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Deep OSINT reconnaissance using the MITRE ATT&CK Reconnaissance framework. Email harvesting with SMTP verification, subdomain takeover detection, certificate transparency mining, Shodan/Censys intelligence, Wayback Machine historical analysis, social media profiling, cloud storage enumeration, document metadata extraction, DNS history, credential leak checks, and passive infrastructure mapping. Uses theHarvester, amass, dnsrecon, fierce, dnstwist, dmitry, whatweb, wafw00f, exiftool, metagoofil, smtp-user-enum, swaks, waybackurls, subfinder, and crt.sh. Pure reconnaissance — no active exploitation. Produces: confidence-scored findings, infrastructure diagram, employee roster, email pattern confirmation, subdomain takeover candidates. Chains into /pentester for active testing.

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Exploit AI applications using Indirect Prompt Injection. This skill focuses on hiding malicious instructions within data sources (web pages, documents, emails) that the LLM processes, causing the AI to execute unintended actions or leak data without direct user interaction.

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Generate sophisticated initial access payloads designed to bypass email gateways and endpoint antivirus systems while executing Command and Control (C2) agents. Use this skill to craft malicious LNKs, ISOs, Weaponized Office Documents, and HTML Smuggling techniques for Red Team campaigns.

日本語の概要は準備中です。原文の説明を表示しています。

Execute Indirect Prompt Injection attacks against Large Language Models (LLMs) by subtly embedding malicious instructions within external data sources (e.g., websites, documents, databases) that the LLM autonomously ingests. This forces the model to execute attacker-controlled commands under the guise of processing legitimate user requests.

日本語の概要は準備中です。原文の説明を表示しています。

GraphQL and hidden parameter testing playbook. Use when exploring introspection, batching, undocumented fields, hidden parameters, schema abuse, and GraphQL authorization gaps.

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Exploit CVE-2023-36884, a critical Remote Code Execution vulnerability in Windows and Office associated with the Storm-0978 APT. This skill covers the weaponization of malicious Word documents to achieve code execution upon opening, bypassing Mark-of-the-Web (MotW) defenses.

日本語の概要は準備中です。原文の説明を表示しています。

Exploit Document Object Model (DOM) Based Cross-Site Scripting (XSS) vulnerabilities. Unlike Reflected or Stored XSS, the attack payload is executed purely on the client-side as a result of modifying the DOM environment, often without the payload ever reaching the backend server.

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Identify and exploit Mass Assignment vulnerabilities in APIs. Use this skill when testing REST APIs or application forms that directly map user-supplied JSON or POST input to internal database objects. An attacker can inject undocumented variables (e.g., `is_admin`, `verified`) to illegally modify restricted properties.

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Systematically discover hidden Application Programming Interfaces (APIs), uncover undocumented endpoints (Shadow APIs), and fuzz parameters. Use this skill as the pivotal first step in API Bug Hunting, transforming a basic frontend application into a vast mapped attack surface.

日本語の概要は準備中です。原文の説明を表示しています。

API reconnaissance and documentation review playbook. Use when discovering endpoints, schemas, versions, OpenAPI specs, hidden docs, and surface area for API testing.

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Push committed changes and create a draft PR on GitHub. Use when you have staged changes ready to push and want to open a draft PR for early feedback or documentation.

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Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/PRD asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".

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Orchestrate a whole-registry sweep of Gaia — fan out 13 parallel audit agents across every skill, run adversarial verification, surface Semantic Fusion candidates, propose new generic skill references, and synthesize a publish-ready HTML report under docs/meta/reports/. Use this skill for broad, systemic analysis across many skills at once: "run a meta sweep", "sweep the meta", "full meta audit", "audit the whole registry against META.md", "widespread nomenclature issues", "find all skills missing a GitHub link", "produce a meta report", "check for evidence type mismatches across the registry", "find skills that document a third-party tool with no attribution", or explicitly types /gaia-meta-sweep. This is the registry-wide macro companion to /gaia-meta-audit (a prioritized queue, single-pass) and /gaia-audit (fixes one skill). Use it when you need the full surface — 13 audit dimensions, adversarial verification, fusion proposals, and a durable findings artifact — not just a queue.

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Regenerate and commit Class S site-served artifacts after registry changes, then sync documentation across the main repo and the adjacent wiki. Use this skill when: you've changed registry/nodes/, registry/named/, or named-skills.json and need to regenerate docs/graph/* so the live website reflects the update; CI Guard E (docs-cohesion.yml) is failing because Class S artifacts are out of date; someone says "sync the docs", "regenerate docs", "run gaia dev docs", "update the site graph", "commit the Class S artifacts", "website is stale", or "update the wiki"; or you're finishing a registry PR and need to ensure docs/graph/gaia.json, docs/graph/gaia.gexf, docs/graph/gaia.svg, and docs/graph/named/index.json are committed alongside the source change. Also covers updating README.md, docs/index.html, and mirroring changes to the adjacent wiki repo at ../gaia-wiki.

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Conduct digital forensics investigations — evidence acquisition, timeline analysis, and court-ready documentation.

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Build and govern scalable design systems with tokens, components, documentation, and adoption strategy.

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Research libraries and APIs automatically by pulling live documentation into the agent's context before answering. Use when writing code against unfamiliar or fast-moving libraries so examples match current versions.

日本語の概要は準備中です。原文の説明を表示しています。

Perform business analysis — requirements gathering, process mapping, gap analysis, and stakeholder-ready documentation.

日本語の概要は準備中です。原文の説明を表示しています。

Design tools for AI agents — clean function interfaces, typed schemas, informative errors, idempotency, and tool documentation. Use when giving an agent new capabilities or fixing flaky tool use.

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Build data-centric LLM applications with indexing and retrieval frameworks — document ingestion, indices, query engines, and RAG pipelines. Use when the core problem is getting the right data in front of the model.

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Execute a project from a folder of raw materials. Use when the user drops messages, screenshots, documents, drafts, and references into a project directory and wants Codex to identify the real goal, build a plan, do the work, drive the project to a submission-ready state, verify completion, and return a clear final summary of what was required, what was completed, and how it was done.

日本語の概要は準備中です。原文の説明を表示しています。

Plan a feature before writing any code. Use this skill at the START of non-trivial feature work — when the user says they want to "add", "build", "implement", "create", "develop", or "ship" a feature, endpoint, component, page, service, or capability. Especially trigger when the user's prompt is short or under-specified ("add a dashboard", "build an auth flow", "let's do user activity reports") — those need planning, not direct execution. The skill walks through requirements clarification, codebase exploration, sketches a Mermaid architecture/flow diagram of the proposed design, and produces a plan.md document the user can hand off to a fresh AI session for execution. Skip only when the change is genuinely trivial (typo fixes, single-line tweaks, renames). When in doubt, plan.

日本語の概要は準備中です。原文の説明を表示しています。

Study unfamiliar codebases and produce evidence-backed knowledge artifacts. Use for repository orientation, architecture mapping, subsystem tracing, onboarding, or codebase documentation.

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This skill enables GitHub repository documentation exploration using DeepWiki API directly via curl. Use when researching repository structure, understanding library APIs, or asking questions about open-source projects. MCP server not required.

日本語の概要は準備中です。原文の説明を表示しています。