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概要と使いどころ
Evaluate factual claims in AI-generated text and teach a lightweight verification habit. Use when a learner wants to fact-check an AI answer, identify uncertainty, choose appropriate independent sources, or practise critical AI literacy.
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。
Post a "what's changed since the last release" recap to the release Slack channel for final QA. Groups merged PRs by author and classifies each as feature / bug fix / task. Use when the user wants a release recap, a changelog since the last tag, or to prep QA before cutting a release from main.
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。
Probabilistic single-cell RNA-seq with scvi-tools — scVI for a batch-corrected latent space, scANVI for semi-supervised label transfer, and Bayesian differential expression. Reach for this skill to integrate scRNA-seq batches, embed cells for clustering, transfer annotations from a reference onto a query, or score differentially expressed genes per cluster. For spatial deconvolution / mapping use the cell2location, DestVI, or Tangram methods instead.
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。
Structure prediction for protein, nucleic-acid, and small-molecule complexes with Boltz-2 (Passaro & Wohlwend et al. 2025, github.com/jwohlwend/boltz). Reach for this skill to validate designed binders against a target, to co-fold a protein with a SMILES or CCD ligand, or to get an open-source AlphaFold3 alternative with optional binding-affinity prediction.
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。
Inverse-fold a protein backbone (PDB structure) into amino-acid sequence with ProteinMPNN (Dauparas et al. 2022, github.com/dauparas/ProteinMPNN). Reach for this skill to run sequence design on RFdiffusion backbones, to redesign one chain of a PDB while holding interface residues fixed, or to generate a temperature-swept set of sequences for downstream folding.
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。
Inverse-fold a backbone with ligand, nucleic-acid, and metal context using LigandMPNN (Dauparas et al. 2023, github.com/dauparas/LigandMPNN). Reach for this skill to redesign the residues lining a binding pocket around a bound small molecule or cofactor, to design metal-coordinating sites where the geometry must be respected, or to get threaded designed-sequence PDBs out of any MPNN run.
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。
Structure prediction for protein, nucleic-acid, and small-molecule complexes with the Chai-1 foundation model (Chai Discovery 2024, github.com/chaidiscovery/chai-lab). Reach for this skill to predict an antibody-antigen or protein-ligand complex from a single FASTA, to re-fold designed binders as an AlphaFold-multimer alternative, or to drive co-folding from Python for batched campaigns on a GPU.
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。
Inverse-fold a backbone with SolubleMPNN — ProteinMPNN retrained on a soluble-PDB subset (Dauparas et al. 2022) — for sequences biased toward cytosolic expression and reduced aggregation. Reach for this skill when designs from vanilla ProteinMPNN are aggregating or going to inclusion bodies, when redesigning a membrane-adjacent fold for soluble expression, or when an E. coli expression screen is the next step.
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。
Predict small-molecule binding poses with DiffDock-L (Corso et al. 2023/2024, github.com/gcorso/DiffDock) — blind diffusion docking that places a ligand into a protein pocket without a predefined search box and ranks the samples with a learned confidence model. Reach for this skill to dock a SMILES or SDF against a PDB, to generate ranked 3D poses for a small fragment library, or to get a starting pose for downstream rescoring. DiffDock predicts geometry, not affinity.
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。
Predict protein structure for monomers and multimers with AlphaFold2 via the ColabFold runner (Mirdita et al. 2022, github.com/sokrypton/ColabFold; AlphaFold2 Jumper et al. 2021). Reach for this skill to fold a sequence or complex with the AF2/AF2-Multimer evoformer, to validate designed sequences by self-consistency pLDDT, ipTM, and RMSD, or to run a quick MSA-backed prediction using the public MMseqs2 server.
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。
Smart contract security audit — 10 DeFi bug classes (accounting desync, access control, incomplete path, off-by-one, oracle, ERC4626, reentrancy, flash loan, signature replay, proxy), pre-dive kill signals (TVL < $500K etc), Foundry PoC template, grep patterns for each class, and real Immunefi paid examples. Use for any Solidity/Rust contract audit or when deciding whether a DeFi target is worth hunting.
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。
External recon for software supply-chain attack surface — package-namespace squatting candidates, dependency-confusion vulnerabilities, GitHub Actions injection openings, container image registry exposure, SBOM mining, internal-package-name leakage, and CI/CD configuration exposure. Reconnaissance and identification ONLY — actual package publishing / typosquat attacks are EXTERNAL-OFFENSIVE and require explicit written sign-off because they can affect the entire npm/PyPI ecosystem. Use when the target has a public GitHub org, when their build artifacts/SBOMs are reachable, when their docker images are on Docker Hub/GHCR, or when you find internal package names in their JS bundles.
