LLM Mart Basic

Runs verification commands and confirms output before success claims. Use before claiming work done or committing or PRs.

Use when you have a spec or requirements for a multi-step task, before touching code

Use when creating new skills, editing existing skills, or verifying skills work before deployment

Aggregates transcript and frame data into an interactive web dashboard. Use for content, topic, or sentiment analysis.

Collects videos from public social accounts. Use to download or scrape from Twitter, TikTok, YouTube, Instagram, or Facebook.

Batch Whisper transcription of video or audio (WAV, podcasts) with a re-runnable provenance record. Use to transcribe recordings.

HTML explainers, diagrams, architecture, timelines, source maps, slide decks, comparison tables, recaps, plan and diff reviews.

Validates and structures lesson candidates before persisting to lessons.json

Atlassian CLI (official `acli` binary, v1.3+ as of 2026) for Jira Cloud, Confluence Cloud, and org admin tasks from the terminal. Use whenever the user wants to create, view, edit, transition, assign, clone, archive, comment on, link, or bulk-operate on Jira work items; list or m

Walks new users through this repo's QA flow — Playwright + KATA + Allure + Xray stack, Jira QA workflow (Backlog → Shift-Left QA → Estimation → Ready For Dev → Ready For QA → In Test → QA Approved → Ready For Release → Deployed to Production), /shift-left-testing for pre-sprint A

Turns a raw bug screenshot into a QA-style annotated evidence image — circles/ovals around the broken region, arrows, callout text boxes, a 'BUG — <KEY>' corner badge, and axis tick-marks for date/offset bugs. Use whenever a bug is visual or positional (overlapping elements, misa

Framework evolution mode — evolves the QA boilerplate itself (KATA, fixtures, cli/, scripts/, api/schemas/ pipeline, package.json deps). Self-contained Plan → Code → Verify → Archive pipeline; runs under the `gentle-ai install --preset minimal` install (no SDD-* skills required).

End-to-end Git operator for any branching strategy. Auto-detects the project's strategy (solo-main, main+integration, enterprise multi-branch, trunk-based, GitFlow, GitHub Flow, GitLab Flow, SDET integration-trunk for chained test-automation suites) from .git config, branches, an

Run bounded Jira administration workflows for project Components or Atlassian instance migration. Use for jira-components, sync Jira components, jira-instance-migration, changed Jira URL, or repoint Jira. Both modes are sealed behind read-first analysis and explicit user approval

Acts as a QA Lead / QA Architect reviewing a pull request's test-automation work against this repo's KATA doctrine (or the target repo's own doctrine, if it has one) and general QA best practices — grounding every finding in a concrete doctrine citation or code location, never a

Onboard a project through four discovery phases: Constitution, Architecture, Infrastructure, and Specification. Produces PRD, SRS, domain glossary, infrastructure context, and backlog access, then hands business maps and the master test plan to `project-context`. Use for set up t

Execute regression test suites via CI/CD, analyze results, classify failures, and produce GO/NO-GO release decisions. Use when running regression, smoke, or sanity suites through GitHub Actions, monitoring workflow runs, downloading Allure or Playwright artifacts, classifying fai

Orchestrates pre-sprint Shift-Left QA on a batch of backlog Stories. Use when the user wants to refine acceptance criteria, surface ambiguities + gaps, draft an ATP outline, and hand off to PO/Dev BEFORE the Story enters a sprint — so defects are prevented in the requirements, no

Plan, write, and review automated tests following KATA (Komponent Action Test Architecture) on Playwright + TypeScript, or explain existing automated tests in a sealed read-only mode. Use when writing E2E or API/integration tests, creating Page or Api components, designing ATCs,

Analyze, prioritize, and document test cases in TMS (Jira/Xray), or repair an existing Story-ATS-ATP-ATR-TC cascade through a sealed explicit mode. Use for Test/ATP/ATR artifacts, ROI and automation verdicts, maintaining traceability, fix-traceability, or broken TMS links. The re

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.

Periodic multi-reviewer sweep of the whole codebase — surfaces a triaged checkpoint report.

Sanctioned lane for non-behavioral work — docs-only edits, dependency bumps, reverts. Type-scaled gates; no TDD demanded of prose.

{{SKILL_ENTRY:post-merge-cleanup}}

Show the codeArbiter command catalog — the public command list and what each routes to.

{{SKILL_ENTRY:commit-gate}}

Stop everything and surface a rule conflict — persona vs. docs vs. code. Present both sides and the conflict-hierarchy level; the user resolves. No silent reconciliation.

{{SKILL_ENTRY:context-check}}

{{SKILL_ENTRY:context-creation}}

{{SKILL_ENTRY:debug}}

{{SKILL_ENTRY:decompose}}

Verify the active host install, package, command ownership, enforcement{{IF:pi}}, wrapper self-test, and active-dispatch coverage gap{{ELSE}}, and harmless live-fire probe{{END}}. Read-only.

Start a feature: brainstorm a spec, get it approved, then drive it test-first through the pipeline. The one entry to implementation.

Fix a confirmed bug: a failing regression test first, then a minimal fix, then the rest of the tdd gates.

Opt this repo into codeArbiter — scaffold the root-level .codearbiter/ state store.

Read-only 3-metric governance glance — override rate, small-lane rate, sprint low-confidence ratio — each with a trend arrow vs. the prior 20-commit window.

Sanctioned, logged bypass of a gate or hard rule — one audit line, then proceed.

{{SKILL_ENTRY:finishing-a-development-branch}}

Zero-onboarding, read-only dry-run of the reviewer fleet against the current uncommitted diff. Predicts reviewers, runs the state-free secret scan, writes nothing.

Trim transcript clutter to extend session lifetime — analyze, prune a copy, or toggle the after-each-turn service. Dry-run by default; gains land at resume/compaction, not the current turn.

{{SKILL_ENTRY:decision-variance}}

Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat ap…

Governance framework for AI coding agents. It runs them through a five-step workflow (plan, build, review, test, ship) where no step counts as done without evid…

Ultimate Multi-Agent OS for Autonomous AI NPCs 2026

Personal AI Agent Hub 2026 — Build Your 24/7 Autonomous Assistant

Proven 2026 Multi-Agent AI Review System – Verdict-Driven Quality Control

Slash API Batch: Cut AI Costs by 50% in 2026

Web dashboard for Hermes Agent — multi-platform AI chat, session management, scheduled jobs, usage analytics

Agent Skills for Solopreneurs

AirLLM dramatically reduces inference memory usage, letting 70B large language models run on a single 4GB GPU card

Zero, your trustworthy AI teammate for real work.

一套 DSH runtime，Desktop、Web 与 TUI 三种开发体验。

Open-source operational advisor for ClickHouse — real-time monitoring plus AI-driven index/partition/materialized-view recommendations.

⚙️ TypeScript Style Guide and Agent Skill. A concise set of conventions and best practices for consistent, maintainable code.

Framework for AI agents to build and maintain a digital brain through Obsidian wiki

Apache Maka (Incubating) is a local-first AI agent workspace. Model messages, tool calls, tool results, permission decisions, and termination events are recorde…

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active H…

Agentic development harness for Claude Code — SPEC-driven plan/run/sync, TRUST 5 quality gates, model+effort routing, and Claude×GLM multi-LLM cost control. Sin…

NocoBase is an open-source AI + no-code platform for building business systems fast. Instead of generating everything from scratch, AI works on top of productio…

An open-source AI coding agent that lives in your terminal.

PawWork — free, open-source desktop AI agent for macOS and Windows. Alternative to Codex App and Claude Cowork. BYOK with 75+ providers, ChatGPT OAuth, local mo…