테스트·보안 스킬

Audit an existing sitemap.xml / robots.txt or generate new ones following sitemaps.org protocol and Google Search Central guidance, with a growth-first default that allows every crawler including AI search and AI training bots. Use this skill whenever the user asks to "build a sitemap", "generate sitemap.xml", "audit the sitemap", "refresh sitemap", "write robots.txt", "check robots", "allow AI crawlers", "block AI crawlers", "fix crawl budget", "submit to Google", or any other discovery / indexing configuration task. Output is a valid sitemap.xml (or sitemap index) and/or robots.txt, plus a written audit when auditing.

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Audit on-page SEO and GEO (generative engine optimization) signals across the site — title tags, meta descriptions, H1/H2/H3 hierarchy, canonical tags, Open Graph, structured data, content length, internal link density, and AI-citation readiness. Use this skill whenever the user asks to "audit SEO", "check metadata", "review titles and descriptions", "check heading structure", "run an SEO audit", "GEO audit", "check schema markup", "find SEO issues", or review any on-page signal affecting organic or AI-search visibility. Output is a prioritized issue list with per-page findings and fixes.

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Generate or audit an `/llms.txt` file at the site root that makes the site legible to LLMs and AI answer engines at inference time, following the llms.txt proposal (Jeremy Howard, 2024). Use this skill whenever the user asks to "build llms.txt", "create llms.txt", "generate llms.txt", "audit llms.txt", "make my site LLM-friendly", "expose the site to AI assistants", "let ChatGPT / Claude / Perplexity cite my site", "add an AI assistants index", or asks about `.md` companion pages for LLM consumption. Output is a valid `llms.txt` file (or an audit) plus optional `.md` companion page generation for top pages.

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Verify an open factory PR before human review - re-runs gates, checks the test proves the fix, checks scope and test tampering. Use when reviewing a factory PR, running the PR review routine, or asked to independently check a change.

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Inspect factory health, stale work, CI, security advisories, and recent run evidence without implementing fixes.

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Classify GitHub issues into the factory's live label queue and write an auditable snapshot. Use for backlog triage or a scheduled triage run.

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Scheduled health sweep that closes the factory loop - reads CI failures, recent commits, dependency and security advisories, and live queue labels, then files issues and writes an immutable run record. Use for the nightly or weekly monitor routine.

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Classify incoming issues into the live GitHub label queue, reproduce where cheap, and write an auditable QUEUE.md snapshot. Use when triaging a backlog, running the scheduled triage routine, or deciding what the factory should pick up next.

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Independently verify a factory pull request, including fail-closed gates, negative test proof, scope, and load-bearing review.

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Companion to atlas-contract. Auto-invoked by its Final Audit on caught drift; also use after Post Reviews or user requests to record a mistake. Distills drift into WHEN/DON'T/INSTEAD clauses, writes t

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Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.

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Generates production-grade Appium mobile automation scripts for Android and iOS in Java, Python, or JavaScript. Supports real device and emulator testing locally and on TestMu AI cloud with 100+ real

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Asset and IT register: serial, model, condition, assignee, location, purchase value, warranty expiry and return date, as CSV, SQL, JSON Schema or Notion on request. Use for asset audits.

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Implement secure API design patterns including authentication, authorization, input validation, rate limiting, and protection against common API vulnerabilities

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You are an API mocking expert specializing in realistic mock services for development, testing, and demos. Design mocks that simulate real API behavior and enable parallel development.

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Authorized security assessment of REST, GraphQL, WebSocket, and SOAP APIs: discovery, authentication and authorization flaws (BOLA/IDOR, JWT/OAuth), rate-limit testing, and a structured multi-phase me

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API security testing workflow for REST and GraphQL APIs covering authentication, authorization, rate limiting, input validation, and security best practices.

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XML-specified Android UI journey testing, interactive step execution, assertion verification, and JSON outcome reporting.

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Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.

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Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls.

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Use when comparing prompt changes against a fixed evaluation set: record actual model settings, required checks, missing results, judge limitations and case-level regression evidence.

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Harden AI/LLM deployments against prompt injection, data exfiltration, model theft, and supply chain attacks.

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Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

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Overview of six AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and p

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