「findings」の検索結果

Captures and retrieves PR-review findings in memory palaces. Use after PR review to store architectural decisions, patterns, and standards for future reference.

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。

Formats review deliverables with consistent structure for comparable findings. Use when finalizing any review or analysis that must be shared or compared.

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。

Provides review-workflow scaffolding for context, evidence, and output. Use at the start of any detailed review to ensure consistent, comparable findings.

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 a completed Shell scenario planning exercise needs to be converted into a TikTok script. Triggers when user says "make a tiktok", "tiktok script", "generate tiktok", or "content from scenario". Requires a completed scenario with narratives, findings, and worldview 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。

Synthesize raw recon/test output into engagement state. Reads everything dropped in targets/<active>/ingest/, extracts hosts/assets/creds/paths, merges into state.md/loot.md/Killchain.md, logs it, archives the raw files. Works for pentest, bugbounty, and ctf. Use when asked to "ingest", "synthesize findings", "process recon", or after dropping tool output in the ingest folder.

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。

Autonomous bug-bounty campaign driver. Runs a full programme end to end with no operator approvals - the deterministic driver (scripts/campaign.py) owns pass state, generates the killchain board from recon, and prints the exact next action (including which Skill and tool to run) every turn. Use when starting or resuming a bug-bounty engagement, "run the bb workflow", "hunt this program", "9-pass campaign", or when handed a *.scope wildcard to test for TIER1 findings. Single agent, refuter-verified, wiki-first, tool-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。

Evaluate Agent Skill design quality with an opinionated, practice-derived rubric informed by public specifications and examples. Use when reviewing, auditing, comparing, or improving SKILL.md files and skill packages. Produces evidence-backed findings, optional multi-dimensional scoring, and prioritized changes; treat the result as diagnostic guidance, not official certification or a universal standard.

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。

把账号档案、研究证据、选题卡、成稿、发布数据和复盘结论整理成能长期积累和复用的内容资产。用户要保存生产结果、建立主题地图、复用旧选题或维护长期内容库时使用。 English: Organize account profiles, research evidence, topic cards, drafts, publishing data, and review findings into reusable long-term content assets. Use to archive production work, build a topic map, reuse past ideas, or maintain a content library.

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。

Guides conversion of gap analysis findings into phased implementation plans with milestones and risk-based prioritisation. Activate when building compliance programmes or allocating privacy budgets. Keywords: remediation roadmap, implementation plan, phased approach, prioritisation.

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。

Guides audit follow-up and verification processes including follow-up scheduling, remediation effectiveness testing, finding closure criteria, re-testing procedures, status reporting, and escalation of unremediated findings. Implements IIA Standard 2500 monitoring requirements and ISO 19011 follow-up guidance for privacy audit engagements. Keywords: audit follow-up, verification testing, finding closure, remediation effectiveness, re-testing, follow-up audit.

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。

Guides audit findings remediation program management including finding prioritization by severity (critical, high, medium, low), owner assignment, remediation planning, deadline tracking, verification testing, closure criteria, escalation protocols, and management reporting. Covers remediation lifecycle from finding issuance to verified closure. Keywords: audit remediation, finding management, prioritization, verification testing, closure criteria, remediation tracking.

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。

Review PRD.md for gaps, contradictions and unverifiable claims, write an improved PRD.md and record the findings in PRD-REVIEW.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。

Plans an architecture-driven change to code that already exists: module boundaries, type responsibilities, layering, coupling, and the public surface a revision moves. Produces a buildable change plan that names the types, modules, and methods involved and records the surface delta each change makes. Use when the user wants to plan, scope, or sequence a restructure, extraction, split, consolidation, responsibility shift, or API revision of existing code, including "these responsibilities are wrong, plan the fix". Does not assess an area and stop at findings — use architectural-analysis. Does not specify new behavior — use plan-a-feature. Does not diagnose a bug — use investigate. Does not write the code — use refactor to restructure it or tdd to build it.

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。

Produces a human-readable, progressive-disclosure overview of unfamiliar code or a pull request's changes — why it exists (the real problem it solves or goal it serves for the business or a user), and from there what it does, how it flows, and where to start — so you can get up to speed before working on or reviewing it. Use when you want to understand, get oriented in, make sense of, explain, or get up to speed on a chunk of code, a file, a directory, a symbol, or a PR's changes. Writes the overview to a scratch file and changes no code. Does not review code quality or raise findings — use code-review for auditing changes or post-code-review-to-pr for posting them. Does not produce durable feature or system documentation — use project-documentation. Does not assess architecture or structural risk — use architectural-analysis. Does not diagnose bugs or root-cause failures — use investigate. Does not pace a person through the code one step at a time in conversation — use code-walkthrough.

