LLM Mart Basic

Docs specialist — docstrings, API refs, README, standalone FAQ/comparison tables. NOT for CHANGELOG (oss:shepherd), linting (foundry:linting-expert), implementation (foundry:sw-engineer), narrative content (foundry:creator). TRIGGER: "write docs for", "add docstrings to", "update

Python static analysis — ruff, mypy, pre-commit, lint/type fixes, type annotations. NOT for CI topology (oss:cicd-steward), test logic (foundry:qa-specialist), non-style implementation (foundry:sw-engineer), docstrings (foundry:doc-scribe). TRIGGER: "is this clean", "lint issues"

Perf engineer — CPU/GPU/memory/I/O bottlenecks, DataLoader throughput, PyTorch tuning. Profile-first, measures before changing. NOT for refactoring (foundry:sw-engineer), architecture (foundry:solution-architect), DataLoader correctness (research:data-steward). TRIGGER: "why is t

QA specialist writing/fixing tests. Black-box tester: public API surface, expectations from docs not implementation. NOT for linting (foundry:linting-expert), implementation (foundry:sw-engineer), test perf (foundry:perf-optimizer), non-Python frameworks. TRIGGER: "write tests fo

Architectural spec specialist — ADRs, API design, migration plans, component diagrams. Reads code, produces specs only. NOT for implementation (foundry:sw-engineer), release mgmt (oss:shepherd), adversarial challenge (foundry:challenger), perf tuning (foundry:perf-optimizer). TRI

Senior SW engineer writing/refactoring Python — features, bugfixes, TDD, SOLID. Also authors hook JS files under hooks/. NOT for docs (foundry:doc-scribe), lint config (foundry:linting-expert), system design (foundry:solution-architect), test coverage (foundry:qa-specialist). TRI

Fetches web pages, API docs, external package/release info — version lookups, GitHub release extraction, docs scraping. NOT for code analysis (foundry:sw-engineer), ML paper analysis (research:scientist), internal docs (foundry:doc-scribe), local codebase search. TRIGGER: "check

CI/CD health specialist, Python/GitHub Actions only — failing CI runs, build times, test matrices, caching, SHA pinning. NOT for ruff/mypy config (foundry:linting-expert), PyPI release/CHANGELOG (oss:shepherd), non-GitHub-Actions platforms. TRIGGER: failing CI runs, slow builds,

Fetches all GitHub API data for a repo (REST + GraphQL) in two parallel groups; writes raw JSONL for oss:repo-warden axis scorers. TRIGGER when: spawned by /oss:analyse (vitality mode) to fetch raw GitHub data. NOT for axis scoring or report generation. NOT for direct user invoca

Scores an assigned group of vitality axes from a pre-fetched DATA_FILE using vitality-scoring.md; writes partial scores JSON for /oss:analyse assembly. TRIGGER when: spawned 3× in parallel by /oss:analyse (vitality mode) to score axis groups A, B, or C. NOT for raw data fetching

OSS shepherd, Python/ML/CV/AI — contributor communication (triage, reply/PR drafts), release coordination (SemVer, PyPI, CHANGELOG). NOT for docstrings/README (foundry:doc-scribe), CI/publish YAML (oss:cicd-steward), diff review (/oss:review), CHANGELOG gen (/oss:release). TRIGGE

Data lifecycle specialist — dataset acquisition, DVC versioning, split audits, leakage detection, DataLoader config. Manual invocation only — no research skill auto-dispatches this agent. Delegates scraping to foundry:web-explorer. NOT for ML experiment design (research:scientist

AI/ML researcher — paper analysis, hypothesis generation, experiment design. ONLY for named research paper/hypothesis/experiment. NOT for general Python (foundry:sw-engineer), SOTA surveys (/research:topic), web content (foundry:web-explorer), dataset acquisition (research:data-s

Creates original editorial illustrations where a recurring mascot character performs the idea — one caught scene by default, a hand-built explainer diagram (labeled stages, a fan-out, timeline, loop, or stack) when the structure itself is the point, or a transparent character cut

Use when the user has agreed to install the Hedgehog build discipline in a project that does not have it yet, or when they mention Hedgehog by name — carries the `npx @skyf0xx/hedgehog init` install procedure and its core and host flags. The plugin's SessionStart hook decides whe

Maintainer-only. Use when re-vendoring vendor-skills/BMAD/ against a newer BMAD-METHOD commit — "update BMAD", "re-vendor BMAD", "bump the BMAD pin". Not part of the Hedgehog discipline a consuming project copies; this only applies to the Hedgehog repo itself.

