LLM Mart Basic

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.

Use aai-cli email commands with Zoho Mail profiles to list, read, send, and delete Zoho messages.

Compiles a single raw Vaultr note into knowledge units using a two-phase AI process (triage → compile). Use this skill whenever the user wants to compile a note into knowledge, extract knowledge from a note, update the knowledge base from a note, merge note content into knowledge

Builds and refreshes domain-based index files for the Vaultr knowledge base. Use this skill whenever the user wants to build, rebuild, refresh, or update the knowledge index, create domain indexes, organize knowledge by domain, or index the knowledge base. Triggers on phrases lik

Extract and update personal memories from Vaultr notes into structured memory files. Use when the user wants to update their personal memory, extract memories from notes, run memory extraction, or refresh the personal memory base. Triggers on phrases like 'update my memory', 'ext

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.

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

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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.

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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.

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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.

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PiG (Pi in Go) is a faithful Go port of upstream Pi, the TypeScript codebase behind the Pi coding agent. It is a parity-bound translation, not a rewrite: upstre…

An AI Agent that lives in your pocket. Local-first and privacy focused.

Unofficial skill that teaches coding agents to build with TypeSafe AI's Jev: typed decisions, calibrated confidence, and prior art from 150+ community projects.

Adaptive Test-time Learning and Autonomous Specialization

Prediction-market trading engine — Wang Transform pricing on 291K+ contracts; paper-traded across Kalshi · Polymarket · Solana DFlow (Jito bundles) · 633 tests

Knowledge Management for Humans and Agents

Open-source Claude Cowork / Codex / WorkBuddy alternative — a local-first AI office agent that turns one request into real PPTX, DOCX, XLSX and HTML files. Runs…

DeepAgent Code: AI coding agent with persistent memory and control plane

Awesome Jev — evidence-graded index of TypeSafe System One: SDKs, MCP tools, agents, apps and open models. 20 languages, rebuilt every 2 hours.

CLI for Telegram — agent-friendly, daemon-based, with webhook event push.

AI deep-research agent that turns any question into a cited report: plans searches, reads real sources, verifies evidence. Self-hosted, multi-provider, Docker-r…

Event-stream AI Agent framework for building your persona bot 🍊

Give the agent a machine. Just not yours. Each AI coding agent gets its own isolated machine with root, Docker, and systemd - active defense detects and stops t…

Local Emperor-style AI agent with Vue WebUI, multi-provider LLMs, streaming chat, tools, skills, memory, and token telemetry.

Open-source AI reverse-engineering agent platform and MCP server for Ghidra, Frida, x64dbg and Rizin — automated PE/APK/binary analysis, CTF and malware researc…

"Never send a human to do a machine's job" - Open Source AI hacking agent

Prismer Cloud

My Personal Blog (Robotics)

Tau Coding Agent - like Pi, but twice as much

Open-source alternative to OpenAI Dots: self-hosted AI chat, tools, approvals, connectors, and computer tasks.