing top and bottom quartile performance across revenue, profitability, and operational scores.
Analyze franchise inventory management for par level optimization, waste tracking and root cause analysis, and theoretical vs. actual usage variance.
Analyze fraud detection systems including rule engines, ML scoring models, real-time transaction monitoring, alert triage workflows, false positive management, SAR/CTR regulatory reporting, adversarial robustness testing, and adaptive retraining pipelines for payment fraud, accou
Analyze fleet fuel optimization systems including MPG consumption analytics, eco-driving behavior scoring, route fuel cost modeling, idling detection and anti-idle programs, IFTA tax compliance reporting, alternative fuel transition planning, EV charging infrastructure readiness,
Analyze university and research institution funding allocation systems including RCM revenue attribution, performance-based budgeting, faculty startup package management, F&A indirect cost recovery distribution, equipment sharing and core facility recharge rates.
Analyze game AI systems including behavior trees, finite state machines, GOAP planning, utility AI scoring, A-star and NavMesh pathfinding, steering and flocking behaviors, perception and awareness models, dynamic difficulty adjustment, NPC dialogue trees and scheduling, boss AI
Analyze game design documents and implementations for core gameplay loop clarity and depth, XP leveling curves and unlock pacing, difficulty curve spikes and plateaus, skill tree viability, player motivation via Self-Determination Theory.
Analyze in-game economy systems including soft and hard currency source-sink balance, inflation projection modeling, loot table drop rate fairness and pity system evaluation, gacha probability disclosure, player marketplace health and price manipulation risks.
Analyze game monetization implementations including IAP purchase flow and server-side receipt validation, ad mediation waterfall and rewarded video placement, subscription lifecycle and grace period handling, battle pass XP progression.
Analyze game code for performance bottlenecks including draw call batching and overdraw, shader complexity and LOD strategy, per-frame GC allocation pressure, object pooling gaps, physics timestep and collision matrix tuning, spatial partitioning for entity queries.
Whole-codebase analysis powered by Gemini 2.5 Pro's 2M token context window. Triggers: bounded per-module analysis misses inter-module patterns or when you need a full-graph view before a major refactor.
Generative Engine Optimization (GEO) / Answer Engine Optimization (AEO) — make a site citable by ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews. Triggers: "GEO", "generative engine optimization", "AEO", "answer engine optimization", "AI search optimization".
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.
/standup
Standup
Daily standup: all 8 departments report on the current project in parallel
/analyze-misfires
analyze-misfires
Identify skills injected where not needed, propose regex and description tightening
/announce
announce
Draft X/Twitter announcement post (or thread) for the latest plugin release
/audit-plugin
audit-plugin
Deep quality audit of all skills, agents, and commands for inconsistencies, gaps, duplication, and token waste
/diagnose-negatives
diagnose-negatives
Analyze negative-signal sessions for a skill, identify failure patterns, propose and apply fixes
/eval-skills
eval-skills
Eval all skills with sufficient data, rank by procedure-following score, identify candidates for optimization
/evolve-skill
evolve-skill
Propose a skill revision and compare fresh executions under a frozen rubric
/prune-sync-log
prune-sync-log
Prune stale entries from the whetstone sync decision log
/release
release
Bump version, commit, push, mirror to ai-skills, and update local plugin
/skillopt
skillopt
Run the SkillOpt process-skill optimizer (offline, local). Default prints the exact bare-terminal command (safe); --run executes it in-session (hardened + checkpointed).
/sync-from-repos
sync-from-repos
Analyze reference repos and recommend skill/agent/command improvements based on cross-repo patterns
/triage-prs
triage-prs
Triage all open PRs with parallel agents, label, group, and review one-by-one
/write-skill
write-skill
Author a new skill from scratch with paired trigger fixtures and full validation. Use when adding a skill that has no upstream skills.sh source (discipline, meta, or internal-pattern skills).
/ia-adr
ia-adr
Create Architecture Decision Records with format selection and lifecycle management
/ia-agent-native-audit
ia-agent-native-audit
Score each of the 5 agent-native principles (parity, granularity, composability, emergent capability, improvement-over-time) against a codebase and report gaps
/ia-brainstorm
ia-brainstorm
Explore requirements and approaches through collaborative dialogue before planning implementation
/ia-changelog
ia-changelog
Create engaging changelogs for recent merges to main branch
/ia-deepen-plan
ia-deepen-plan
Expand each section of a plan via parallel research agents that add framework specifics, library conventions, and concrete implementation steps
/ia-document-release
ia-document-release
Post-ship documentation sync. Reads all project docs, cross-references the diff, updates README/ARCHITECTURE/CONTRIBUTING/CLAUDE.md to match what shipped, polishes CHANGELOG voice, and optionally bumps the version.
/ia-feature-video
ia-feature-video
Record a video walkthrough of a feature and add it to the PR description
Make any song you can imagine
39 views 0 likesLeading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars
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34 views 0 likesGeneral-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…
20 views 0 likesAutonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.
20 views 0 likesTSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目
15 views 0 likesCurated, verified Agent Skills powered by ModelStudio.
18 views 0 likesRun Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…
17 views 0 likespi had nothing (nothing), so I made something (something) — sorry mariozechner-senpai, I went ahead and lovingly soiled your pure pi for you. opinionated fork o…
14 views 0 likesA persistent workspace for development work that self-improves and continues beyond one session.
33 views 0 likesOpen-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.
20 views 0 likes📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…
28 views 0 likesDeterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.
31 views 0 likesDeterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…
20 views 0 likesNative Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…
32 views 0 likesAgent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.
15 views 0 likesGit for agent memory. Branches, diffs, PRs, and rollback for what your agents know.
34 views 0 likesMulti-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…
16 views 0 likesProduction-grade MCP server for MikroTik RouterOS with secure AI-native network automation.
29 views 0 likes