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「sse」の検索結果

8,051 件 ・ 関連度順

概要と使いどころ

Audits whether a machine-readable regelrecht law model is faithful to the LETTER of the wettekst — and strictly separates the wettekst (leading) from the toelichting (Nota/Memorie van Toelichting; explanatory, not a norm). Runs in critical passes per article/lid and detects four deviation classes: toelichting-bleed (a modeled criterion that the letter only states as an open norm, or not at all), missing verbatim elements (a word/condition such as a "tenzij" or a qualifier dropped from the model), wrong legal_basis anchoring (an endpoint hung on a "kapstok"-article while the operative norm lives elsewhere), and verbatim-drift in text: (an ingetrokken/older redaction). Also detects positief-lid vs uitsluitings-lid conflicts and checks the chapeau for an explicit derogation rule ("zo nodig in afwijking van het eerste lid") before judging precedence. Classifies every finding as modelfout (fix), wettekst-gevolg (report, do not fix), or letter-vs-toelichting-question (jurist decides what is leading + revision signal). Use when the user wants to know if a model is "dicht bij de letter", mentions letter vs toelichting/bedoeling, fidelity, "natuurgetrouw", or before trusting feature outcomes.

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。

NederlandseDigitaleDienst/regelrecht252026年10月17日 更新

outreach

無料

Open the warm channel for a role the pipeline already assessed. Finds who the user already knows at the company, researches named targets from public professional presence when they know nobody, grades each path honestly, drafts the ask through the voice agent, and writes the contacts into the Referrals table in job_search.md.

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。

VonTerraProject501c3/slushpile252026年8月17日 更新

Map existing business processes using BPMN 2.0 notation or simplified swimlane diagrams. Identify waste, handoffs, decision points, and improvement opportunities using Lean principles (8 Wastes). Use when documenting workflows for SOP creation, automation assessment, or process improvement. Do not use for software architecture diagrams — use architecture tools 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。

hoavdc/CodexKit252026年10月11日 更新

Assess organizational readiness for financial audits (internal or external). Map assertions to account balances, check evidence completeness, score readiness using a Red/Amber/Green framework, and generate a remediation timeline. Aligned with SOX, IFRS, and GAAP audit standards. Use before scheduled audits or when preparing for first-time compliance.

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。

hoavdc/CodexKit252026年10月11日 更新

Turn launch dates, campaign inputs, and asset requests into a structured content calendar and workback plan. Use when the work is recurring marketing coordination and schedule packaging. Do not use for brand strategy, positioning design, or deep performance interpretation.

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。

hoavdc/CodexKit252026年10月11日 更新

Use this agent when you need to review UniProt annotation rules (ARBA, UniRule) for quality, biological accuracy, and GO annotation appropriateness. This agent performs comprehensive analysis of rule condition sets, evaluates literature support, assesses taxonomic scope, and recommends curation actions.

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。

ai4curation/ai-gene-review242026年10月17日 更新

aiohttp

無料

Use when building Python async HTTP services or clients with aiohttp - web server routing, middleware, WebSocket, SSE, streaming, client sessions, pytest-aiohttp testing, or troubleshooting SSL and timeout issues

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。

CodeAtCode/oss-ai-skills242026年10月9日 更新

Use when developing Thunderbird MailExtensions - Manifest V2/V3 configuration, messenger.* APIs for accounts, messages, folders and compose, UI actions, message display scripts, Experiment APIs, ATN submission, or migration from legacy extensions

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。

CodeAtCode/oss-ai-skills242026年10月9日 更新

Essential fuzzing payloads: SQL injection, command injection, special characters. Curated essentials for vulnerability testing.

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。

ShulkwiSEC/bb-huge232026年7月11日 更新

Utilize Shodan, the search engine for Internet-connected devices, to discover exposed assets, vulnerable ports, default credentials, and specific infrastructure configurations using advanced search queries (dorks).

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。

ShulkwiSEC/bb-huge232026年7月11日 更新

Test Model Context Protocol (MCP) servers and tool-calling systems for security vulnerabilities including tool injection, parameter manipulation, privilege escalation, and data exfiltration through AI agent tool interfaces. Use this skill when assessing MCP server implementations, AI agent tool integrations, or any system that exposes tools to language models. Covers tool confusion attacks, cross-tool exploitation, and MCP server hardening assessment.

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。

ShulkwiSEC/bb-huge232026年7月11日 更新

Internal network assessment. VLAN hopping, ARP spoofing detection, broadcast protocol abuse (LLMNR/NBT-NS/mDNS), network segmentation verification, SNMP enumeration, NFS exposure, router/switch audit, and internal service mapping. Assumes attacker has network access. Uses nmap, arp-scan, nbtscan, snmpwalk, onesixtyone, smbmap, nfs-common, masscan, hping3, and netexec.

