LLM Mart Basic

Invoke whenever spatial SQL or its execution backend is the decision: PostGIS, DuckDB Spatial, SpatiaLite, ST_* functions, recurring spatial joins, concurrent/growing workloads, or large GeoParquet queries. Covers backend selection, schemas, GiST/BRIN indexes, KNN, geometry versu

Always invoke for classical analysis, classification, validation, or comparability of satellite, aerial, or drone imagery. This skill owns sensor, product, processing-level and processing-baseline harmonization, including multi-date inputs; add change-detection only after compara

Always invoke before testing a geographic pattern for clustering, hotspots, dependence, or explanatory regression, even when aggregation or ordinary OLS is proposed as routine. Covers Moran's I, LISA, Getis-Ord Gi*, weights, MAUP and scale sensitivity for areas/grids, residual de

Always invoke to review, repair, or deliver geospatial or GeoAI code, including contract compliance, security, error handling, transactions, tests, scripts, functions, notebooks, packages, CI/CD, and repository changes, even when deployment is not requested. Pair with the domain

Always invoke for terrain, drainage, viewshed, or visibility analysis from elevation, even before the DEM or correct surface is chosen. Covers DTM-versus-DSM selection, slope, aspect, curvature, hillshade, conditioning, flow direction/accumulation, streams, watersheds, and catchm

Manage Preset teams, workspaces, memberships, invites, role identifiers, seat checks, and audit logs through direct Management API calls. Use only for direct API workflows; Do not use for MCP-only work.

Prepare direct Preset API access: auth, JWT exchange, base URLs, pagination, Rison parameters, response handling, and shared API setup. Use only for direct API workflows; Do not use for MCP-only work.

Use Snowflake Cortex Agent REST and SQL APIs for listing, describing, creating, updating, deleting, running agents, streaming responses, and SQL wrappers. Use only for direct API workflows; Do not use for MCP-only work.

Inspect Preset workspace dashboards, charts, dashboard composition, screenshots, thumbnails, chart data, and chart/dashboard operation routing through direct Superset API calls. Use only for direct API workflows; Do not use for MCP-only work.

Inspect or route Preset database connection configuration, validation, OAuth, upload, create, update, and delete workflows through direct Superset API calls. Use only for direct API workflows; Do not use for MCP-only work.

Inspect Preset workspace datasets, database metadata, schemas, tables, columns, metrics, and dataset/database workflow routing through direct Superset API calls. Use only for direct API workflows; Do not use for MCP-only work.

Review destructive, overwrite-capable, sparse-update, all-assets restore, database import, and secret-bearing Preset import workflows through direct Superset API calls. Use only for direct API workflows; Do not use for MCP-only work.

Review embedded analytics row-level security clauses, tenant filters, guest-token RLS rules, and external-viewer isolation for direct API workflows. Use only for direct API workflows; Do not use for MCP-only work.

Inspect embedded dashboard configuration, trusted domains, origins, guest-token routing, and embedded RLS routing through direct Superset API calls. Use only for direct API workflows; Do not use for MCP-only work.

Prepare and create Preset embedded dashboard guest tokens, external-user claims, resource claims, RLS claims, and token-handling plans through direct Superset API calls. Use only for direct API workflows; Do not use for MCP-only work.

Inspect and route direct Superset import/export workflows for dashboards, charts, datasets, databases, saved queries, themes, and asset bundles. Use only for direct API workflows; Do not use for MCP-only work.

Review Preset role, workspace membership, permission, access-control, DAR/RLS-adjacent, and effective-access changes through direct API calls. Use only for direct API workflows; Do not use for MCP-only work.

Prepare Snowflake Cortex direct API access: account URL, auth method, role, warehouse, database/schema context, privileges, and Cortex Agent routing. Use only for direct API workflows; Do not use for MCP-only work.

Run or route SQL Lab execution, result retrieval, exports, query stop, saved-query mutation, and permalink workflows through direct Superset API calls. Use only for direct API workflows; Do not use for MCP-only work.

Inspect Preset SQL Lab bootstrap, query history, saved queries, result/export routing, query control, and SQL execution routing through direct Superset API calls. Use only for direct API workflows; Do not use for MCP-only work.

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.

Scan for codebase bloat using 3-tier progressive analysis: dead code, duplication, God classes, and documentation waste.

Review the current working diff against the elegant-code decision ladder and propose deletions, honoring the negligence floor.

Suggest tier-1 filter commands for a log file before any compression or paste. Anchors on the log-debugging-hygiene module.

Analyze and optimize context window usage using MECW principles

Remove dead code, duplicate files, and unused dependencies with user approval at each step. Backs up before deleting.

The ONLY way to stop the egregore. Human-initiated graceful shutdown that saves all state.

Install the egregore watchdog daemon for automatic session relaunching

Show current egregore state and progress

Summon the egregore to autonomously process work items through the full development lifecycle. Runs indefinitely by default until dismissed.

Remove the egregore watchdog daemon and clean up files

Add or edit a knowledge annotation

Rebuild the knowledge base from the current codebase

Build, search, and query the code knowledge graph

Start or resume a guided onboarding path

Show challenge accuracy stats, weak areas, and streak

Run an ad-hoc gauntlet challenge session (5 questions, random scope)

Interactive interface to enable/disable rules

Convert Python SDK hooks to declarative rules

Display help and documentation

Create behavioral rules to prevent unwanted actions

Open-source, self-hosted AI media server. One server replaces your entire media stack, with a web app, native iPhone app, and an AI agent that gets things done.…

A curated list of tools built for Jev — TypeSafe AI's System One model for typed decisions.

🦦 Crayotter: A Multimodal AI-Agent for Video-Editing, Video-Composing, and Video Production. Powered by Multimodal LLMs for autonomous Text-to-Video agentic fr…

Webextension tool for Odoo