「eal」の検索結果

Review the retained annotation candidate queue and curate per-coin editorial history. Use weekly during active event periods, monthly otherwise, or on queue-health warnings; this does not restore the retired live chart overlay.

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。

RSA attack playbook for CTF and real-world cryptanalysis. Use when given RSA parameters (n, e, c) and need to recover plaintext by exploiting weak keys, small exponents, shared factors, or padding oracles.

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 Server-Side Request Forgery (SSRF) vulnerabilities in applications hosted on AWS to access the highly sensitive Instance Metadata Service (IMDS). This allows an attacker to steal valid IAM roles and temporary security credentials, leading to catastrophic cloud account compromise.

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 weak password reset and change flows via CSRF on reset forms, cross-user password modification by swapping username parameters, token predictability in reset links, reset displaying old password in plaintext (revealing weak storage), missing current-password verification on change forms, and session hijacker lockout via passwordless change. Test with Burp Suite, OWASP ZAP following OWASP Forgot Password Cheat Sheet.

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 advanced network scanning and service enumeration using Nmap for penetration testing and security assessments. Use this skill when conducting network reconnaissance, port scanning, service version detection, OS fingerprinting, and vulnerability scanning. Covers stealth scanning, firewall evasion, NSE script usage, and network mapping for infrastructure penetration tests.

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。

Linux kernel exploitation playbook. Use when exploiting kernel vulnerabilities (UAF, OOB, race condition, type confusion) for privilege escalation via commit_creds, modprobe_path overwrite, or kernel ROP chains in CTF and real-world scenarios.

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。

Test organizational egress controls by executing various data exfiltration techniques during a red team engagement. Use this skill to simulate an adversary attempting to steal sensitive data without triggering DLP (Data Loss Prevention) or network monitoring alerts. Covers exfiltration over DNS, ICMP, HTTP/S, alternative protocols (SSH/FTP), cloud services, and physical methods.

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。

Simulate supply chain and adversarial machine learning attacks by injecting poisoned data or targeted backdoors into training and fine-tuning datasets. Use this skill when assessing the integrity controls of MLOps pipelines or evaluating the resilience of AI models against highly targeted, stealthy manipulation intended to alter model behavior on specific triggers.

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 and analyze malware samples within a highly controlled, instrumented sandbox environment to observe their true behavior, network communications, file system modifications, and registry changes in real-time.

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。

Covers object-level authorization bypass in GraphQL APIs where introspection reveals hidden fields or mutations that accept arbitrary user/resource IDs without ownership checks. Trigger on keywords like "GraphQL", "query", "mutation", "introspection", "resolver", "node ID", "relay", "object type", "schema", "batching", or "alias". Applies to dual-stack REST+GraphQL apps, Relay-style global IDs, and unauthenticated resolvers.

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。

Systematically extract hidden system prompts, core directives, and invisible context intentionally concealed within Large Language Model (LLM) applications. This skill utilizes targeted linguistic engineering and boundary manipulation to bypass prompt opacity.

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。

AI/ML security playbook. Use when assessing model supply chain attacks (pickle RCE, poisoned weights), adversarial examples, model poisoning, model stealing, data privacy attacks (membership inference, model inversion), and autonomous agent security risks.

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。

Phase 4 of the Gaia evidence verification pipeline. Checks every URL in the evidence data lake for HTTP liveness — catches dead links (404, 403, timeout, connection errors) before evidence is ingested into the registry. Use this skill when running the full /ev-pipeline, asked to "validate links", "check evidence URLs", "run link validation", "find dead links in the data lake", "check HTTP status of evidence sources", or "verify evidence links still work". Wraps validate_sources.py as a temporary coexistence URL-health shim.

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。

Generate a prioritized review queue of registry skills and catalog items that need attention. Use this skill whenever someone asks: "what needs review?", "what's overdue for audit?", "where are the weak spots in the registry?", "what should I audit next?", "run a health check on the registry", "show me flagged skills", "find problems in the registry", "what skills need fixing?", or "triage the registry". This is the triage layer — it surfaces candidates ranked P0–P4 so that focused work (via /gaia-audit) targets the right things first. Run this before any audit pass. Also invoke proactively when a PR changes registry/named/ at scale, or before a release, to catch regressions early.

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。

Canonical entry point for the full Gaia evidence verification pipeline. Invoke as /evidence-verification-pipeline or /ev-pipeline — both names trigger this skill. Use whenever you need to run the evidence phases end-to-end: collecting raw evidence from the data lake, verifying live GitHub star counts, running Phase 2B benchmark-source verification, running adversarial auditing for noise and URL errors, and checking link health via Firecrawl. Also use when someone says "run the evidence pipeline", "verify the evidence lake", "audit evidence", "run ev-pipeline", "full evidence check", "pipeline run", "prepare evidence for ingestion", or "refresh the data lake". This is the pre-ingestion step — run it before importing any evidence into the registry.

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。

Curate Gaia bot crawler branches into real-skill catalog entries and clean up processed bot/* branches. Use when the user says: "process bot branches", "curate the crawl output", "clean up bot proposals", "run bot curation", "merge the crawler results", "review bot/* branches", "ingest crawler data", or explicitly types /gaia-bot-curate. Also triggers when the user asks to review pending `bot/*` branches, turn crawler JSON proposals into registry nodes, decide which crawled skills to accept vs reject, or batch-add skills from an automated crawl run. This skill handles the full pipeline: fetch remote bot branches, triage proposals, run `gaia dev` mutations, validate, open a PR, and delete consumed bot branches.

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。

Discovery-only Gaia curation for one manually selected source page. Fetches and normalizes up to five real SKILL.md candidates, deduplicates and maps them for human L4 review, then stops without evidence scoring or registry mutation.

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。

Focused single-target audit of one Gaia skill, named skill, or real-skill catalog item. Use this skill when: auditing a specific skill by ID or name, a skill looks overpromoted, evidence feels thin or dead, a contributor's skill seems outdated or superseded, the rank doesn't match the source quality, evidence is mapped to the wrong Evidence Type, a skill at 3★+ is missing a working GitHub link, someone asks "does this skill deserve its stars?", or you want the smallest possible correction with validation — not a bulk sweep. This is NOT for bulk curation passes (use /gaia-curate for that) or meta-level registry sweeps (use /gaia-meta-audit). It is specifically for "fix this one skill, get it right."

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。

Use this skill whenever the user wants to see how their branch will look on the live Gaia website before merging — "preview this branch", "show me what this looks like", "deploy a preview", "trigger a design preview", "can I see the site with these changes", "preview the skill profile", "check how this renders on the site", "spin up a preview deployment". This skill dispatches a Cloudflare Worker preview deployment for the current branch via GitHub Actions — no local build tooling required. Ideal for containerized environments, design reviews, and confirming that newly curated skills or profile pages render correctly before a PR is merged to main. The preview does NOT regenerate docs; it deploys `docs/` from the branch as-is. If your change depends on regenerated Class S artifacts, run `gaia dev docs` and commit those first — the preview then reflects them.

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。

Craft UI animations with Framer Motion: page transitions, micro-interactions, scroll reveals, and shared layouts for polished interfaces. Use for interface animation beyond basics.

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。

Elasticsearch search and analytics — mappings, queries, and cluster health — use when building search or log analytics.

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。

Electronic health record analysis — phenotyping, missingness, bias, and observational study design with EHR data.

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。

Run customer success — onboarding, health scoring, retention plays, expansion, and churn prevention.

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。

Get productive with agentic coding assistants — task framing, iterative prompting, file-scoped workflows, review loops, and multi-file refactors. Use when pairing with an AI coding agent on real codebases.

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。