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。

ShulkwiSEC/bb-huge232026年7月11日 更新

Test for indirect prompt injection vulnerabilities where malicious instructions are injected through external data sources (websites, emails, documents, database records) that the LLM processes. Use this skill when assessing LLM-integrated applications that process user-generated content, retrieve web pages, parse emails, or read documents. Covers injection via web content, email bodies, user profiles, and database records that are fed to LLM context.

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。

ShulkwiSEC/bb-huge232026年7月11日 更新

Exploit advanced HTTP Request Smuggling combining Transfer-Encoding vulnerabilities (TE.TE). By obscuring the Transfer-Encoding header, an attacker forces desynchronization between a frontend proxy (which processes the request one way) and the backend server (which processes it another way), allowing the smuggling of malicious requests to bypass security controls or poison caches.

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。

ShulkwiSEC/bb-huge232026年7月11日 更新

Penetration test AWS cloud environments for misconfigurations, privilege escalation, data exposure, and lateral movement. Use this skill when assessing AWS accounts for security weaknesses including S3 bucket misconfigurations, IAM policy flaws, EC2 metadata exploitation, Lambda function abuse, and cross-account attack paths. Covers both external and authenticated AWS pentesting.

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。

ShulkwiSEC/bb-huge232026年7月11日 更新

Test APIs for authentication and authorization bypass vulnerabilities including JWT manipulation, OAuth2 flaws, API key leakage, broken authentication, and token forgery. Use this skill when assessing REST/GraphQL APIs for access control weaknesses, session management flaws, or credential handling issues. Covers JWT algorithm confusion, OAuth redirect manipulation, and rate limit bypass.

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。

ShulkwiSEC/bb-huge232026年7月11日 更新

Analyzes CVE vulnerabilities in project dependencies with code path tracing and PoC generation for Burp Suite. Traces vulnerable code from user input to sink, assesses exploitability, and generates HTTP requests for testing.

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。

ShulkwiSEC/bb-huge232026年7月11日 更新

Prepare flawless design-to-development handoffs with specs, assets, behaviors, and QA processes.

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。

aicodedecode/awesome-muse-skills232026年10月10日 更新

Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.

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。

shalintripathi/saas-marketing-agents232026年10月16日 更新

Post-mortem analysis of a PhysicsIntern workspace run (Claude Code, Pi, Codex, or OpenCode host). Reconstructs the trajectory from the session record — JSONL file(s) for Claude/Pi/Codex, the SQLite store for OpenCode — audits methodology adherence against the workspace's own CLAUDE.md / AGENTS.md and skill/agent prompts, checks commit discipline and flag dispositions, and assesses substantive quality. Produces a thorough evidence-anchored markdown report. Use after a workspace has been worked on to identify what went well, where the methodology slipped, and what prompts to improve.

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。

huggingface/physics-intern232026年7月1日 更新

checkpro

無料

Audit essays, reports, literature reviews, dissertations, proposals, and source-backed assignments for high-score academic quality. Use when the user asks whether a paper can get a high grade, wants teacher/rubric feedback addressed, needs a pre-submission review, or needs checks for strict rubric compliance, academic standards, prompt/rubric alignment, argument quality, comparative analysis, evidence hierarchy, table/figure integration, citation specificity, conclusion strength, academic language, source-claim integrity, or evidence boundaries.

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。

zxzin/runpro232026年7月19日 更新

Use when the user wants their way of working with Claude assessed — "review my session", "how am I using Claude Code", "audit my setup / workflow", "am I following best practices", "coach me", "what should I improve" — or pastes a Claude.ai/Cowork/Tag transcript and asks how they could have worked better. Do NOT use for reviewing code changes (that is code review) or for teaching a product from scratch (use academy-learn); this skill only reviews how the human works with Claude.

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。

MrMarudi/academy-coach232026年8月24日 更新

Detects packing and encryption by measuring Shannon entropy across a binary's sections and regions: flagging high-entropy executable sections, entropy spikes, and size/raw-vs-virtual anomalies that indicate compression or encryption. Activates for requests to measure entropy, detect packing, or assess whether a sample is compressed/encrypted.

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。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Uses Ghidra to disassemble and decompile a binary, navigate to key routines via imports and strings, annotate decompiled code, and run headless scripts to automate extraction of C2, crypto, and config. Activates for requests to reverse engineer with Ghidra, decompile a binary, or script Ghidra headless analysis.

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。

meltedinhex/analyst-ai-pack222026年7月7日 更新