LLM Mart Basic

ACCESS-GATED beta. Deepline Monitors are provider event feeds (job posts, email replies, funding, intent) that stream into your warehouse and trigger plays. Only use if you have monitor access: run `deepline monitors status` first; if it reports no access, do NOT use this recipe

Use for Deepline GTM work that searches, enriches, scores, collects signals, or automates a workflow: find companies or people, enrich a CSV, find emails or LinkedIn, compare providers, build a waterfall, create a webhook or cron, or write a Play. For live information work, run a

Use this skill when a human needs to review a Deepline Play result and hand feedback, labels, or approval back to the agent for revision, evaluation, comparison, or bounded iteration. Triggers on “put this run in a Sheet,” “review these results,” “read my feedback,” “make this a

Use when the user wants a last30days-style pre-research pass in Deepline: discover the critical public, private, CRM, workflow, social, and web data sources for a research/enrichment job; compare provider coverage; estimate Deepline credit cost; recommend the source plan before b

Run a quick Deepline demo recipe to show the user how Deepline works.

Use when finding real role-holders at known company domains from an ICP, especially prompts like 'find all job titles at these companies', 'find qualified titles', 'find RevOps or marketing-ops buyers', or when exact title discovery should precede paid people search.

Resolve LinkedIn profile URLs from name + company with strict identity validation to avoid false positives.

Discover niche first-party signals that differentiate Closed Won vs Closed Lost accounts for ICP analysis. Use when the user provides won/lost customer domain lists and wants differential signals (website content, job listings, tech stack, maturity markers) to build account scori

Find companies backed by a specific investor or accelerator, then find contacts and build personalized outbound.

Create a concrete Deepline execution plan before running GTM work. Use when the task needs routing, sequencing, provider selection, approval gating, or a plan that maps cleanly onto the skill docs.

Build company or contact seed lists for GTM workflows. Use for discovery, TAM building, portfolio prospecting, known-company contact finding, and provider-driven list construction before enrichment.

Full-sweep quality audit of .claude/ config — cross-references, permissions, inventory drift, model tiers, docs freshness. Scope tokens select what to audit; --upgrade applies docs-sourced improvements; --adversarial runs foundry:challenger + Codex adversarial review; --efficienc

Iterative brainstorming skill for turning fuzzy ideas into approved tree documents. Diverges into branches, deepens and prunes them over many rounds, saves a tree doc. Run breakdown on the tree to distill it into a spec via guided questions.

Calibration testing for agents and skills. Generates synthetic problems with known outcomes (quasi-ground-truth), runs targets against them, measures recall, precision, confidence calibration — reveals whether self-reported confidence scores track actual quality.

Interactive outline co-creation for developer advocacy content — collects format, audience profile, story arc (Problem→Journey→Insight→Action), and voice/tone; detects out-of-scope requests (FAQs, comparison tables); surfaces conflicts between user brief and audience needs. Write

Strip AI-writing tells from prose destined for humans — docs, PR/commit bodies, reports, release notes, blog posts, Slack/email drafts. Removes LLM-vocabulary clichés (delve, boasts, testament, underscore, robust, tapestry...), banned constructions (not just X but Y, rule-of-thre

Systematic diagnosis for unknown failures — local environment, tool setup, CI vs local divergence, hook misbehavior, and runtime anomalies. Gathers signals broadly, ranks hypotheses, uses adversarial review (Codex or foundry:challenger) for ambiguous cases, probes each, and repor

Create, update, or delete agents, skills, and rules; update or delete hooks (hook creation not yet implemented — edit `hooks/<name>.js` directly). Full cross-reference propagation. Trivial edits (typos, small fixes ≤10 words) applied inline without agent; `.md` content-edits dele

Session clock-time AND token/cost analyzer. Reads the foundry plugin's timings.jsonl and invocations.jsonl logs (written by task-log.js) for wall-time, plus Claude Code transcripts (~/.claude/projects/**, main-loop + subagent files) for token usage and USD cost, and merges both i

Session state that outlives a context reset — `dump` sweeps the live conversation and writes a compact handover doc (goal, decisions + why, lessons, standing instructions, files-touched table, outstanding items, next step), then prints `/clear`; the `session-restore.js` SessionSt

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.

