LLM Mart Basic
@llm-mart · Joined Jun 2026
Read a detached Codex bridge job's current state.
Ask Claude Code a read-only question from Codex through the sandbox-external bridge.
Ask Claude Code to implement one bounded write-capable change through the sandbox-external bridge.
Request a read-only adversarial review from Claude Code through the sandbox-external bridge.
Configure, authenticate, repair, and verify the Codex to Claude Code Bridge; safe stages run by default and sensitive stages require separate approval.
Safely manage Codex Rig role-agent shims: doctor, status, install, or remove; one action only.
Audit Codex configuration, workflow, and prompt-efficiency (instruction cost, value-per-token) drift; emit ranked gaps and measurable gates.
Calibrate skills/role cards for leaks/gaps with recall, precision, and confidence-accuracy checks.
Apply selected review fixes; bare PR targets use current online items, while PR +review adds the latest matching artifact.
Close PRs at an evidence gate or review local diffs/PRs with specialists and JSON artifacts.
Implement changes with a linear plan-build-verify workflow and measurable quality gates.
Investigate code debugging and root-cause narrowing; use measurable gates before fixes.
Build/extend grounded Kaggle Jupytext notebooks for training, EDA, inference, or resume workflows, grounding schema and submission format through the authenticated kaggle CLI.
Optimize a measurable metric with bounded iterations, guardrails, and regression gates.
Assess SemVer release readiness with gates/artifacts; never tag, publish, upload, or force-push.
Research docs, papers, or state of the art; provide source-backed recommendations and caveats.
Dry-run active plugin cache drift; refresh/reinstall only with approval; keep shims separate.
Adversarial review — drills to bedrock, treats claims as unproven until evidence. NOT for: plan design (foundry:solution-architect), test coverage (foundry:qa-specialist), config formatting (foundry:curator). TRIGGER: "challenge this", "devil's advocate", "poke holes in". SKIP: w
Content specialist — blog posts, slide decks, social threads, talk abstracts. Reads approved outline, applies four-beat arc. NOT for in-code docs/README/FAQs (foundry:doc-scribe), release notes (oss:release). TRIGGER: "write a blog post", "create slides", "draft a thread". SKIP:
Config quality reviewer. Scope: agents/skills/rules (*.md) — verbosity, duplication, cross-refs, roster overlap; applies fixes. NOT for hooks (foundry:sw-engineer), ADRs (foundry:solution-architect), adversarial challenge (foundry:challenger). TRIGGER: "audit this agent", "review
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.
/smart-fix
Smart fix
Intelligent issue resolution with multi-agent debugging, root cause analysis, and verified fix implementation
/typescript-scaffold
Typescript scaffold
Scaffold a TypeScript project (Next.js, React with Vite, Node.js API, or library) with pnpm, testing, and dev tooling
/ai-assistant
Ai assistant
Build AI assistant application with NLU, dialog management, and integrations
/langchain-agent
Langchain agent
Create LangGraph-based agent with modern patterns
/prompt-optimize
Prompt optimize
Optimize prompts for production with CoT, few-shot, and constitutional AI patterns
/finetune
Finetune
Run the eval-gated fine-tuning lifecycle end to end — eval harness, method selection, data, environment, training, checkpoint gate, export
/promote-checkpoint
Promote checkpoint
Re-gate an existing fine-tuned checkpoint against the current eval harness and export it on PROMOTE
/ml-pipeline
Ml pipeline
Orchestrate specialized agents to build a production ML pipeline from data analysis through training, deployment, and monitoring
/find
Find
Quick gallery search. Use when user runs /meigen-ai-design:find with keywords to browse inspiration.
/gen
Gen
Quick image generation. Use when user runs /meigen-ai-design:gen with a prompt. Skips intent assessment, generates directly.
/multi-platform
Multi platform
Orchestrate cross-platform feature development across web, mobile, and desktop with API-first architecture
/monitor-setup
Monitor setup
Set up monitoring and observability with Prometheus metrics, Grafana dashboards, distributed tracing, log aggregation, and alerting
/slo-implement
Slo implement
Implement SLOs with SLI selection, error budgets, burn-rate alerting, dashboards, and reporting
/ai-review
Ai review
Run an AI-assisted code review that combines static analysis tools with AI review of security, performance, and architecture
/multi-agent-review
Multi agent review
Coordinate specialized review agents in parallel or in sequence and synthesize their findings into one code review
/certify
Certify
Full quality certification with badge
/compare
Compare
Compare two skills head-to-head
/eval
Eval
Evaluate a plugin or skill for quality
/audit-chain
Audit chain
Verify every receipt in ./receipts/receipts.jsonl against the signer's public key. Detects tampered or malformed receipts across the audit trail.
/verify-receipt
Verify receipt
Verify a single Ed25519-signed receipt file against the signer's public key. Returns exit 0 if valid, 1 if tampered, 2 if malformed or the key is missing.
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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