「pact」の検索結果

Find and identify the CCSPlayer_ItemServices_DropActivePlayerWeapon virtual function in CS2 binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the "drop the currently held weapon" vfunc by RTTI-walking the CCSPlayer_ItemServices vtable and confirming the candidate reads the player's active weapon and forwards it, with a computed toss velocity, into the weapon's own drop vfunc. Trigger: CCSPlayer_ItemServices_DropActivePlayerWeapon

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。

[30] ANALYZE. Understand how changes impact the system — what's the core, what's affected, what depends on what. Use when planning changes, analyzing systems, debugging issues, or anytime you need to see the full picture of cause and effect. Triggers on "what's affected", "impact analysis", "dependencies", "scope mapping", or when you need to understand ripple effects.

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。

Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.

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。

Consumer-Driven Contract Testing (CDC) using Pact framework and OpenAPI-based contract validation. Covers microservice-to-microservice contract verification, provider contract testing, consumer contract testing, contract publishing pipelines, and contract breaking-change detection. USE WHEN: designing microservice APIs, establishing service boundaries, verifying service-to-service contract compatibility, integrating with Pact framework, preventing contract-breaking changes, or setting up a contract testing pipeline in CI/CD. Triggers on "contract test", "Pact", "consumer- driven contract", "CDC", "service contract", "API contract", "breaking change".

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。

Designs and audits data retention and file compaction for an embedded SQLite datastore in a long-lived service — a unified retention registry (one declared policy per table), TTL / absolute-age / row-count-cap policies, a fail-loud coverage guard, WAL/checkpoint tuning, and auto_vacuum/incremental-vacuum so pruning actually shrinks the file. Use when a SQLite DB grows unbounded, a table has an index but no DELETE, a pruned DB never shrinks on disk, metrics are stored as raw events forever, or a new table needs bounding. Keywords retention policy, TTL, reaper, prune, VACUUM, auto_vacuum, incremental_vacuum, WAL checkpoint, freelist, DB bloat, row cap, per-tenant quota. NOT for Postgres/MySQL/server-DB partitioning or TTL, log-line rate-limiting/sampling, backup/replication, schema migrations, or query-performance indexing.

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。

OpenLineage, DataHub, Marquez for data lineage tracking and impact analysis. Activate on: data lineage, OpenLineage, DataHub, Marquez, impact analysis, data catalog, column lineage, data discovery. NOT for: data quality validation (use data-quality-guardian), dbt documentation (use dbt-analytics-engineer).

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。

Treat tokens as a coding swarm's cost-of-goods-sold and legibility engine while accounting for finite subscription allowance when per-call price is unknown. Covers provider windows, remaining-usage evidence, burn forecasts, preemptive checkpoint/model switching, per-agent budgets, compaction, shared digests, context degradation, and spend metering. Activate on: "token budget", "context budget", "compaction strategy", "briefing as compression", "context rot", "summarization collapse", "COGS for agents", "subscription usage remaining", "five-hour or weekly limit", "burn forecast", "model switch before limit", or "/context-economics-for-agent-swarms". NOT for: memory architecture (use always-on-agent-architecture), single-prompt wording (use prompt-engineer), mechanism-design proofs (use nisan-et-al-2007-algorithmic-game-theory), physical containment (use sandboxed-adversarial-test-harness), or production rebodiment and fencing (use agent-resurrection-and-body-continuity).

