「reporting」の検索結果

Render Markdown, HTML, or PDF paid-advertising reports from a validated Claude Ads JSON run bundle. Use for ads report, client report, audit PDF, executive audience reporting, or exporting prior audit and plan results.

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。

Audit Snapchat Ads measurement, Snap Pixel and Conversions API, mobile and app campaigns, creative, AR and catalog formats, audiences, budgets, brand safety, and reporting. Use for Snapchat Ads, Snap Ads, Snap Pixel, Snapchat Conversions API, AR Lens ads, app-install campaigns, or Snapchat dynamic product ads.

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。

Operate professional paid advertising across Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, and X. Use for account intake, source-grounded audits, strategy, budget and measurement planning, creative production, experiments, reporting, monitoring, and explicitly approved campaign changes. Also trigger on PPC, paid social, retail media, attribution, tracking, landing pages, cross-platform conversion totals, negative keywords or search terms, beta-feature scoring, stale platform claims, API-token or credential setup, campaign deletion, and safe Claude Ads installation or uninstall.

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。

Audit Pinterest Ads measurement, Pinterest Tag and Conversions API, catalog and shopping readiness, visual creative, audiences, Performance+ intent, budgets, brand safety, and reporting. Use for Pinterest Ads, promoted Pins, shopping ads, catalog sales, Pinterest Tag, Pinterest Conversions API, or Pinterest Performance+.

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。

Create a professional paid-advertising strategy covering objectives, economics, platform selection, campaign architecture, audiences, budget, creative, measurement, experiments, governance, rollout, and reporting. Use for ad plan, media plan, PPC strategy, paid-social strategy, campaign architecture, advertising roadmap, or channel planning.

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。

Audit Amazon Ads profiles, regions, Sponsored Products, Sponsored Brands, Sponsored Display, DSP, portfolios, targeting, search terms, retail readiness, creative, budgets, ACOS, TACOS, reporting, and policy. Use for Amazon Ads, sponsored ads, Amazon PPC, ACOS, TACOS, ASIN advertising, Amazon DSP, or retail-media optimization.

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。

Audit Reddit Ads measurement, campaign structure, community and interest targeting, creative-native fit, catalog advertising, budgets, brand safety, and reporting. Use for Reddit Ads, promoted posts, conversation ads, community targeting, Reddit Pixel, Reddit Conversions API, or Reddit dynamic product ads.

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。

Audit X Ads measurement, X Pixel and Conversions API, campaign objectives, keyword and conversation targeting, creative, budgets, brand safety, app measurement, and reporting. Use for X Ads, Twitter Ads, promoted posts, X Pixel, X Conversions API, conversation targeting, or paid campaigns on X.

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。

Create and modify Excel workbooks with mandatory deterministic Python verification of workbook structure, required sheets, populated columns, and sample counts before reporting completion.

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。

Runs full Trailmark structural analysis by building a graph, running `preanalysis()`, and reporting hotspots, taint, blast radius, privilege boundaries, attack surface, and version-gated Trailmark 0.4+/0.5+ data such as proxy counts, subgraph edges, type/reference summaries, and entrypoint attributes. Use when vivisect needs detailed structural data for a target. Triggers: structural analysis, blast radius, taint analysis, complexity hotspots, proxy nodes, type references.

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。

Validates security patches with reproducible baseline-versus-patched evidence, including original exploits, root-cause variants, behavior preservation, regressions, and newly introduced security failures. Use after a patch exists and before accepting, merging, or reporting it as fixed; also use when an AI-generated patch, remediation commit, pull request, or proposed upstream fix needs adversarial post-patch validation across any language.

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。

Deep-dive offensive methodology for dependency confusion and namespace attacks across all major package ecosystems. Covers npm scope confusion exploiting the gap between public and private scoped packages and .npmrc misconfigurations where registry mappings fail to pin internal scopes exclusively. Addresses PyPI namespace attacks through --extra-index-url resolution ordering, NuGet feed priority exploitation when multiple package sources are configured without clear directives, Maven and Gradle repository ordering where artifact resolution traverses repositories sequentially, Go module proxy abuse through GOPROXY misconfiguration, Ruby gems namespace squatting, and Docker image tag confusion with unqualified image references. Provides complete proof-of-concept methodology using safe callbacks including DNS canary via interactsh or Burp Collaborator and HTTP beacon with no destructive payload. Covers reconnaissance techniques for discovering internal package names through GitHub repository analysis, error message harvesting, JavaScript source map extraction, lock file parsing, job postings mentioning internal tools, and package manifest inspection. Directly references and builds upon Alex Birsan's seminal 2021 dependency confusion research. Each ecosystem section includes registry-specific exploitation mechanics, configuration vulnerabilities, and defensive countermeasures for engagement reporting.

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。

Audit or critique a product flow, journey, workflow, funnel, onboarding path, checkout path, settings path, screen, or multi-step product experience by capturing screenshots first, then reporting UX, design, and accessibility findings inline from that evidence. Use Figma only when the user explicitly asks for a board. Use when the user asks to audit, review, critique, inspect, assess, analyze, evaluate, or give feedback on a product experience.

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。

Prepare KPI readouts, scorecards, WBR/MBR/QBR updates, and executive summaries from quantitative business or product metrics; use when the task is to report status, compare against targets, explain validated drivers, and state operating implications.

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 work out of 10 against a clear rubric, then improve it round by round until every item reaches the target score the user named (for example "get it to 8 out of 10", "bring everything under 6 up to 6+"). Covers anchored rubrics, measurable criteria, independent or blind judging, before/after scorecards, and honest reporting of anything still short. Use whenever the user asks to score, rate, grade or judge something out of 10, names a target score, or asks "what would make this a 9?".

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。

Diagnostic protocol to run before reporting a sandbox blocker or asking for a configuration change. Eight checks that eliminate false positives, then a report template the person holding the settings can act on. On one measured day, six of eight reported blockers turned out to be false, all from the same handful of method errors.

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。

This skill should be used when the user asks to "analyze experimental results", "run strict statistical analysis", "compare model performance", "generate scientific figures", "check significance", "do ablation analysis", or mentions interpreting experiment data with rigorous statistics and visualization. It focuses on strict analysis bundles, not Results-section prose.

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。

This skill should be used when the user asks to "write an experiment report", "summarize experimental results", "do experiment retrospection", "write a results report", "写实验总结报告", "写实验复盘", or mentions turning completed experiment artifacts into a structured, decision-oriented research report. It assumes strict analysis should come from `results-analysis` first.

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 before any Worker taskflow call or assigned-task workflow, including reading task state, acknowledging a task, executing a task, tracking progress, handling blockers/questions, submitting structured results, or reporting completion. Always use this skill when the message mentions assigned task, task ID, shared/tasks, spec.md, meta.json, result.md, deliverables, BLOCKED, REVISION_NEEDED, SUCCESS, submit_task, or ack_task.

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。

Optional Sergo examples for cache formats and reporting templates.

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。

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。

Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.

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。