LLM Mart Basic
@llm-mart · Joined Jun 2026
端到端测试(生成或执行 E2E 用例)
全自动 PDLC 新功能开发(串联 PRD→设计→TDD→实现→评审→发布)
全自动 Bug 修复(定位→复现→修复→测试→文档)
国际化(i18n)
按设计文档和已有测试用例实现代码(带前置守卫、自检、handoff)
代码质量检查与自动修复
打印循环下一步应执行的命令(机器可读,供 loop 驱动)
收敛循环引擎(自动推进 tdd→implement→review 到 review_done 或 blocked)
新人引导 / 自动化生成用户手册
性能优化
创建 PRD 文档(自动化生成 + 自检 + handoff)
质量闸门——跑真实 check、对照质量目标、出可核对报告,由人签字放行
代码重构(保持外部行为不变,改善内部结构)
管理 feature 关系链(set/query/impact/orphans/rebuild/validate)
迭代复盘——读状态机历史出趋势报告
安全审计
交互式配置 PDLC(当前:状态栏 statusline 的启用/停用/展示项)
发布工作流(收评审通过的功能 → 跑测试 → bump VERSION → 更 CHANGELOG → tag)
管理 00_standards 规范型 surface 产物(add/edit/archive/index)
查看项目 PDLC 状态总览(读 docs/.pdlc-state/ 输出进度)
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.
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.
/log-provenance
log-provenance
Log derived files and trace provenance back to ENCODE source data
/manage-credentials
manage-credentials
Store, check, or clear ENCODE API credentials for restricted data
/quality-check
quality-check
Assess ENCODE experiment quality using audit counts and replicate counts
/search-encode
search-encode
Search ENCODE experiments by assay, organ, biosample, or target
/track-experiments
track-experiments
Track ENCODE experiments locally with publications and provenance
/browse-files
browse-files
List, search, and inspect ENCODE files by format, type, and assembly
/cite-encode
cite-encode
Generate ENCODE citations for publications, grants, and presentations
/compare-experiments
compare-experiments
Check if two ENCODE experiments are compatible for combined analysis
/cross-reference
cross-reference
Cross-reference ENCODE data with PubMed, GEO, ClinicalTrials, and bioRxiv
/download-encode
download-encode
Download ENCODE files (BED, FASTQ, BAM, bigWig) with MD5 verification
/log-provenance
log-provenance
Log derived files and trace provenance back to ENCODE source data
/manage-credentials
manage-credentials
Store, check, or clear ENCODE API credentials for restricted data
/quality-check
quality-check
Assess ENCODE experiment quality using audit counts and replicate counts
/search-encode
search-encode
Search ENCODE experiments by assay, organ, biosample, or target
/track-experiments
track-experiments
Track ENCODE experiments locally with publications and provenance
/document
Document
Record the present state by mode — decision (ADR, RFC, rule), code (spec, doc, guide, scenario), or research (a ready report or one external material); a gate picks the document type.
/init
Init
First-time Archcore setup — wire host configs, measure the authored context, compose the full first-day seed in one preview, and create it on one confirm; import converts CLAUDE.md, AGENTS.md, rule files, ADRs, and docs into native documents; refresh adds new facts or drills into one domain.
/plan
Plan
Plan a feature or initiative through a computed route — a small fix exits with no documents, one capability gets a spec and a plan, a large initiative gets an umbrella PRD with one spec per capability; start with sdd, sources (market research), iso (regulated work), or research (technical investigation) to run that path directly.
/review
Review
Review branch changes against Archcore docs, or report project health; drift runs staleness detection, deep a full documentation audit, closeout closes a finished feature, experience captures a repeated pattern.
/cite-check
cite-check
Verify that citations actually exist and that the claims they support are faithful to the cited source. Runs deterministic existence checks (Crossref / OpenAlex / Semantic Scholar / arXiv) plus a claim-faithfulness pass via the alterlab-citation-verifier skill.
LLM-powered toolkit for skill analysis, AI interviews, resume scoring, and job structuring. Automates professional skill taxonomy and interview processes with a…
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