LLM Mart Basic

Propagates dimensional annotations through arithmetic and call chains, reporting mismatches found during propagation

Validates dimensional consistency and detects dimensional bugs in annotated code

Analyzes data flow from source to vulnerability sink, mapping trust boundaries, API contracts, environment protections, and cross-references. Spawned by fp-check during Phase 1 verification.

Verifies whether a suspected vulnerability is actually exploitable by proving attacker control, mathematical bounds, and race condition feasibility. Spawned by fp-check during Phase 2 verification.

Creates proof-of-concept exploits (pseudocode, executable, and unit tests) demonstrating a verified vulnerability, plus negative PoCs showing exploit preconditions. Spawned by fp-check during Phase 4 verification.

Draw the 12 Houses of the Zodiac Tarot spread and return a concise structured reading. Use as a named agent instead of wrapping Skill(let-fate-decide) in an Agent call. Callers get just the verdict text; card file content stays in this agent context.

Deduplication judge for the rust-review pipeline. Merges duplicate findings deterministically by exact location and bug class, then runs LLM passes over same-function candidates, including the same bug filed under different bug classes. Spawned by the rust-review skill orchestrat

Second-stage judge in the rust-review pipeline. Runs after dedup-judge on merged primaries only. Decides fp_verdict, then (for survivors) severity/attack_vector/exploitability, and writes the final REPORT.md + REPORT.sarif. Spawned by the rust-review skill orchestrator only.

Runs one assigned rust-review cluster task and writes finding files to the run's output directory. Spawned by the rust-review skill orchestrator only.

Evaluates APIs, configurations, and library interfaces for misuse resistance and footgun potential. Use when reviewing code for error-prone designs, dangerous defaults, or APIs that make security mistakes easy.

Checks one documented requirement against the code that should implement it, and returns a verdict with the lines that evidence it. Writes its analysis to disk and returns a compact record. Use for a single requirement; use the spec-compliance workflow for a whole document.

Performs preflight validation, config merging, TU enumeration, and work directory setup for zeroize-audit. Produces merged-config.yaml, preflight.json, and orchestrator-state.json.

Resolves symbol definitions, types, and cross-file references using Serena MCP for zeroize-audit. Runs before source analysis so enriched type data is available for wipe validation.

Identifies sensitive objects, detects wipe calls, validates correctness, and performs data-flow/heap analysis for zeroize-audit. Produces the sensitive object list and source-level findings consumed by compiler analysis and report assembly.

Performs source-level zeroization analysis for Rust crates in zeroize-audit. Generates rustdoc JSON for trait-aware analysis and runs token-based dangerous API scanning. Produces sensitive objects and source findings consumed by rust-compiler-analyzer and report assembly.

Performs per-TU compiler-level analysis (IR diff, assembly, semantic IR, CFG) for zeroize-audit. One instance runs per translation unit, enabling parallel execution across TUs.

Performs crate-level MIR and LLVM IR analysis for Rust in zeroize-audit. A single instance runs per crate (unlike 3-tu-compiler-analyzer which runs one per C/C++ TU). Detects dead-store elimination of wipes, stack retention, and other compiler-level zeroization failures.

Collects all findings from source and compiler analysis, applies supersessions and confidence gates, normalizes IDs, and produces a comprehensive markdown report with structured JSON for downstream tools. Supports dual-mode invocation: interim (findings.json only) and final (merg

Crafts bespoke proof-of-concept programs demonstrating that zeroize-audit findings are exploitable. Reads source code and finding details to generate tailored PoCs — each PoC is individually written, not templated. Each PoC exits 0 if the secret persists or 1 if wiped. Mandatory

Compiles and runs all PoCs for zeroize-audit findings. Produces poc_validation_results.json consumed by the verification agent and the orchestrator.

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.

Run the reliability scorecard for one service, or every connected service if omitted - error-budget burn rate where an SLO is defined, trend reporting otherwise

Generate the current on-call handoff brief - what's paging, what's escalated without an owner, last-shift history, and known-flaky alerts to watch

Draft a blameless postmortem for a given incident (by ID or name), or the most recent significant incident within a time window

List all devices at a Domotz-monitored site

Find a Domotz device by name, IP address, or MAC address

Overview of a Domotz site's network health

Pull full detail for one Checkpoint Harmony Email detection and the message behind it

Restore quarantined mail to its recipients in Checkpoint Harmony Email, with task polling

Find messages in Checkpoint Harmony Email by sender, subject, attachment hash or quarantine state

Sweep security events in Checkpoint Harmony Email by type, state, severity and date range

Get summary of recent phishing and training campaigns from KnowBe4

Get security awareness metrics for a KnowBe4 group

View phishing campaign results and click rates from KnowBe4

Check training completion status for users or groups in KnowBe4

Get risk score and risk history for a KnowBe4 user

Full health check for one Proofpoint Essentials customer org

Resolve a Proofpoint Essentials customer org by name or domain and show its details

View recent TAP threat events including blocked messages, delivered threats, and click activity

Decode a Proofpoint URL Defense rewritten URL back to the original URL

Deep-dive threat investigation with forensics, campaign context, and remediation options

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…