LLM Mart Basic

World-class completeness audit — score a project's rules/standards/features against best-in-class exemplars, name the gaps, fill missing rules, adopt as binding, then offer to conform existing code. Triggers on keywords: "/gold-standard", "gold-standard", "audit rules", "are we w

Failure-mode audit (FMEA for software) — for each way the system can fail (network, storage, partial completion, crash, concurrency, bad input), check whether code DETECTS, HANDLES, RECOVERS, and COMMUNICATES it. Triggers on: "/resilience-audit", "resilience-audit", "FMEA audit".

Code-health scan — dead code, bug-prone logic, resource leaks, concurrency bugs, silent failures, input-boundary issues, doc rot. Triggers on: "/rot-canary", "rot-canary", "code-health" (legacy aliases: "/rotcanary", "rotcanary"). Auto-runs at session end on touched files (QUICK,

Performance complexity and resource allocation canary — checks for O(N^2) loops, database N+1 query patterns, memory leaks (unbounded collections), and blocking calls in main event loop. Triggers on keywords: "/scale-canary", "scale-canary", "performance audit", "scale audit". Us

Verify version-sensitive facts against live authoritative sources before asserting them in code or answers. Triggers on: "/source-grounding", "source-grounding", "sourcing". Standing rule — always active via CLAUDE.md. Invoke for deep verification work (API signatures, CVEs, mode

Software supply chain audit — dependencies (CVEs, maintenance, licenses, transitive risk), build/CI integrity (SHA-pinned actions, lockfile, CI-only release), artifact integrity (checksums, signing, SBOM). Triggers on: "/supply-chain-audit", "supply-chain-audit", "dependency audi

Observability and structured logging canary — checks for structured logs (JSON), OpenTelemetry metrics/traces, proper error stack traces, and flags empty catches or silent log swallowing. Triggers on keywords: "/telemetry-canary", "telemetry-canary", "observability audit", "struc

Testability and design decoupling canary — checks for tight coupling, lack of Dependency Injection (DI), hardcoded constructors, Single Responsibility Principle (SRP) violations, and mockability gaps. Triggers on keywords: "/testability-canary", "testability-canary", "testability

Automate controlled local ArcGIS Pro and ArcPy workflows through arcgis-mcp-bridge: inspect .aprx projects and file geodatabases, run geoprocessing, projection, raster, network, spatial-statistics, editing, symbology, and layout export with path and mutation guards. Use when the

Always invoke before answering any request to create, compare, design, or review a user-facing map, even if the request is terse or underspecified. Covers publication maps, choropleths, map series and small multiples, comparable multi-date panels, proportional/bivariate/flow maps

Change analysis, once the observations are comparable. Not for cases whose blocker is comparability itself: mixed sensors, product levels or processing baselines to remote-sensing-analysis, undocumented vertical datums to point-cloud-lidar, multi-decade archive trends over large

Always invoke when geospatial data must be acquired, prepared, repaired, scaled, or moved through a repeatable pipeline. Covers open-data/OSM/STAC acquisition, spatial formats, CRS transforms, quality checks, and batch ETL architecture for growing or recurring joins. Invoke along

Invoke before recommending, training, or auditing a neural method for geospatial imagery, including vision transformers, U-Net/DeepLab/SegFormer, object detection, pixel classification, building/road extraction, and EO foundation-model fine-tuning. Also invoke for neural chip-spl

Route genuinely ambiguous or multi-stage geospatial work across specialist skills while enforcing shared CRS, validity, leakage, units, verification, and reproducibility rules. Use for requests spanning multiple stages such as acquisition, imagery, modeling, analysis, and map del

Turn scattered point measurements into continuous surfaces with quantified uncertainty: variogram modeling, ordinary/universal/regression kriging, IDW, and spatially honest cross-validation. Use when unobserved values must be estimated from sparse samples such as stations, wells,

Invoke when Earth Engine, GEE, ee., or geemap is named; when work needs its server-side catalog; or when choosing Earth Engine versus local xarray or desktop processing for a large area or long archive. Covers image collections, masking, compositing, reducers, zonal statistics, t

Always invoke for spatial suitability, site selection, AHP, criteria weights, or weighted-overlay work, including audits of inconsistent pairwise judgments and requests for only a final map. Covers consistency, standardization, constraints, ranked surfaces, shortlists, and sensit

Always invoke for training, validating, tuning, benchmarking, or claiming readiness of a predictive model. Covers leakage audits, spatial and grouped splits, metrics, reproducibility, and honest reporting. Invoke especially when spatial dependence, split design, or deployment geo

Movement and trajectory analytics from GPS/GNSS tracks: cleaning, stop/trip detection, road-network map matching, speed/direction, flow aggregation, and origin-destination construction. Use for fleets, human mobility, animal tracking, AIS, or sports tracks. Trigger on GPS points,

Always invoke for access to facilities or opportunities by walking, driving, cycling, or public transport, even for a conceptual question with no routing terms or data yet. Covers hospital and service access, transit/GTFS, routes, isochrones, OD matrices, closest facility, 2SFCA,

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.

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.

An open-source, privacy-first, self-hosted knowledge workspace where humans and AI agents work together 开源、隐私优先、自托管的知识工作空间，让人与智能体在此协作

Scale computer-use 2.0 with open-source drivers, cross-OS fleets, and benchmarks for training, evaluation, and data generation.

The go-to web for your AI coding agent — local-first search, fetch, crawl & research over MCP. No API keys, no cloud, $0/query. Public beta.

Transform and optimize your markdown documentation for Large Language Models (LLMs) and RAG systems. Generate llms.txt automatically.

合乎周礼：DeepSeek-powered Zhouli-style Chinese translator, web app, and distributable Skill package.

This is a fork of the https://dockbox.dev project I made

🏆 Curated, ranked list of AI agent harnesses (100+) — plus an MCP server, llms.txt & JSON so agents can recommend them too. Rescored weekly.

A Python framework for modular, self-contained skill management for machines.

ADHD — a skill for coding agents. Tree-of-thought with pruning, built on the Claude & Codex Agent SDK. Fans out parallel divergent thoughts under different cogn…

AI Agent 驱动的开源可自部署视频工作台：将小说与剧本转为角色、场景、道具资产、分镜、视频和剪映草稿，支持跨镜头一致性、多供应商与费用追踪 | Self-hosted AI video workspace for stories, storyboards and short-form video producti…

DeepSeek Harness Desktop App: a local AI desktop workspace for DSH Sessions, projects, files, web research, plugins, and Office artifacts.

Autonomous Offensive Security, Bug Bounty & Red Teaming Agent Framework powered by Hermes Agent, specialized reasoning skills, and multi-model LLM orchestration…

⌥ Coding agent with the IDE wired in

Supercharge AI Agents, Safely

X (Twitter) Scraper API and X API Alternative. You do not need an official X developer account. You do not need to connect or use an X account for supported scr…

My AI Stand. Realtime by day, rewriting itself by night. Summon my AI superpower.

Open-source coding agent for your terminal, built in Rust and on a journey of continuous community improvement. Issues and PRs welcome.

观澜 / Guanlan：AI Agent 的中文互联网研究、阅读与信源路由工具。

Mac Agent for macOS 26: the agentic AI harness for your Mac Desktop. Computer use, automation, scripting, coding, and more. Powered by 18+ providers across loca…

Semantic version control => entity-level diffs, blame, and impact analysis on top of git. 28 languages via tree-sitter. Built for coding agents.