Maintainer-only. Use when triaging inbound GitHub issues and pull requests on skyf0xx/hedgehog — "triage the issues", "check the PRs", "review inbound", "what's in the queue". Reads each item read-only, judges it for security and for whether it is real, then fixes and closes or c

Use when uncommitted changes need to be split into atomic, conventional commits ordered for review. Triggers on "commit this", "make commits", "clean up commits", "commit the changes". In Hedgehog, each Loop step is already meant to be its own commit — this skill matters most whe

Use when the user wants to contribute a fix or ROADMAP.md item back to the Hedgehog project itself (skyf0xx/hedgehog) rather than their own project. Triggers on "let's fix that in Hedgehog", "I want to contribute", "let's pick up a roadmap item", or when `tweaker` offers this at

Use on any core for first-run planning intake — Phase 0 runs the vendored BMAD-METHOD planning shelf, shared by every core, and Phase 1 (mining `04-prd.md` into intent records plus the Add-ons/sync-and-remote-entities decision) is full-stack-app's and pwa-app's shared procedure —

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.

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.

Discover testnet↔mainnet subnet lineage from repo configs and open a PR for review (pass --dry-run to report only)

Triage raw inbox notes into reviewed repository destinations without deleting their sources.

Audit and rewrite content to remove AI writing patterns

Log a completed piece of content to content/log.md after the user confirms it was published.

Validate a dream artifact, review each proposal, and apply only individually accepted changes.

Run a curator pass against the validated memory directory and produce a proposal artifact.

End a session — log what happened, update state and the decision log, propose memory updates, and check for uncommitted or unpushed work

Find relevant context files by topic. Use when you need to load files for a topic without a slash command, or when a task spans multiple domains.

Inventory and migrate selected Gemini CLI workflows with dry-run review and parity checks.

Find repeated workflows in selected Gemini CLI sessions and draft portable skills after review.

Scan multi-session drift and offer individually reviewed fixes only after explicit approval.

Scan orphaned worktrees and stale branches, then offer explicit approval-gated cleanup.

Guided onboarding or import for durable workspace context

Start a session — load state files, flag staleness, and give a briefing on current priorities, deadlines, and blockers

Create a morning heartbeat from repository state and update the local heartbeat log.

Mid-session checkpoint — append progress to today's session log and update state files if a priority shifted, without ending the session

Maintainer-only. Find every file that would newly ship to adopters, classify each one against the written distribution-boundary categories, default to withhold on no clean match, and ask the maintainer only where the taxonomy does not settle it. Drives the release CLI, which refuses to produce a manifest until every shipping file has an answer.

Audit memory, wiki, and auto-loaded files for duplication, conflicting instructions, and stale content. The default path researches, then asks you a single Apply / Discuss / Decline question; on Apply it applies the report, files any out-of-scope problem as a tech-debt issue, then commits, opens a PR, and merges it on a main-branch run like /update-deps. Pass --apply to re-run the apply-and-publish stage against the most recent report.

Fix the tech-debt backlog, a single issue or a recommended related batch, highest severity then oldest first, on a fresh isolated branch through the audit gate, closing the issue(s) on merge. Pass `list` to see the ordered backlog, `why <issue-number>` to explain the recommendation, or a bare `<issue-number>` to fix that issue directly.

Health-check and auto-heal this project's Claude integration, triage, heal, verify, and report an F-to-A+ grade.

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.