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 an evidence-based investigation of a bug, failure, or unexpected behavior with investigate and publishes the resulting investigation report to a user-specified Confluence location. Use when the user wants something debugged, diagnosed, or root-caused AND the findings posted to a Confluence space or page. Requires a configured Atlassian MCP server. Does not investigate to a local file only — use investigate. Does not publish an arbitrary existing markdown file — use markdown-to-confluence. Does not document an already-understood feature to Confluence — use project-documentation-to-confluence. Does not plan or specify a new feature to Confluence — use plan-a-feature-to-confluence. Does not publish to Jira — use work-items-to-jira.

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。

Builds a feature specification from scratch with plan-a-feature and publishes it to a user-specified Confluence location, posting the spec as a parent page and each companion artifact (decision log, team findings, technical notes) as a child page beneath it. Use when the user wants a new feature planned, designed, scoped, or specified AND posted to a Confluence space or page. Requires a configured Atlassian MCP server. Does not plan to local files only — use plan-a-feature. Does not publish an arbitrary existing markdown file — use markdown-to-confluence. Does not refine or stress-test an existing plan — use iterative-plan-review. Does not document already-built features to Confluence — use project-documentation-to-confluence.

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。

Applies Han's shared Human-Readable Output Standard to a target you already have — a file on disk, text pasted into the prompt, or a draft already produced in the conversation — by dispatching the readability-editor to rewrite its prose so the main point comes first, headings are descriptive, each paragraph carries one idea, and sentences stay short and active, while preserving every fact. Use when you want to make a document or draft readable, edit or polish prose for readability, clean up writing, tighten wording, or re-apply the readability standard to something already written. Rewrites prose only, leaving code, diagrams, and citation identifiers unchanged. Does not write new feature or system documentation — use project-documentation. Does not restructure code or review it — use refactor to restructure code and code-review to audit it. Does not judge the underlying work or raise findings; it only rewrites the writing.

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 deep architectural analysis of a specified module, directory, or feature area by examining structural coupling, data flow, concurrency patterns, risk, and SOLID alignment. Use when the user wants to assess, evaluate, or review the architecture, design quality, dependency structure, coupling, cohesion, or technical debt of an existing part of the codebase. Not for investigating specific bugs, runtime errors, or failures — use investigate. Not for test planning — use automated-test-planning. Not for file-level code review — use code-review. Not for researching open-ended options, prior art, or how something works — use research. Not for designing a new interface or contract — use design-an-api. Not for planning the change its findings imply — use plan-a-change. Not for discovering bounded contexts, ubiquitous language, or where code boundaries diverge from domain boundaries — use ddd-analysis. Not for writing documentation or architectural decision records.

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。

Parallel multi-AI cross-validation research workflow (大版本). Dispatch N internal sub-agents + grok + gemini in parallel, automatically cross-validate findings, tier by confidence (strong consensus / partial / conflict / insufficient), generate tiered action items with arbitration. Use when user says "多 AI 调研", "交叉验证", "独立共识", "三脑调研", "multi-ai research", "parallel research", "cross-validate", or needs deep research that benefits from internal data + external 2026 consensus. NOT for quick factual Q&A, pure code reasoning, or tasks needing deep project 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。

全面代码库审计 — 自适应并行深度分析（前后端契约、数据完整性、异常处理/安全、架构/技术债、配置/缓存），结构化 findings + 对抗验证 + 基线对比，输出按严重程度排序的统一报告和修复路线图。支持 quick 快速体检模式。Use when user asks to audit, analyze, or review an entire codebase for design issues, find hidden bugs, check architecture health, or asks '全面审查', '代码库审计', '分析设计问题', 'audit codebase', 'health check', '有哪些问题', '快速体检'. Also trigger when user asks to find silent degradation, data flow breakpoints, type mismatches between frontend and backend, or wants to understand technical debt across a 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。

Scan code, dependencies, containers, IaC and SBOMs with Snyk via its first-party MCP server: authenticate, trust a folder, run the right scanner, read the findings, fix and re-scan. Includes package-health checks before adding a dependency.

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 before pushing a PR that touched UI to find untranslated keys in any of the 21 non-English locales and to catch user-visible English strings that bypass context.l10n. Reports findings as a checklist; refuses to declare clean until all are addressed or explicitly waived. Invoke with /check-l10n.

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。

Statically analyze code to detect security vulnerabilities including buffer overflows, injection risks (SQL, command, XSS), insecure deserialization, improper authentication, hard-coded credentials, and unsafe cryptography. Use when: (1) Performing security code review, (2) Analyzing code for OWASP Top 10 vulnerabilities, (3) Identifying CWE-classified weaknesses, (4) Generating security audit reports, (5) Reviewing code before deployment, or (6) Assessing third-party code security. Findings categorized by CWE ID and severity (Critical/High/Medium/Low).

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。

Analyze vulnerable code to identify underlying root causes such as violated assumptions, incorrect invariants, missing validation checks, or unsafe component interactions. Use when investigating security vulnerabilities, CVEs, exploit code, or security audit findings. Infers why the vulnerability exists beyond surface symptoms, identifies systemic issues, and explains the chain of failures that enable exploitation.

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。