LLM Mart Basic
@llm-mart · Joined Jun 2026
Annotate genetic variants (GWAS hits, eQTLs, rare variants) with ENCODE functional data to interpret non-coding variation. Use when the user has variants of interest and wants to understand their regulatory context, identify causal variants from GWAS loci, assess variant impact o
Comprehensive guide for visualizing ENCODE data including deeptools heatmaps, IGV screenshots, UCSC track hubs, and publication-quality plots. Use when users need to create visualizations of ChIP-seq signal, peak landscapes, genome browser views, or any visual representation of E
Make software health, failure, degradation, and recovery visible through useful observability and diagnostics. Use when adding logs, metrics, traces, health checks, alerts, incident signals, or operational feedback.
Inspect the real repository, environment, dependencies, and runtime evidence before designing or changing software. Use for greenfield construction, unfamiliar codebases, uncertain behavior, or any task where assumptions could create rework.
Reflect on failures, incidents, reviews, and completed software work to turn evidence into durable tests, guardrails, documentation, and process improvements.
Debug software by making failures visible, reproducing them, finding contributing causes, and adding durable regression protection. Use for bugs, failing tests, incidents, regressions, flaky behavior, and unexplained production errors.
Improve software continuously through small, safe, behavior-preserving changes that reduce maintenance cost. Use for refactoring, cleanup, technical debt, naming, duplication, dead code, or post-change polish.
Choose simple, maintainable software designs by removing speculative complexity, comparing alternatives, and making explicit tradeoffs. Use for architecture, API, data-model, dependency, and scope decisions.
Implement software through small, repeatable, integrated vertical slices with clear exit criteria and honest verification. Use when a design is understood and code needs to be built or changed.
Review software with careful attention to correctness, maintainability, security, operations, and meaningful detail. Use for diffs, branches, pull requests, architecture decisions, or final quality checks.
Author a greenfield build blueprint in four gated stages — business logic, tech stack, logic-to-stack mapping, and a phase plan — each requiring explicit user approval before the next. Use when building a new project or a substantial new subsystem from scratch.
Step 0 of consequential software work under Monozukuri. Classify the task, assess its risk tier, choose execute or sensei mode, and compose the sequence of Monozukuri skills and the Definition of Done for it. Skip for trivial one-line edits, pure questions, and throwaway scripts.
Clarify software goals, constraints, stakeholders, and risks before consequential design or implementation work. Use for greenfield ideas, ambiguous requirements, architecture decisions, or changes where misunderstanding would be costly.
Prevent software mistakes through strong boundaries, safe defaults, meaningful tests, and mechanically enforced invariants. Use for TDD, validation, schemas, authorization, edge cases, regression coverage, or reliability-sensitive behavior.
Prepare software for responsible release, migration, deployment, rollback, and handoff with evidence about compatibility, health, ownership, and recovery.
Use when creating or updating AGENTS.md files, .github/copilot-instructions.md, or other AI agent rule files, onboarding AI agents to a project, standardizing agent documentation, or when anyone mentions AGENTS.md, agent rules, project onboarding, or codebase documentation for AI
Record a decision, document existing code, or file a supplied research material. Modes: document decision (ADR, RFC, or rule), document code (spec, doc, guide, or scenario for existing behavior), document research (only when a finished report or one external material is already i
First-time Archcore setup. Wires the host (MCP config, hooks, CLAUDE.md/AGENTS.md managed block), measures the authored context the repo already holds, then composes a first-day seed — stack rule, run guide, data-model, integrations, config, entry points, public surface, a linked
Plan a feature or initiative through a computed route: the conductor derives the canon delta and assembles the document package — from a zero-document null route for small fixes to an umbrella PRD with one spec per capability for large initiatives. Modes, named as the first word:
The pre-merge review of a branch in a project that records its specs, decisions, and rules in .archcore/. Run this first for 'review my branch', 'review the changes before merge', or 'review before merge': it checks the changed code against the project's recorded canon and the ch
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.
/bloat-scan
bloat-scan
Scan for codebase bloat using 3-tier progressive analysis: dead code, duplication, God classes, and documentation waste.
/elegant-code-review
elegant-code-review
Review the current working diff against the elegant-code decision ladder and propose deletions, honoring the negligence floor.
/filter-log
filter-log
Suggest tier-1 filter commands for a log file before any compression or paste. Anchors on the log-debugging-hygiene module.
/optimize-context
optimize-context
Analyze and optimize context window usage using MECW principles
/unbloat
unbloat
Remove dead code, duplicate files, and unused dependencies with user approval at each step. Backs up before deleting.
/dismiss
dismiss
The ONLY way to stop the egregore. Human-initiated graceful shutdown that saves all state.
/install-watchdog
install-watchdog
Install the egregore watchdog daemon for automatic session relaunching
/status
status
Show current egregore state and progress
/summon
summon
Summon the egregore to autonomously process work items through the full development lifecycle. Runs indefinitely by default until dismissed.
/uninstall-watchdog
uninstall-watchdog
Remove the egregore watchdog daemon and clean up files
/gauntlet-curate
Gauntlet curate
Add or edit a knowledge annotation
/gauntlet-extract
Gauntlet extract
Rebuild the knowledge base from the current codebase
/gauntlet-graph
gauntlet-graph
Build, search, and query the code knowledge graph
/gauntlet-onboard
Gauntlet onboard
Start or resume a guided onboarding path
/gauntlet-progress
Gauntlet progress
Show challenge accuracy stats, weak areas, and streak
/gauntlet
Gauntlet
Run an ad-hoc gauntlet challenge session (5 questions, random scope)
/configure
configure
Interactive interface to enable/disable rules
/from-hook
from-hook
Convert Python SDK hooks to declarative rules
/help
help
Display help and documentation
/hookify
hookify
Create behavioral rules to prevent unwanted actions
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