LLM Mart Basic
@llm-mart · Joined Jun 2026
用户直接运行 cm-test、要求分析当前分支相对主分支的业务影响,或说“测试已有功能”“根据代码生成用例”“用浏览器走查”时使用。无参数分析已提交差异、单测覆盖率与回归重点;明确说“补齐单测”时连续补测并重跑、审查。显式目标保留原模式,不擅自修产品代码。
UI 还原工程师 Skill,把已确认的设计基准像素级还原为生产代码(token 先行、原子顺序、按交付形态量化验收:Web 用 BackstopJS、App 用 Maestro+模拟器截图);有基准才出场,不做业务逻辑
项目代码库上下文管理。通读项目生成参考文档(scan),或加载文档辅助开发(dev)。
Darwin Skill 2.0 (达尔文.skill 2.0): autonomous skill optimizer, v2.0 integrates Microsoft Research SkillLens (arXiv 2605.23899) 9-dim rubric + SkillOpt (arXiv 2605.23904) validation-gated design + human-in-the-loop checkpoints. Evaluates SKILL.md files using a 9-dimension rubric (s
将产品讨论、问题研究、学术研究、根因假设、测试设计或对抗审查交给外部高能力模型,并由本地主执行者核验、裁决和留存证据;不修改代码或代替正式测试。
Extract a production-ready brand-lock.md from a brand's existing assets. Point it at a website URL, a brand book PDF, screenshots, or a written description and it produces the nine-section brand-lock the rest of shotkit consumes, with a confidence and source noted for every value
Turn a creative brief into a production-grade storyboard with shot specs, timing, on-screen text, and per-shot rationale. Use when the user describes a video brief, plans a video, references shots or beats, scripts a social video, or hands over a creative concept to break into sc
Render a structured storyboard (storyboard.md, shots.json, text-overlays.json, brand-lock.snapshot.md) into a single-file HTML preview that is shareable, printable, and offline. Use when the user wants to share a storyboard, export for review, hand off to an editor, or print a ha
Critique a generated image against its source storyboard shot and prompt, producing revision notes. Use when the user has generated an image and wants feedback before committing. Triggers on "does this match the brief", "review this render", "is this on-brand", "what should I cha
Generate model-specific prompts from shots.json. Outputs copy-paste-ready prompts for stills (Midjourney, Flux, Ideogram, GPT Image, Nano Banana, Seedream) and motion video (Kling, Veo, Seedance, Hailuo). Also runs a revision mode that reads a critique.json and re-emits prompts f
Use aai-cli to inspect and manage Confluence spaces, pages, comments, attachments, and page moves.
Use aai-cli to create local spreadsheet files, manage their sheet tabs, and read, update, or clear cell values — Excel (.xlsx/.xlsm) and delimited text (.csv/.tsv).
Use aai-cli to inspect and manage GitHub repositories, issues, pull requests, reviews, branches, source files, and Actions logs.
Use aai-cli to find Google Drive files and folders, read their metadata, download their content (including Google-native Docs, Sheets, and Slides), check who a file is shared with, and upload a local file back to Drive.
Use aai-cli to inspect HubSpot CRM records, files, events, conversations, visitor identification, and custom channels.
Use aai-cli to search and manage Jira issues, Jira Product Discovery ideas, projects, boards, sprints, comments, and attachments.
Work with Microsoft 365 through aai-cli by choosing the right Microsoft service and resource model, then using durable Graph credentials for Outlook, OneDrive, SharePoint, Teams, Excel, To Do, and Planner workflows.
Use aai-cli to read OpenPanel projects, raw event exports, aggregated insights (metrics, pages, referrers, devices, geo), and user profiles.
Use aai-cli to manage Pipedrive leads, persons, organizations, deals, labels, activities, notes, deal flow/stage history, and synced mailbox data.
Use aai-cli to query PostHog product analytics, read projects, execute HogQL event queries, list saved insights, inspect persons and cohorts, read team dashboards, and view release annotations.
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.
A green PR, a controller reporting success, and not one line of the new code running
/doc-api
Doc api
Generate API documentation from code
/docs
Docs
Update or generate YAML documentation for SQL models with proper descriptions and tests
/e2e-setup
E2e setup
Configure end-to-end testing suite
/estimate-assistant
Estimate assistant
Generate accurate project time estimates
/explain-code
Explain code
Analyze and explain code functionality
/explain-issue-fix
Explain issue fix
Explain how tasks in an issue were implemented with detailed breakdown
/find
Find
Search and locate tasks across all orchestrations using various criteria.
/five
Five
Apply the Five Whys root cause analysis technique to systematically investigate issues
/fix-github-issue
Fix github issue
Analyze and fix a GitHub issue with comprehensive testing and verification
/fix-issue
Fix issue
Fix a specific issue or problem with the given identifier or description
/fix-pr
Fix pr
Fetch unresolved comments for current branch's PR and fix them
/future-scenario-generator
Future scenario generator
Generate and analyze future scenarios with plausibility scoring, trend integration, and uncertainty quantification.
/generate-api-documentation
Generate api documentation
Auto-generate API reference documentation
/generate-linear-worklog
Generate linear worklog
You are tasked with generating a technical work log comment for a Linear issue based on recent git commits.
/generate-test-cases
Generate test cases
Generate comprehensive test cases automatically
/generate-tests
Generate tests
Generate comprehensive test suite for $ARGUMENTS following project testing conventions and best practices.
/git-status
Git status
Show detailed git repository status
/hotfix-deploy
Hotfix deploy
Deploy critical hotfixes quickly
/husky
Husky
Verify repository is in working state by running CI checks and fixing issues
/implement-caching-strategy
Implement caching strategy
Design and implement caching solutions
Make any song you can imagine
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