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。
Triage ASM/recon output for ownership before testing — separate the target's real assets from namespace-collision noise. Automated recon keyword-matches on the brand name, so for any target whose name is a common/dictionary word, the output is dominated by assets belonging to UNRELATED same-named companies (repos, cloud buckets, mobile apps, breach corpora, typosquats). Built from an authorized engagement where an ASM report's "Criticals" were overwhelmingly false positives and the combo/repos/mobile/bucket lists were polluted with unrelated same-named orgs. Use at the START of any engagement, immediately on receiving any ASM/recon/OSINT dataset, BEFORE testing anything.
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。
Comprehensive OSINT methodology for external red-team operations and authorized attack-surface assessments. Covers the 5-stage recon pipeline (seed discovery, asset expansion, enrichment, exposure analysis, reporting), asset-graph discipline with 29 asset types, severity rubric (CRITICAL/HIGH/MEDIUM/LOW/INFO), confidence upgrade workflows, time budgeting, asset-level triage rules, scale-based tactics, identity-fabric mapping (Entra/Okta/ADFS/Google/SAML/M365 Teams+SharePoint+OAuth), API and auth-map methodology, JavaScript deep analysis, mobile attack surface, cloud attack surface, breach×identity correlation, detectability tagging, detection-aware probing (back-off, persona rotation), read-only validator discipline, WAF/CDN bypass + origin discovery, vulnerability prioritization (CVE/EPSS/KEV), phishing infrastructure planning + pretext development, bug bounty submission templates, client deliverable templates with risk translation, threat-actor investigation (incl. RU/CN pivots), cryptocurrency tracing, image/video forensics, chronolocation. Use when planning or executing reconnaissance against authorized targets, mapping an organization's external attack surface, investigating a person/entity, tracing crypto flows, geolocating media, or performing attribution work.
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。
Operational arsenal for authorized external red-team and bug-bounty recon. Concrete probes, wordlists, regexes, dorks, curl one-liners for: subdomain enum, GraphQL/Swagger/REST discovery, identity fabric (Entra/Okta/ADFS/Google/SAML/M365 deep — Teams/SharePoint/OneDrive), cloud bucket enum (S3/GCS/Azure), CDN/WAF bypass, origin discovery, vendor fingerprinting (Citrix/F5/Pulse/Fortinet/PaloAlto/Cisco/VMware), CI/CD exposure, 48-pattern secret-scan catalog (AWS/GCP/GitHub/Stripe/Slack/Anthropic/OpenAI/Atlassian/DataDog/npm/PyPI), Postman workspaces, breach correlation (HudsonRock/HIBP/DeHashed/IntelX), TLS/JA3 audit, certificate transparency, JS endpoint extraction, package registry leaks, mobile/APK recon, sat imagery, sector-specific recon (healthcare DICOM, finance SWIFT, ICS/SCADA Modbus/BACnet). Detail content in 15 modular reference files, loaded on demand. Use for any authorized recon: scoping, asset discovery, attack-path mapping, secret triage, severity scoring.
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。
Hunting skill for ssrf vulnerabilities. Built from 15 public bug bounty reports including AWS metadata SSRF (HackerOne $25k Analytics PDF, Shopify Exchange $25k, Capital One 106M-record breach, Dropbox/HelloSign $4,913), GCP metadata SSRF (Snapchat $4k), Azure IMDS SSRF (Azure DevOps $15k chain, ChatGPT Custom Actions MSRC), DNS rebinding SSRF (Concrete CMS, GitLab UrlBlocker), gopher-protocol-to-Redis-RCE (Yahoo Mail $15k), link-preview SSRF (Reddit Matrix $6k), and headless-browser PDF-generator SSRF chains. Use when hunting SSRF on any target — OOB Collaborator confirmation mandatory for blind cases.
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。
Hunt shadow / zombie / undocumented API surface (OWASP API9 Improper Inventory Management) — enumerate the full API version history (v1/v2/beta/legacy paths, header- and subdomain-based versioning), pull and diff every reachable OpenAPI/Swagger spec (including ones only findable via the Wayback Machine), and behaviorally diff old vs. current versions for auth/rate-limit/validation regressions rather than just response-shape differences. Distinct from hunt-api-misconfig, which owns exploitation once you have a spec or endpoint (mass assignment, JWT, OData, Swagger-chain attacks); distinct from hunt-subdomain, which owns host-level discovery. This skill owns the version-inventory and behavioral-diff workflow itself. Use when the target has versioned API paths, multiple specs, a changelog referencing deprecated endpoints, or a mobile app whose hardcoded backend calls look older than the current web app's.
