LLM Mart Basic
@llm-mart · Joined Jun 2026
Use this skill when you need to form evidence-based performance bottleneck hypotheses and validation steps; triggers include performance bottleneck analysis.
Use this skill when you need to compare performance evidence across versions and assess regression risk; triggers include performance regression analysis.
Use this skill when you need to interpret performance results, evidence quality, and risk without inventing conclusions; triggers include performance result analysis.
Use this skill when you need Gatling performance scope, simulations, or runnable entry points; triggers include Gatling, Gatling simulations, and Gatling performance testing.
Use this skill when you need to design JMeter test plans with Thread Groups, samplers, data sets, assertions, timers, CLI runs, and HTML reports; triggers include JMeter performance testing, performance testing, and performance-test-jmeter.
Use this skill when you need to model realistic performance workload, traffic, and acceptance assumptions; triggers include performance workload modeling.
Use this skill when you need to determine test impact from a pull request or code diff; triggers include PR test impact analysis.
Use this skill when you need to analyze production-incident evidence, impact, and follow-up actions; triggers include production incident analysis.
Use this skill when you need to plan or assess evidence-based production verification after a release; triggers include production verification.
Use this skill when you need to design safe prompt-injection tests for AI systems and tool boundaries; triggers include prompt injection testing.
Use this skill when you need to test prompt behavior, regression risk, and output boundaries across versions; triggers include prompt testing and prompt-regression.
Use this skill when you need to turn invariants, generation domains, and shrinking strategies into reviewable property-test candidates; triggers include 基于属性的测试 and property-based test design.
Use this skill when you need evidence-bounded quality dashboard audiences, decision questions, panels, drill-downs, freshness, and alert boundaries; triggers include 质量仪表盘 and quality dashboard.
Use this skill when you need evidence-bounded quality-debt items, origins, impact, age, priority, ownership, and paydown tradeoffs; triggers include 质量债务 and quality debt.
Use this skill when you need evidence-bounded entry criteria, evidence requirements, owners, and exception paths for a delivery or release gate; triggers include 质量门禁 and quality gate.
Use this skill when you need evidence-bounded quality-practice maturity dimensions, rubric anchors, evidence sufficiency, and improvement gaps; triggers include 质量成熟度 and quality maturity.
Use this skill when you need evidence-bounded quality metric definitions, calculation rules, data sources, freshness, and anti-gaming boundaries; triggers include 质量指标 and quality metric.
Use this skill when you need evidence-bounded quality and delivery metrics, denominators, attribution limits, gaming risk, and the Human-use boundary; triggers include 质量生产力 and quality productivity.
Use this skill when you need to identify and prioritize quality risks from product, change, and evidence inputs; triggers include quality risk analysis.
Use this skill when you need evidence-bounded grounding, relevance, completeness, citation support, abstention, and answer-level evidence in RAG outputs; triggers include RAG 质量 and RAG quality.
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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