699 件 ・ 関連度順
概要と使いどころ
Turn vulnerability notes, disclosure reports, PoCs, source code, or Codex Security findings into self-contained, sceptically validated, natural-sounding vulnerability reports. Use for one vulnerability or a disclosure campaign; a Codex Security scan is optional.
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。
Research why the TypeScript team made a specific typing decision. Use when evaluating whether ts-reset should override a built-in type, or when triaging issues that propose type changes. Searches the microsoft/TypeScript repo for relevant issues, PRs, and team comments.
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 a series of pre-release checks on the repo.
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 a Sandcastle GitHub issue and try to reproduce it with Docker. Use when given an issue number to triage or verify.
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。
Proactive threat hunt over web/application logs — no alert in hand. Profiles the corpus, runs a hypothesis-driven hunt loop with a mandatory written ledger, confirms suspects in source, detonates a local PoC, and writes INCIDENTS.json + INCIDENT_REPORT.md. Use when asked to "hunt the logs", "find the campaign", "look for signs of compromise", or "run dnr-hunt". The no-alert entry to the detection & response track; /dnr-respond is the lead-in-hand entry.
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。
Incident response workup for a lead in hand — an alert, an IOC, or a /dnr-hunt finding. Scopes the lead across the logs, verdicts whether the attack succeeded, quantifies blast radius, confirms root cause in source with a local PoC, and writes a proposed (never executed) containment/remediation/recovery plan. Use when asked to "respond to this alert", "work this incident", "how bad is this", or "run dnr-respond". /dnr-hunt is the no-alert entry to the same track.
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。
Performs graph-assisted triage of a single security finding, SARIF result, weAudit annotation, suspicious function, or report excerpt using Trailmark reachability, entrypoint paths, taint, privilege-boundary, blast-radius, caller/callee, and neighborhood evidence. Use when deciding whether one candidate issue is reachable, prioritizing a finding before PoC work, preparing evidence for exploit validation, or checking whether a static-analysis result is actionable.
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。
Penetration test and red team report writing methodology. Covers executive summary structuring (risk-led narrative for non-technical readers), technical finding format (title, severity, affected scope, narrative, reproduction steps, impact, remediation, references), CVSS v3.1 / v4.0 scoring with vector justification, OWASP risk rating, evidence hygiene (redacting credentials, hashing client data, time-stamping every action), screenshot and PoC artifact management, finding chain narratives, scope/limitations/assumptions documentation, retest evidence and remediation tracking, deliverable formats (PDF, DOCX, HTML, JSON for SIEM ingestion), client-customer-deliverable separation, and common report mistakes (over-CVSSing, undermining the triager, missing the 'so what'). Use at the end of an engagement when authoring a deliverable, when restructuring a draft for executive readability, or when establishing a reusable report template for a consulting practice.
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。
Turn vulnerability notes, disclosure reports, PoCs, source code, or Codex Security findings into self-contained, sceptically validated, natural-sounding vulnerability reports. Use for one vulnerability or a disclosure campaign; a Codex Security scan is optional.
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。
Build the effects of a fire skill as one visual language in Three.js. Flames that read as fire, not as orange fog or cones: ray-marched flame volumes whose turbulence rises with buoyancy (slow at the root, accelerating and stretching as it climbs) instead of scrolling, a temperature ramp from a white-hot core a little above the fuel through yellow and orange to deep red tips, broad brighter licks inside, walls of fire broken into clumps of separate tongues of very different heights with notches between them and licks that detach and go out, a fire whirl wound in helical sheets with a waist and a blue root; charcoal smoke drawn premultiplied over the frame and lit only by the fire (cauliflower billows for a burst, a thin streaked curtain off a grass-fire front, fibrous wisps off small fires, ragged hot cracks inside a burst's smoke); embers and sparks that drift on a curl field, cool from white through orange to red and fall as ash; heat haze as refraction; firelight shared with the world; a world-space heat map that makes the ground's needles smoulder as hairlines and its pockets breathe; and gentle ink impact frames limited to three flashes a second. Use for fire or flame skills, fireballs, fire waves or breath, rings of fire, fire tornadoes or whirls, burning ground, wildfire fronts, smoke columns, embers, smouldering aftermath, "fire and smoke", "realistic fire", "flame thrower", "inferno", "burning field" or "skill effects only". Includes a reusable module and a five-beat demo on a scanned CC0 burned-ground floor with failure-mode switches.
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。
攻防秘典索引。渗透测试、代码审计、红队攻击、蓝队防御、威胁情报、漏洞研究。安全研究全授权，零废话直出技术细节+PoC。当魔尊提到安全、渗透、攻防、红队、蓝队、漏洞时路由到此。
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。
Complete bug bounty workflow — 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 for ANY bug bounty task — starting a new target, doing recon, hunting specific vulns, auditing source code, testing AI features, validating findings, or writing reports. 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。
Complete bug bounty workflow — recon, pre-hunt learning, vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (ASI01-ASI10), A-to-B bug chaining, bypass tables, language-specific grep patterns, and reporting (7-Question Gate, 4 validation gates, CVSS 3.1, PoC generation, submission checklist). Use for ANY bug bounty task — recon, hunting specific vulns, auditing source code, testing AI features, validating findings, or writing reports.
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。
Use when the user wants to create or manage a Specialist agent or create, revise, publish, or delete a Skill through the conversational `/Customize` entry. Routes Skill work to the internal skill-creator and handles Specialist work through the JavaScript host.agents SDK.
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。
Compose one publication-grade multi-panel figure. Start from a one-line claim plus immutable data Artifact Version references, or inspect an existing figure and draft its outline directly. Plan a 12-column panel outline, delegate one worker per panel, compose and inspect the result, then run at most three adversarial review rounds while regenerating only affected panels. For a standalone plot use `figure-style`; for whole-paper figure ordering use `paper-narrative`.
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。
Inspect Open-Science's JavaScript control REPL, discover managed Project files, Sessions, and Agent Frames, and safely feature-gate host.* calls with host.capabilities(). Use when an Agent needs to discover available host APIs, locate an Artifact or Upload Version, diagnose a Session, or read a Frame transcript in the current Project.
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。
Publication-grade correctness and legibility rules for final-deliverable scientific figures, not exploratory plots. Use for a figure that will ship in a report, paper, export, or kept artifact. Covers data fidelity, label economy, color threading, chart choice, layout, and render-then-verify QA without imposing a visual house style. For multi-panel composition use `figure-composer`; for whole-paper ordering use `paper-narrative`.
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。
Embed proteins with Meta AI's ESM-2 (`fair-esm` package). Use this skill when: (1) Extracting per-residue or per-sequence embeddings for downstream ML, (2) Masked-LM likelihood / mutation effect scoring, (3) Contact prediction from a sequence.
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。
Score, embed, and generate DNA sequences with Evo 2, a long-context genomic foundation model. Use this skill when: (1) Computing per-nucleotide or per-sequence likelihoods for variant effect scoring, (2) Embedding genomic windows for downstream classification, (3) Generating DNA conditioned on a prefix, (4) Scoring regulatory or coding regions across species.
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 therapeutic indication dossier. Covers the patient population, epidemiology, disease biology, standard of care, regulatory precedent, and landmark clinical trials.
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。