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。
Hunt SAML / SSO attacks. Patterns: XML Signature Wrapping (XSW) — modify Assertion while keeping Signature valid by relocating signed element, comment injection in NameID (admin@target.com<!--evil-->@attacker.com → some parsers see admin@target.com), signature stripping (remove Signature element entirely, server should reject but doesn't), key confusion (signed by attacker's IdP, accepted by SP), audience-restriction not validated, replay attack (same Assertion accepted twice within validity window). Tools: SAML Raider Burp extension, samlmagic, manual XML manipulation. Detection: any /saml endpoint, /Shibboleth.sso, /sso/saml/, Microsoft ADFS endpoints. Validate: account takeover via altered NameID, admin role injection via altered AttributeStatement. Use when hunting SSO flows, when SAML AssertionConsumerService is reachable, when chaining IdP-trust to SP-impersonation.
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。
Hunting skill for cache poison vulnerabilities. Built from 10 public bug bounty reports including X-Forwarded-Host poisoning, X-HTTP-Method-Override / GCS cache, reflected→stored XSS via cache, classic Omer-Gil Web Cache Deception, Cloudflare Cache Deception Armor bypass, session-token cache deception, Akamai hop-by-hop smuggling → server-side edge poisoning, and Kettle's 2024 path-normalization WCD against Cloudflare/Fastly/GCP. Host/X-Forwarded-Host injection that reaches app logic (reset-link poisoning, routing SSRF, OAuth issuer) is owned by hunt-host-header; this skill owns the case where the poisoned response is CACHED and served to other users. Use when hunting cache poisoning, Web Cache Deception, CDN-fronted apps.
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。
Hunt CI/CD pipeline vulnerabilities — GitHub Actions workflow injection (pull_request_target Pwnrequest + ${{ }}-into-shell), self-hosted runner poisoning, OIDC trust-policy abuse, Jenkins script-console RCE and CVE-2024-23897 file read, GitLab CI runner-token registration, Terraform state file leakage, artifact/log secret leakage, pipeline env-var disclosure. Use when target has a public GitHub/GitLab org, exposed CI dashboards (Jenkins/TeamCity/Drone/Argo), or build artifacts/images are reachable.
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。
Hunt MFA / 2FA bypass — 7 distinct patterns. (1) MFA not enforced on sensitive endpoints (password change, email change accept without MFA challenge), (2) MFA-step skip via direct navigation to post-login URL, (3) MFA-token replay (same code accepted twice), (4) brute-force the 6-digit OTP without rate limit (10^6 attempts at server speed), (5) race condition on OTP validation, (6) recovery-code dump via /api/me, (7) backup factor downgrade (SMS factor with no rate limit). Plus the chain: cookie theft + password oracle + no step-up = ATO without MFA challenge. Detection: trace auth flow in Burp, find every state transition, check if MFA is middleware-gated vs per-endpoint, check OTP entropy and rate limit on OTP-validate. Validate: attacker session reaching post-MFA state. Use when hunting auth bypass, MFA flows, chaining primitives toward ATO.
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。
Hunt fintech-specific GraphQL vulnerabilities: money-movement mutations (transfers, redemptions, withdrawals, card top-ups), ledger/balance/portfolio query IDOR, decimal-precision and rounding abuse, idempotency-key bypass enabling double-spend, KYC/PII field-level authorization gaps, and admin-override mutations reachable via mass assignment. Distinct from hunt-graphql, which owns generic GraphQL discovery and IDOR/mutation methodology — this skill owns the delta introduced when a GraphQL layer sits in front of a ledger, wallet, payments, banking, brokerage, or lending backend, where a resolver bug moves real money instead of just leaking data. Use when hunting a fintech, banking, payments, wallet, neobank, brokerage, or lending target that exposes a GraphQL API, or when a schema/response includes balance, transfer, ledger, redeem, quote, KYC, or account-linking fields.
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。
Local-tooling companion to the bug-bounty orchestrator — carries the SAME complete bug-bounty workflow, but reach for THIS variant when you also need to resolve where tools, wordlists, and clones are installed on the local machine (jhaddix, SecLists, trufflehog, ffuf, dalfox, ghauri); for pure orchestration/routing use the bug-bounty skill. Workflow it covers — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation gates, human-tone writing, templates by vuln class, CVSS 3.1, PoC generation, always-rejected list, conditional chain table, submission checklist). Use when you need the local install path of a tool / wordlist / clone for a hunt, or as the full-workflow variant when operating from this local toolkit; for general routing use the bug-bounty skill. 中文触发词：漏洞赏金、安全测试、渗透测试、漏洞挖掘、信息收集、子域名枚举、XSS测试、SQL注入、SSRF、安全审计、漏洞报告
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。
Hunt NTLM/Negotiate information disclosure on internet-reachable IIS/SharePoint/Exchange. Anonymous NTLM Type-2 challenge capture leaks NetBIOS domain, internal DNS forest, computer name, AD timestamp via AV_PAIRS structure. Default Windows-installer hostnames (WIN-XXXXXXXXXXX pattern) signal lazy provisioning. Use when target advertises `WWW-Authenticate: NTLM` or `Negotiate` headers anonymously.
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。