1,292 件 ・ 関連度順
概要と使いどころ
Bug bounty workflow skill for program scope mapping, recon-to-report automation, deduplication against prior submissions, and high-signal reporting on HackerOne, Bugcrowd, Intigriti, YesWeHack, and self-hosted programs. Use to organize bounty work end to end while staying inside program rules.
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。
Identify and exploit default or weak credentials on web application login forms, admin panels, CMS backends (WordPress wp-admin, Joomla, Drupal), and embedded device management interfaces. Signals include framework fingerprinting (WhatWeb, Wappalyzer, Nikto), exposed admin paths from robots.txt/dirbusting, and weak password policy acceptance of "Password1" or "123456". Tools: Burp Suite Intruder, Hydra, Medusa, OWASP ZAP.
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。
Anti-debugging detection and bypass playbook. Use when reversing protected binaries that detect debuggers via ptrace, PEB flags, timing checks, or signal/exception handlers on Linux and Windows.
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 testing PyQt/PySide6 applications with pytest-qt - qtbot fixture, signal/wait patterns, mouse/keyboard simulation, dialog testing, model/view testing, threaded code testing, or manual debugging techniques
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 building cross-platform desktop apps with PyQt6 or PySide6 - hub for installation, project structure, signals and slots basics, and pointers to widgets, styling, dialogs, threading, and testing sub-skills
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 developing desktop applications with Qt in C++ - CMake setup, signals and slots, QThread and QtConcurrent, QML integration, model/view programming, Qt5 to Qt6 migration, or windeployqt/macdeployqt/linuxdeployqt deployment
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。
Identify and remove phrasing, structure, and word choices that signal AI authorship. Runs iterative passes through fresh voice-agent instances with the orchestrator acting as gatekeeper on every change. Use on a cover letter before submission, or on any prose that has to read as human-written.
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。
Supreme policy layer governing all agent behavior. Autonomy, one-line prompt interpretation, speed standards, emphasis signal processing, cross-skill coordination, done definitions, conflict resolution. Loaded every prompt.
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。
Captures and evolves user preferences with confidence levels. Maintains Voice of the Customer model with exact language, dissatisfaction and aspiration signals. Handles promotion/demotion, global vs project scoping, auto memory system, and Omi wearable data integration.
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。
Angular 17–19 standalone components, signals, built-in control flow, inject() DI, the resource API. Load when writing or migrating Angular components.
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。
SolidJS fine-grained reactivity — signals, effects, memos, stores, resources, control-flow components. Load when writing Solid components or reactive state.
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。
Qwik resumable framework - zero hydration, $ lazy boundaries, signals, Qwik City file-based routing, routeLoader$, routeAction$, server$ RPC, serialization rules
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。
CLI code review patterns. Use when reviewing CLI applications built with Commander.js, @clack/prompts, picocolors. Covers exit codes, signal handling, error messages, user experience, testing adequacy.
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。
CLI specification planning frameworks. Use when a spec touches a command surface, an interactive flow, config precedence, exit codes, or output modes. Covers flag contracts, prompt flow design, precedence tables, exit-code taxonomy, TTY/piped/JSON output, error text, signals, and cross-platform concerns.
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 what people have discussed in the last 30 days across high-signal public platforms. Use when the user asks for `/last30days`, recent trend research, competitive intelligence, market pulse briefs, or engagement-ranked synthesis from Reddit, Hacker News, GitHub, X, YouTube, Polymarket, and similar sources.
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。
Consult this skill BEFORE proposing a fix to any CLI gap or schema gap that touches evidence, trust magnitude, evidence types, evidence grades, the TM formula, or star-level promotion gates. Also read it whenever an issue mentions citations, stars, commits, contributors, views, reviewers, percentile, arxiv, github-stars-own, repo-own, social-signal, benchmark-result, peer-review, self-attestation, fusion-recipe, verifier-attestation, or proxy-containment — those are the 10 canonical evidence types and the raw inputs that feed their formulas. Also read it when asked whether a skill qualifies for a given star level (0★–6★): the Star Bar and promotion gates live in `META.md`, not in the TM methodology page. Reading both prevents proposing a calibration that satisfies the TM grade threshold but violates a Star Bar installability or link requirement.
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 1 of the Gaia evidence verification pipeline. Use this skill whenever you need to gather, consolidate, or refresh raw evidence for named skills in the registry. Trigger phrases: "collect evidence", "populate the data lake", "gather sources", "run ev-collection", "Phase 1", "compile the evidence index", "refresh the unified lake", "aggregate skill evidence", "build the evidence database". Also invoke as the first step before running ev-star-verification, ev-adversarial-audit, or ev-link-validation — nothing downstream is meaningful without a fresh, compiled index. Covers GitHub repo links, stargazer signals, YouTube showcases, arXiv papers, peer reviews, benchmark results, blog/newsletter posts, and self-attestation artifacts.
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。
Skippable Phase 0 of the Gaia evidence verification pipeline. Use only on declared need for higher-quality Stage-2 evidence: a promotion candidate, or a skill that gaia-meta-sweep flagged as under-evidenced. Given a skill id, source repo/context, and needed evidence types (benchmark-result, arxiv, peer-review, social-signal), it runs Firecrawl searches, scrapes top hits to markdown, and appends discovered sources into Phase 1 inputs. Missing benchmark evidence is recorded as benchmark-source candidates first, not direct scoring rows. Trigger phrases: "discover evidence", "find new evidence", "Phase 0", "run ev-discovery", "search for benchmarks/papers", "under-evidenced", "promotion candidate needs stronger proof". This is the ONLY ev-* skill that searches the web for NEW evidence; other ev-* skills aggregate or verify known sources. Requires Firecrawl to be usable (`firecrawl --status` authenticated OR FIRECRAWL_API_KEY set); skips gracefully when neither holds.
