「findings」の検索結果

Audits Convex performance for reads, subscriptions, write contention, and function limits. Use for slow features, insights findings, OCC conflicts, or read amplification.

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Read the Convex deployment's 72h insights (read limits, OCC contention), root-cause each event in code, report evidence-backed perf/cost findings with fixes.

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。

[21] UNDERSTAND. Deep research workflow for this project using 150% scope (100% core + 50% boundary), evidence-based reasoning, and structured investigation notes. Use when the task requires investigation, root-cause analysis, or mapping unknown areas. Always maintain a research log file that captures findings, hypotheses, and next branches; use web.run when external verification is needed.

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。

Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.

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。

Replicate and validate a GitHub issue by spinning up Archon, analyzing the issue, and systematically testing all described symptoms using browser automation. Use when: User wants to reproduce a bug, validate a GitHub issue, confirm a reported problem, or investigate whether an issue is real before working on a fix. Triggers: "replicate issue", "reproduce issue", "validate issue", "confirm bug", "test issue", "can you reproduce", "try to replicate", "verify the bug". Capability: Checks out main, pulls latest, starts Archon, reads the GitHub issue, then uses agent-browser to systematically test every symptom and produce a findings report. NOT for: Fixing issues (use /archon or /exp-piv-loop:fix-issue), general UI testing (use /validate-ui).

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。

Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", "test this app/site/platform", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.

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Framework-directable information security risk assessment. Identifies threats, evaluates likelihood/impact via a 3x3 matrix, maps findings to any compliance framework, and recommends risk treatment options with prioritization guidance.

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。

Multi-source deep research agent. Searches the web, synthesizes findings, and delivers cited reports. No API keys required.

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。

Manus-style file-based planning for complex tasks. Creates and maintains task_plan.md, findings.md, and progress.md under .kiro/plan/. Use when planning, breaking down work, resuming a multi-step task, tracking phases, or restoring context after compaction. Trigger phrases include start planning, continue task, resume work, current phase, restore 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。

Implements Manus-style file-based planning to organize and track progress on complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when asked to plan out, break down, or organize a multi-step project, research task, or any work requiring >5 tool calls. Supports automatic session recovery after /clear.

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。

Implements Manus-style file-based planning to organize and track progress on complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when asked to plan out, break down, or organize a multi-step project, research task, or any work requiring >5 tool calls. Supports automatic session recovery after /clear.

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 context files (CLAUDE.md, .claude/ tree, READMEs, docs) for broken references and verifiably stale content. Runs a deterministic offline link/path checker first, then a bounded semantic review where every finding must cite evidence. Reports findings; fixes only on request. Use when the user says "docs check", "/docs-checker", "check the docs for stale content", "audit CLAUDE.md", or when a scheduled cloud routine fires.

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。

Azure DevOps pull requests, for repos whose git remote is on dev.azure.com or *.visualstudio.com. Covers comment threads, which `az repos pr` cannot read or post. Use to create a PR for the current branch, check out, list or complete PRs, post code comments on a PR, reply to threads, and assess whether review feedback was addressed. Trigger on "create PR", "checkout PR 123", "list PRs", "complete PR", "comment on the PR", "post these review findings", "check PR feedback", "/dev-azdo:pr".

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 technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants measurable accessibility, performance, responsive, theming, or anti-pattern findings—not when they mainly want an overall UX critique or final visual/detail polish.

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 the full Forge pipeline unattended: each phase is reviewed by a fresh evaluator subagent, the findings feed back, and the run advances itself. Use when the user runs /forgemaster-auto or wants a feature built end to end without approval gates.

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Use when auditing or improving example.com's SEO/indexing — Google Search Console issues (404s, sitemap, "discovered not indexed"), on-page checks (title/meta/canonical/OG/H1/internal links), or wiring search-engine notification (IndexNow/GSC/Bing/Yandex). Also use when the operator pastes GSC findings and asks to fix + validate.

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This skill teaches security teams how to detect and respond to unauthorized cryptocurrency mining operations in cloud environments. It covers identifying cryptomining indicators through compute usage anomalies, network traffic patterns to mining pools, GuardDuty CryptoCurrency findings, and runtime process monitoring on EC2, ECS, EKS, and Azure Automation workloads.

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。

Detecting data exfiltration attempts from AWS S3 buckets by analyzing CloudTrail S3 data events, VPC Flow Logs, GuardDuty findings, Amazon Macie alerts, and S3 access patterns to identify unauthorized bulk downloads and cross-account data transfers.

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This skill outlines methodologies for performing authorized penetration testing against AWS, Azure, and GCP cloud environments. It covers understanding the shared responsibility model for testing scope, leveraging cloud-specific attack tools like Pacu and ScoutSuite, exploiting IAM misconfigurations, testing for SSRF to cloud metadata services, and reporting findings aligned to MITRE ATT&CK Cloud matrix.

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Migrates legacy AEM (6.x, AMS, on-prem) to AEM as a Cloud Service using BPA CSV or cache, CAM/MCP target discovery, and a one-pattern-per-session workflow. Use for BPA/CAM findings, Cloud Service blockers, or fixes for scheduler, ResourceChangeListener, replication, EventListener, OSGi EventHandler, DAM AssetManager, HTL data-sly-test lint. OSGi configs → Cloud Manager — scan ui.config, .cfg.json, secrets, $[secret:]/$[env:] — agent follows references/osgi-cfg-json-cloud-manager.md when prompted. After BPA/CAM discovery, migration hands off each (pattern, file) pair to the code-assessment skill — code-assessment owns the five pattern guides (scheduler/, resource-change-listener/, replication/, event-migration/, asset-manager/) and the shared references for SCR→DS, ResourceResolver/SLF4J, HTL lint, and prerequisites.

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Use when asked to run, read, or interpret react-doctor output on the Namias portfolio. Covers the npm scripts, the doctor.config.json schema, the score model, the 12-rule catalog, and which findings are real vs false-positive by design.

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Reviews authentication and authorization implementation for session management, CSRF, cookie security, and auth flow vulnerabilities with findings, severity assessment, and fix recommendations. Use for "auth review", "session security", "CSRF protection", or "authentication audit".

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Use when adapting academic findings for a public audience (op-ed, social post, podcast) and the simplification must stay evidence-faithful, avoid overclaiming, respect embargoes, and disclose AI assistance.

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Hunt source code and build artifact leakage — JavaScript source maps (.js.map) reconstructing TypeScript/ES6 source, Swagger/OpenAPI JSON endpoint discovery, .env/.git exposure, webpack chunks with hardcoded secrets, robots.txt/security.txt recon, build-info files, asset-manifest.json API route discovery, .DS_Store file listing. Use at the START of every recon session — these findings often unlock the entire attack surface.

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。