LLM Mart Basic

Use when recent resolved feedback may reveal a broader recurring defect pattern across the project surface. Not for source-level feedback collection: use feedback-sweep.

Use when one named review viewpoint must run fix cycles until a fresh reviewer finds nothing. Not for multi-viewpoint review or remote, credential, publish, deploy, or irreversible changes.

Use when the user invokes this skill to generate targeted questions proving the author understands the change's codebase effect. Not for reviewing the change: use review.

Use when asked to review a pull request, examine code changes, find bugs, or audit a branch, in standard or depth mode. Not for an iterative review-and-fix loop: use audit-project.

Use when the user wants a per-finding visual walk through a diff or PR. Not for written review reports: use review. Not for codebase tours: use show-me.

Use when implementation must be checked against an authoritative specification, or during PR review for spec drift against checked-in specs. Not for spec updates: use spec-driven-implementation.

Use when the user runs /browser-qa for report-only QA results without entering a fix loop. Not for remote, credential, publish, deploy, or irreversible changes.

Use when asked to reproduce, profile, or verify CLI/TUI behavior. Produces a deterministic transcript or profile proof with session cleanup. Not for CLI design advice, use cli-for-agents.

Use when asked to verify or reproduce browser or Electron UI behavior with before-and-after evidence and no leftover processes. Not for remote, credential, publish, deploy, or irreversible changes.

Use when asked to prove coverage, find missing cases, or enumerate state, decision, requirement, or behavior space. Not for round-based or single-property tests: use askme, property-test-authoring.

Use when a complete product needs production-like acceptance evidence against documented acceptance criteria. Not for single-component evaluation or evaluation without documented criteria.

Use when verification is looping, would re-run untouched code, or duplicates an established proof. Not for tasks that require source or remote-system changes.

Use when a test surface needs behavior-guarding coverage raised to a configured target with mutation kill evidence. Not for line-coverage inflation without mutation proof.

Use when asked to initialize, scope, estimate, configure, validate, or optimize a mewt, muton, or mutation testing campaign before execution. Writes the TOML config. Not for running it: use the mewt CLI.

Use when a mutation campaign leaves surviving mutants needing triage. Classifies each as false-positive, missing-test, genotoxic, or removable. Not for setup: use mutation-campaign-configuration.

Use when a product surface must be tested against extreme or hostile worlds. Not for design disputes: use possible-worlds. Not for remote, credential, publish, deploy, or irreversible changes.

Use when property-based testing, theorem proving, or formal proof tactics require zero unproven properties. Not for remote, credential, publish, deploy, or irreversible changes.

Operate explicit orchestrator, implementer, validator, and scribe roles through a caller-selected agent runtime. Triggers: "agent-native factory", "role-shaped agent panes", "persistent workers".

Use an explicitly selected AGY runtime for one provided packet or fresh validator context. Triggers: "agy", "antigravity", "AGY evidence".

Run one caller-supplied Codex command non-interactively and capture evidence. Triggers: "run Codex headless", "capture Codex evidence".

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.

SonarQube 정적분석 실행 및 결과 조회. 코드 품질·보안 핫스팟·커버리지 확인 시 사용.

GitHub 이슈 #$ARGUMENTS 를 처리한다(이슈 우선 워크플로):

이슈/기획서 기준 SDLC 한 사이클(이슈→개발→테스트→검증→PR)을 사람 개입 없이 자동 실행.

GitLab 이슈 #$ARGUMENTS 를 처리한다(이슈 우선 워크플로):

이슈/기획서 기준 SDLC 한 사이클(이슈→개발→테스트→검증→MR)을 사람 개입 없이 자동 실행.

Invoke a repeated task with `/name`. File name = command name (`fix-issue.md` → `/fix-issue`).

Handle issue #$ARGUMENTS (issue-first workflow):

Renders the connection structure of the AGENTS.md ecosystem

Automatically runs one SDLC cycle (issue → development → testing → verification → PR/MR) based on an issue or spec, without human intervention.

Run SonarQube static analysis and check the results. Use to check code quality, security hotspots, or coverage.

Handle GitHub issue #$ARGUMENTS (issue-first workflow):

Automatically runs one SDLC cycle (issue → development → testing → verification → PR) based on an issue or spec, without human intervention.

Handle GitLab issue #$ARGUMENTS (issue-first workflow):

Automatically runs one SDLC cycle (issue → development → testing → verification → MR) based on an issue or spec, without human intervention.

Show Hermes planning-with-files status for the current project.

Start Hermes planning-with-files workflow in the current project.

بدء تخطيط الملفات بنمط Manus. إنشاء task_plan.md و findings.md و progress.md للمهام المعقدة.

Lock the current task_plan.md content with a SHA-256 attestation. Hooks then refuse to inject plan content if the file diverges from the attested hash, blocking silent tampering. Use --show to print the stored hash, --clear to remove the attestation. Available since v2.37.0.

Starte Manus-artige Dateiplanung. Erstelle task_plan.md, findings.md, progress.md für komplexe Aufgaben.

Self-check for the planning-with-files mechanisms that fail silently: plan resolution, hook injection, canonicalizer path shape, attestation state, install surfaces, and per-fire hook latency. Run it whenever hooks seem quiet or after installing on a new machine. Available since v3.6.0.

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Reliable AI Skill + MCP toolkit for agent-driven desktop CAD automation.

Curated real-world use cases for Hermes Agent — the self-improving AI agent from Nous Research. Backed by primary sources.

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MCP server and CLI tools for web search and crawling, built on SearXNG and Crawl4AI

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Roblox Studio macOS Window Capture Fix 2026: Real Screenshot Tool Instead of Magenta Playtest Glitch

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