Create and manage database migrations

Analyze GitHub issue and create technical specification with implementation plan

Scaffold new feature with boilerplate code

Create a Jobs to be Done (JTBD) document for a product feature focusing on user needs

Create developer onboarding guide

Create a new branch, commit changes, and submit a pull request with automatic commit splitting

Create a Product Requirements Document (PRD) for a product feature

Create a comprehensive Product Requirement Prompt (PRP) with research and context gathering

Guide for creating pull requests using GitHub CLI with proper templates and conventions

Manage git worktrees for open PRs and create new branch worktrees

Manage cross-platform reference links

Systematically debug and fix errors

Analyze decision quality with scenario testing, bias detection, and team decision-making process optimization.

Explore decision branches with probability weighting, expected value analysis, and scenario-based optimization.

Audit dependencies for security vulnerabilities

Map and analyze project dependencies

Design optimized database schemas

Design RESTful API architecture

Create systematic digital twins with data quality validation and real-world calibration loops.

Analyze directory structure and purpose

MCP server for reusable prompt templates, multi-step workflow chains, and quality gates. Compose agentic workflows with an operator syntax; export as native ski…

中国股票数据基础设施，覆盖行情、研报、资金面、筹码、公告、龙虎榜、ETF/期权、舆情互动、基本面、行业板块、宏观与风险事件等核心数据。42+A股数据集，日更、自托管、MCP 原生，零注册、零 API Token

OKF (Open Knowledge Format): Durable, structured memory for AI agents. Author, validate, consume, and maintain portable knowledge bundles through an ecosystem o…

토스증권을 AI 에이전트와 터미널에서 다루는 도구. CLI 와 MCP 서버로 계좌·시세·주문은 물론 웹앱 전용 기능(수급·AI 시그널·스크리너·배당)까지, JSON·CSV 구조화 출력으로 AI 도구·자동화에 바로 연동.

Claude skills for LinkedIn. 11 Claude Code and Codex skills that write human-sounding LinkedIn posts, craft comments that get noticed, analyze your feed, and bu…

MCP server connecting AI agents to ITASCA engines (PFC, FLAC, 3DEC, MPoint, MassFlow) — run geotechnical & geomechanics simulations through natural conversation

A curated list of amazingly awesome articles, people, applications, software libraries and projects related to the knowledge management space

One local dashboard for every Claude Code, Codex, Cursor, Antigravity, and Kilo Code session on your Mac. Spawn in parallel, ship in parallel. Open source, MIT.

Building blocks for frontier OpenAI agents in Rust. Nanocodex empowers you with Codex-level performance anywhere.

The AI agent that lives in your framework/browser

Self-Programming AI Assistant. Capture, automate, and refine all your workflows.

Consider it done. The open-source AI agent that works out of the box · 想到，就能做到。开源、开箱即用的 AI Agent。

Make Any Website into CLI & Use your logged-in browser by AI agent.

ISO 24495 Plain Language skills and Claude Code plugin

Deterministic, fail-open tool routing for Hermes Agent with an optional local-model fallback.

1인 사업가 생산성 키트 — 직원 없이 49개를 자동화했고, 그중 바로 쓸 수 있는 AI 에이전트 스킬 26개(+실행 스크립트)를 공개합니다

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agent…

The open-source, self-hosted video conferencing software. Scalable, customizable, and with a powerful AI Meeting Agent.

Business operating system for Claude Code — 57 skills, 21 agents, smart daemon. Unified inbox (WhatsApp/Email/Slack/Telegram), autonomous PR merge, full-AWS mon…

A local-first, cross-platform Electron desktop workspace for Pi Coding Agent, with sessions, project files, browser tools, skills, plugins, and messaging integr…