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。
Maintain Pulp's installed design-time agent capability manifest and public-surface ledger. Use when adding, removing, renaming, or materially changing public audio, MIDI, signal, timebase, or sequence APIs; registering a new algorithm for generators; changing capability support or deprecation state; or repairing agent-capabilities freshness, schema, fingerprint, tombstone, or installed-SDK 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。
Building and shipping a Forge app (Modular, Instrument, MIDI, FX, and the sequencer work to come) as a signed installer somebody else can actually use. Covers the seam between the Forge and Pulp repos, what a green signal does and does not prove, shipping the runtime rather than only the binary, and the wiring gaps that make a finished feature behave like a missing one.
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。
Explains DSP math concepts to developers who need the theory behind an algorithm. Use whenever the user asks how a signal-processing concept works, wants intuition behind a formula, or hits a math-shaped bug. Trigger on phrases like "how does a Fourier transform work", "explain z-transforms", "what is convolution", "why does my biquad ring", "what is windowing for", "what causes aliasing", or "how do I convert gain to dB". Also trigger when the user pastes DSP code and asks why it behaves a certain way.
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。
Library-agnostic Flutter/Dart code review checklist covering widget best practices, state management patterns (BLoC, Riverpod, Provider, GetX, MobX, Signals), Dart idioms, performance, accessibility, security, and clean architecture.
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 social media operations for B2B SaaS brand building and engagement. Use this skill to develop LinkedIn strategy, decide whether to run a LinkedIn newsletter and how to scope it, capture consented registrations from LinkedIn Events, check LinkedIn Live eligibility, manage Twitter/X presence, create YouTube content, engage on Reddit communities, decide whether and how to answer on Quora, build community, develop influencer and creator partnerships, vet a creator before paying them, start or fix a B2B podcast, book podcast guests and guest appearances, judge whether a podcast is worth appearing on when you cannot audit its numbers, write show notes and transcripts, run social listening (what are people saying about us, share of voice, brand monitoring, validated sentiment, alert thresholds, routing signals to the right owner), and execute organic social campaigns. Also triggers on: LinkedIn, LinkedIn newsletter, LinkedIn Events, LinkedIn Live, event registration form, subscribe to our newsletter on LinkedIn, marketing consent checkbox, Notify Employees, Twitter/X, YouTube, Reddit, community, influencer, creator partnerships, influencer vetting, engagement rate, fake followers, engagement pods, FTC disclosure, sponsored post disclosure, media kit, social media strategy, organic social, employee advocacy, podcast, podcast strategy, podcast guesting, how do I know if this podcast has real listeners, the host says they get 50k downloads, is this podcast worth going on, podcast RSS feed research, IAB podcast measurement certification, Listen Score, Apple Podcasts reviews, show notes, audiogram, episode transcript, social media account access, who has admin on our LinkedIn page, the person who ran our social accounts left, locked out of our company account, social media offboarding, YouTube channel owner, Slack primary owner, social account MFA, social media approval workflow, pause all scheduled posts, social listening, what are people saying about us, brand monitoring, brand mentions, share of voice, social share of voice vs competitors, sentiment analysis, is our sentiment dashboard accurate, listening query, boolean query, mention alerts, spike alert, CrowdTangle replacement, Reddit API access, which platforms can our listening tool see, someone on Reddit asked for a tool like ours, comment mining, voice of customer from social.
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。
Sales enablement, technical presales and deal acceleration for B2B SaaS revenue teams. Use this skill when planning outbound campaigns, running discovery calls, building deal strategy, creating battle cards, writing proposals, responding to RFPs, preparing a product demo, scoping a proof of concept or pilot, answering a security questionnaire or the AI annex buyers now attach to it, executing sales sequences, coaching qualification, or deciding what the website's AI chat agent is allowed to say. Also triggers on: outbound, cold outreach, reply handling, reply classification, out-of-office replies, auto-replies counted as replies, our reply rate is inflated, prospect replied remove me, opt-out by reply, is this list ready to send, launch readiness, CRM segment outbound, we emailed a current customer, outbound hit an open opportunity, ownerless leads, prospects engaging our competitors, competitor connections, displacement list, is this personalization creepy, can we mention they visited our site, signal freshness, deal strategy, pipeline, battle card, objection handling, common objections, why do we keep hearing this objection, mine call transcripts for objections, objection register, proposal, RFP, discovery call, MEDDPICC, sales sequence, qualification, sales engineer, solutions engineer, presales, demo plan, demo script, POC, proof of concept, pilot success criteria, technical evaluation, technical win, security questionnaire, vendor security review, SOC 2 questionnaire, AI security questionnaire, AI annex, AI vendor due diligence, the buyer is asking if we train on their data, do you train on customer data, which model do you use, model provider sub-processor, AI subprocessor disclosure, where does inference run, can the customer turn the AI feature off, AI-CAIQ, CSA AI Controls Matrix, ISO 42001, ISO/IEC 42001, NIST AI RMF, EU AI Act Article 50, are we a provider or a deployer, AI feature disclosure, our model vendor changed and nobody told the buyer, technical objection, mutual action plan, MAP, close plan, mutual close plan, buyer enablement, the deal is stalled, deal stalled after the demo, how do I get this deal to close, close date keeps slipping, JOLT, buyer indecision, no-decision loss, website chatbot, chat widget, AI chat agent, AI SDR, inbound AI SDR, conversational marketing, live chat, what should our chatbot be allowed to say, our chatbot quoted the wrong price, the bot promised a discount, do we have to disclose it is AI, EU AI Act chatbot disclosure, chatbot handoff to sales, chat transcript review, prompt injection on our chatbot, Drift, Qualified, Intercom.
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。