LLM Mart Basic
@llm-mart · Joined Jun 2026
Triage a fetched PR review with the user, comment by comment, drafting each reply and producing a REQUIREMENTS file for the accepted code changes. Takes the PR-REVIEW file produced by fetch-pr-review. Invoke manually only.
Refine a development ticket — or brainstorm a raw idea — into a validated, self-contained REQUIREMENTS document — the "what", verified against the codebase. Invoke manually only.
Assist a human reviewing a pull request or branch locally — diff a source branch against its target (auto-detected or from a PR link) and return concise, human-voice review comments with file and line locations. Read-only, never posts.
Triage a ticket or ticket set before work starts — compare it against the codebase and save a review covering verdict, feature walkthrough, and only the high-cost questions worth raising.
Run nx format, lint, test, and build on affected or specified projects, then fix unambiguous failures
Capture durable user feedback into the governing skill/doc, or propose creating a new skill when no suitable one exists, so future sessions don't repeat the mistake. Use when the user rejects, reverts, or overrides the agent's output or approach on something a skill/doc covers or
Self-review a changeset until merge-ready — a fresh-context reviewer checks it as a maintainer would, the author answers every finding, and a compact report for the PR proves the review happened.
Split a plan into small, individually reviewable tasks grouped into PR-sized batches, appended as a task section at the end of the plan file.
Voice rules for text published under a person's name and read as if a person typed it, such as chat replies, PR comments and descriptions, commit messages, review replies, and code comments. Defines the wording only, never the content.
Verify the engineer is ready to implement a feature — a teach-back conversation over a .TICKET-REVIEW.md where they explain the feature in their own words and the agent probes and corrects.
1:1 rebuild of award-winning creative websites (WebGL / scroll-animation / portfolio sites). Evidence-driven pipeline - mirror-first forensics, line-number-traceable reverse engineering of minified bundles, verbatim porting, quantitative verification gates. Use when user asks to
Use when auditing a specific page's SEO performance, content quality, and competitive position. The agent fetches the URL, Googles the primary keyword, reads the top 3 competitors, and produces a full 7-dimension audit — no exports, no analytics access required.
Use when planning a new article. The agent Googles the keyword, reads the top 10 results, classifies intent, maps the content gap, and produces a writer-ready brief with structure, outline, and on-page artifacts. No keyword tool required.
Use when writing a complete SEO article. Includes the full anti-AI-slop ruleset (banned vocabulary, banned phrases, banned structural patterns) and voice rules. The agent researches the SERP itself if needed — no keyword data exports required.
Use when rewriting or refreshing an existing page that's underperforming. The agent fetches the URL, analyzes the current content, researches the SERP, and rewrites using the full anti-AI-slop ruleset — no data exports needed.
Use when planning to rank for a specific keyword. The agent Googles it, reads the top 10, classifies intent, reads the top 3 competitor pages, and produces a 90-day ranking plan with intent, SERP analysis, and content recommendations.
Use when a page ranks for a keyword but isn't in the top 3 and you want to know exactly what's missing. The agent compares the page to the top-ranking competitors and produces a specific list of entities, subtopics, and relationships to add.
Use when auditing a page for E-E-A-T signals. The agent reads the page and scores Experience, Expertise, Authoritativeness, and Trustworthiness — then tells you exactly what to add to each dimension.
Use when planning a topic cluster (hub + spokes) for a new content area. The agent researches the space, identifies the hub topic, maps the spokes, and produces a specific content plan with internal linking strategy.
Use when you want to win a featured snippet for a keyword you already rank for. The agent checks the current snippet format, analyzes your content, and rewrites the relevant section to match what Google wants.
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.
/export
Export
Export a page or set of pages
/gaps
Gaps
What is missing from my understanding
/graph-export
Graph export
Export the graph for outside analysis
/graph
Graph
Report the shape of the graph
/handoff
Handoff
Prepare a handoff brief
/health
Health
Quick health check
/hubs
Hubs
Find pages that swallowed the graph
/index
Index
Rebuild the index
/ingest-chats
Ingest chats
Import an exported chat history
/ingest-highlights
Ingest highlights
Ingest book or article highlights
/ingest-mine
Ingest mine
Ingest your own finished work
/ingest-newsletter
Ingest newsletter
Ingest newsletters without duplicating
/ingest-paper
Ingest paper
Ingest an academic paper
/ingest-pdf
Ingest pdf
Ingest a PDF
/ingest-url
Ingest url
Clip and ingest a web page
/ingest-voice
Ingest voice
Ingest a voice note
/ingest-youtube
Ingest youtube
Ingest a video or podcast transcript
/ingest
Ingest
Ingest new material from raw/ into the wiki
/init
Init
Scaffold a new vault
/install
Install
Install the skills, commands and agents
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