LLM Mart Basic
@llm-mart · Joined Jun 2026
Use when the user explicitly asks to build, modify, or publish a Manifest V3 Chrome extension. Not for store submission without human-gated credentials.
Use when setting up or modifying CI/CD pipelines, quality gates, test runners, or deployment pipeline configuration through workflow files. Not for triggering a deployment.
Use when "CI is red", "fix the checks", or "make CI green", one check needs classifying, or a bounded sweep runs. Not for deploys, credentials, or rerun-as-fix. Non-CI bugs: use strike-the-root.
Use when a C or C++ build uses clang and needs diagnostics, optimization remarks, clang-tidy, ThinLTO with lld, LLVM PGO, or a GCC-to-Clang migration. Not for LLVM IR work: use llvm.
Use when setting up a project, auditing agent command permissions, or asking which read-only bash commands and domains to allow. Not for remote, credential, publish, deploy, or irreversible changes.
Use when the user just edited a durable artifact, or says "clean and true", "run the hygiene pass", or "taste the output". Routes the artifact through the hygiene passes it earned.
Use when asked to run /clean-clean-cut to cut accumulated records and residue. Not for untracked or non-VCS changes, or branch/worktree cleanup: use git-cleanup.
Use when asked to build or review a CLI intended for coding agents and return flag-driven, pipeline-safe, idempotent design advice. Not for running or profiling a CLI: use control-cli.
Use when the user wants to batch-close resolved or outdated tracker items. The agent never closes tracker items itself. Not for individual closure or items still under active work.
Use when a human explicitly runs /cloud-task-orchestrator for a large task across cloud agents to drain a verified task graph. Not for local subagent coordination: use orchestration-patterns.
Use when writing CMakeLists.txt, out-of-source builds, target_link_libraries, target properties, find_package/FetchContent, toolchain files, CPack, CMake presets, or cmake configure errors.
Use when reading llc output, tracing IR through legalization and instruction selection, or scoping a new LLVM target. Not for IR-level passes: use llvm-ir-and-passes.
Use when the user asks to simplify, clean, or refine code. Not for new abstractions or whole-codebase refactors.
Use when building or reusing a CodeQL database, running CodeQL security analysis, or modeling project-specific sources and sinks. Not for manual vulnerability review: use security-review (mode: confirmed).
Use when asked to commit changes, create a typed branch, format history for a changelog, or rewrite messages of HEAD or an unpushed range. Not for pushing or a PR: use commit-push-pr.
Use when a human asks to commit and push, not publish, the checked-out branch, including directly to the default branch, with no branch creation and no pull request. Not for a feature branch off the default: use commit-push-pr in its no-PR mode.
Use when asked to commit and push a feature branch, with or without a pull request. Its no-PR mode publishes without a PR. Not for a PR body alone: use create-pull-request.
Use when asked to research a feature across competitor products or to analyze competitor release changelogs (mode: changelog), and publish a cited report.
Use when the user asks for direction and a compilable 3D workflow from an interview. Not for remote, credential, publish, deploy, or irreversible changes.
Use when building a lexer, Pratt or recursive-descent parser, AST, symbol table, type checker, or LLVM IR emitter for a language or DSL. Not for optimizing IR: use llvm-passes.
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.
/update
Update
CoalWash self-update — check for a newer version and offer to apply it, or set how updates are handled.
/create-skill
Create skill
Create an AI skill from any source (URL, repo, PDF, video, notebook, etc.)
/install-skill
Install skill
One-command skill creation and packaging for a target platform
/sync-config
Sync config
Sync a scraping config's URLs against the live documentation site
/mc-validate
Mc validate
Generate and run validation queries for the current change
/mc-validate
Mc validate
Generate and run validation queries for the current change
/setup-code-intelligence
setup-code-intelligence
Check code-intelligence prerequisites (ripgrep + a language server) and print install hints
/ci-mockup-figure
Ci mockup figure
Create space-efficient paper and proposal figures (HTML mockups, TikZ, or skia-canvas) from tool selection through LaTeX insertion
/editable-figure
Editable figure
Design concise overview, mechanism, or workflow figures as editable PowerPoint objects
/implement-review
Implement review
Run the implement-review staged-change review loop
/my-router
My router
Detect the work type (papers, proposals, code, figures, admin) and dispatch to the right domain skill
/prun
Prun
Run prun: parallel delegation fan-out on Agy workers (the session coordinates)
/readme-polish
Readme polish
Audit a GitHub README and rewrite it with modern patterns for a scannable ten-second skim
/vet
Vet
Vet the staged change: run the implement-review review loop (short alias)
/ci-mockup-figure
Ci mockup figure
Create space-efficient paper and proposal figures (HTML mockups, TikZ, or skia-canvas) from tool selection through LaTeX insertion
/editable-figure
Editable figure
Design concise overview, mechanism, or workflow figures as editable PowerPoint objects
/implement-review
Implement review
Run the implement-review staged-change review loop
/my-router
My router
Detect the work type (papers, proposals, code, figures, admin) and dispatch to the right domain skill
/prun
Prun
Run prun: parallel delegation fan-out on Agy workers (the session coordinates)
/readme-polish
Readme polish
Audit a GitHub README and rewrite it with modern patterns for a scannable ten-second skim
Persistent session memory for AI coding agents — local-first, with on-device inference, associative recall, and drift detection. Works with Claude Code, Cursor,…
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16 views 0 likes💼 One MCP server to search job boards and company career sites
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28 views 0 likesGive your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
12 views 0 likesBrowser Harness | Self-healing harness that enables LLMs to complete any task.
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15 views 0 likesAgenta is a workspace where you and your team build agents and automations.
16 views 0 likesTerminal Director. One lightweight app, eight features, your whole dev workflow in a single window.
15 views 0 likesAI turns documents or topics into real, native PowerPoint decks—with native shapes, transitions and animations, data-backed charts and tables on demand, audio n…
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