LLM Mart Basic
@llm-mart · Joined Jun 2026
Raise the visual quality of something that already renders: build, screenshot, independent scored critique, fix, against rubrics with hard accessibility, design-token, runtime and asset-licensing gates. Use when asked to make a UI, page, HTML doc, dashboard, game scene or 3D asse
Decide where an instruction belongs and write it there, then sync and lint. Use when asked to add, change or remove a rule, skill, instruction, hook, setting or CLAUDE.md line, to "remember" something that should persist beyond this session, or when a correction should apply to f
Verify a third-party library, asset, model, font, dataset or copied snippet is safe to ship under the project's licensing stance, and record it. Use before adding or upgrading any dependency, before downloading any asset, and before a release.
Write, review or apply a database schema migration without destroying data. Use for any task that creates or modifies a migration file (Alembic, Prisma, Django, Rails, Flyway, raw SQL), and before applying one to a shared environment.
Fence an autonomous or long-running agent loop: the built-in sandbox with network off, or a container with the worktree mounted. Use before any unattended loop, before `execute` autonomy on an unfamiliar repo, and whenever a task pulls untrusted input.
Frame a spike so its result is a decision: the question, the cheapest experiment, a numeric exit criterion, the measured result, the machine it ran on. Use when asked to "spike", "prototype to find out", "de-risk", or "check whether X is feasible", and when writing the spikes sec
Bound what subagents return and what tool output enters the transcript; load when briefing a subagent or reading large output.
Contribute from a fork to a repository you do not own without burning maintainer trust. Use when the working repo has an `upstream` remote, when the user says "open a PR against <someone else's repo>", or before the first commit in any repo the user is a guest in.
Show progress of background Workflow runs: who has returned, who is still working, how much output. Use when the user asks about workflow progress, says "/workflows doesn't work", asks "is the workflow done", "how's the workflow going", "check the workflow", or wants to inspect a
Isolate an agent's work in its own git worktree branched off the default branch, so two agents never land conflicting changes on the shared checkout. Use at the start of any implementation task in a repo where others may also be working, and whenever a repo's instructions say "wo
Pre-pipeline aggregator that scans AI agent cache directories (.claude, .cursor, .antigravity, .openclaw) or any user-specified directory for experimentation logs, extracts insights and numeric results, and formats them as PaperOrchestra-ready inputs (idea.md + experimental_log.m
Step 3 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the literature search strategy from outline.json — discover candidate papers via web search, verify them through Semantic Scholar (Levenshtein > 70 fuzzy title match, temporal cutoff, dedup by paperId), cross-corro
Step 1 of the PaperOrchestra pipeline (arXiv:2604.05018). Convert (idea.md, experimental_log.md, template.tex, conference_guidelines.md) into a strict JSON outline containing a plotting plan, literature search plan (Intro + Related Work), and section-level writing plan with citat
Run the four paper-quality autoraters from PaperOrchestra (arXiv:2604.05018, App. F.3) — Citation F1 (P0/P1 partition + Precision/Recall/F1), Literature Review Quality (6-axis 0-100 with anti-inflation rules), SxS Overall Paper Quality (side-by-side), and SxS Literature Review Qu
Orchestrate the full PaperOrchestra (Song et al., 2026, arXiv:2604.05018) five-agent pipeline to turn unstructured research materials (idea, experimental log, LaTeX template, conference guidelines, optional figures) into a submission-ready LaTeX manuscript and compiled PDF. TRIGG
Reverse-engineer raw materials (Sparse idea, Dense idea, experimental log) from an existing AI research paper to build a benchmark case for evaluating paper-writing pipelines. Replicates the PaperWritingBench dataset construction procedure from arXiv:2604.05018 §3 / App. C. TRIGG
Step 2 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the visualization plan from outline.json — render plots and conceptual diagrams from experimental_log.md and idea.md, optionally refine via VLM critique loop, and produce context-aware captions. Runs in parallel wi
Step 4 of the PaperOrchestra pipeline (arXiv:2604.05018). ONE single multimodal LLM call that drafts the remaining paper sections (Abstract, Methodology, Experiments, Conclusion), extracts numeric values from experimental_log.md into LaTeX booktabs tables, splices the generated f
从游戏客户端(安装包/APK/IPA/EXE 或 dump.cs、lua、usmap、抓包等)反推服务端协议并复现可部署服务端。含阅读路径分派、原理层(primer:三要素/数据包协议/协议表/热更源码)、四阶段路线图(workflow-roadmap:静态分析→建工具+登录链→重定向→补包循环→清单迭代)、11 种反推方法选择器(含内联服务端路线)、接口清单提取器(tools/)、协议规格模板(protocol.spec.yaml)、wire 级定点改写(不等 schema 齐就能跑)、客户端地址来源清查、三轴状态与验收体系、发布运维清单、进度清单(T
Apply the Minimum Sufficient Work (MSW) principle through the MSW Kernel to scope, execute, verify, and stop agent work. State the requested outcome and smallest proof, admit a claim only when deleting it would leave the contract unmet or unproven, do and prove each necessary cla
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.
/group-chat
Group chat
Create a multi-agent group chat with AG2 using configurable speaker selection patterns
/new-a2a-agent
New a2a agent
Scaffold an A2A-compliant AG2 agent with server wiring, card settings, and skill definitions
/new-agent
New agent
Scaffold a new AG2 ConversableAgent with tool functions, system prompt, and LLM config
/new-tool
New tool
Create a tool function for an AG2 agent with type annotations, docstrings, and JSON return contracts
/sequential-workflow
Sequential workflow
Create a sequential multi-agent pipeline where each agent processes and passes results to the next
/workflow-from-spec
Workflow from spec
Design a complete multi-agent workflow from a natural language description, selecting the right orchestration pattern
/act
Act
Follow RED-GREEN-REFACTOR cycle approach for test-driven development
/add-authentication-system
Add authentication system
Implement secure user authentication system
/add-changelog
Add changelog
Generate and maintain project changelog
/add-mutation-testing
Add mutation testing
Setup mutation testing for code quality
/add-package
Add package
Add and configure new project dependencies
/add-performance-monitoring
Add performance monitoring
Setup application performance monitoring
/add-property-based-testing
Add property based testing
Implement property-based testing framework
/add-to-changelog
Add to changelog
Add a new entry to the project's CHANGELOG.md file following Keep a Changelog format
/agent-preflight
Agent preflight
Preflight a repo before AI agents change files
/all-tools
All tools
Display all available development tools
/architecture-review
Architecture review
Review and improve system architecture
/architecture-scenario-explorer
Architecture scenario explorer
Explore architectural decisions through systematic scenario analysis with trade-off evaluation and future-proofing assessment.
/bidirectional-sync
Bidirectional sync
Enable bidirectional GitHub-Linear synchronization
/big-features-interview
Big features interview
Interview to flesh out a plan/spec
Paper trading simulator for Polymarket — built for AI agents. MCP server, live order books, strategy backtesting. Install: npx clawhub install polymarket-paper-…
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4 views 0 likesProfessional cloud architecture diagrams with official AWS, Azure and GCP icons, from Terraform code or a plain JSON graph. MCP server + agent skill.
2 views 0 likesA ready-to-use self-growing desktop AI assistant for long-running tasks, memory, agents, tool reviews, MCP, and high-concurrency workspace automation. / 开箱即用的自我…
5 views 0 likesCollection of templates using the Alchemyst AI Platform for your next big AI app.
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27 views 0 likesThe open source AI research agent.
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