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。

指定した会話と期間で共有されたOpenClawの変更提案や課題を集め、GitHubで状態と根拠を確認し、影響度と対応準備に応じて優先順位を付けるスキル。

• 先週の会話で共有されたPRの整理
• 掲載済み提案の状態を再確認したいとき
• 同じ期間から未掲載の提案を探す

コード変更を確認する人に向けて、図や差分による要約、変更前後の動作証拠、取り消しやすさと影響範囲を短く整理したプルリクエスト本文を書くスキル。

• プルリクエスト本文を作成したいとき
• 構成変更をツリーや差分で説明したいとき
• 画面変更の前後を証拠で示したいとき

リポジトリから外部経由で悪用できる脆弱性を探し、入力から危険な処理までの経路、再現手順、影響を確認して報奨金制度向けの報告を支援するスキル。

• 外部リクエストで届く脆弱性の調査
• 静的解析の結果を精査したいとき
• 最小限の再現手順と影響の整理

曖昧な機能要望や影響の大きい変更を、作業範囲・前提・リスクとともに整理し、期待する動作と検証方法が明確な受け入れ基準や引き継ぎ資料にまとめるスキル。

• 曖昧な機能要望を整理したいとき
• 認証変更やデータ移行の受け入れ基準作成
• 別のエージェントやチームへの実装引き継ぎ

顧客の契約・請求状況を調べ、重複購入や更新失敗を分類し、返金・解約・請求管理画面の復旧から、顧客への返信案と製品の改善点まで整理するスキル。

• 重複契約や意図しない請求の調査
• 更新失敗や支払い方法の問題への対応
• 請求管理や解約画面を復旧したいとき

Claude Codeの作業状況や決定事項、次の手順をプロジェクト別に保存するスキル。別のセッションでも概要を読み込み、前回の続きから作業を再開できます。

• 終了前に進捗と次の手順を保存
• 前回のセッションから再開したいとき
• 複数プロジェクトの状況確認

Use when working on complex multi-step tasks, when a session is getting long (40+ tool calls), when the agent starts ignoring rules it followed earlier, when conventions drift, when output quality seems to degrade, or after any context compaction event. Prevents long-session corruption AND context compaction amnesia through behavioral self-enforcement.

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。

Govern Power Automate flows and Power Apps at scale using the FlowStudio MCP cached store. Classify flows by business impact, detect orphaned resources, audit connector usage, enforce compliance standards, manage notification rules, and compute governance scores — all without Dataverse or the CoE Starter Kit. Load this skill when asked to: tag or classify flows, set business impact, assign ownership, detect orphans, audit connectors, check compliance, compute archive scores, manage notification rules, run a governance review, generate a compliance report, offboard a maker, or any task that involves writing governance metadata to flows. Requires a FlowStudio for Teams or MCP Pro+ subscription — see https://mcp.flowstudio.app

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。

Pre-breach impact analysis: inventories sensitive data (PII, PHI, PCI-DSS, credentials), traces data flows, scores exposure vectors, and produces a regulatory blast radius report with fine ranges sourced verbatim from GDPR Art. 83, CCPA § 1798.155(a), and HIPAA 45 CFR § 160.404. Cost benchmarks from IBM Cost of a Data Breach Report (annually updated). All citations in references/SOURCES.md for verification. Use when asked: "assess breach impact", "what data could be exposed", "calculate blast radius", "data exposure analysis", "how bad would a breach be", "quantify data risk", "sensitive data inventory", "data flow security audit", "pre-breach assessment", "worst-case breach scenario", "breach readiness", "data risk report", "/data-breach-blast-radius". For any stack handling user data, health records, or financial information. Output labels law-sourced figures (exact) vs heuristic estimates (planning only). Does not replace legal counsel.

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。

Build accretion/dilution analysis for M&A transactions. Models pro forma EPS impact, synergy sensitivities, and purchase price allocation. Use when evaluating a potential acquisition, preparing merger consequences analysis for a pitch, or advising on deal terms. Triggers on "merger model", "accretion dilution", "M&A model", "pro forma EPS", "merger consequences", or "deal impact 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。

Generate a personal Claude Code usage & impact report ("receipts") from this machine's local session transcripts — for justifying Claude Code usage/spend to a manager, self-review, or "what have I been using this for" check-ins. Mines ~/.claude/projects locally (no extra API calls beyond one final write-up), cross-references local git history, and writes a markdown report plus a self-contained HTML receipt to your home directory. Use when the user asks for "receipts", an "impact report", "usage report", wants to "show my Claude Code activity", "prove the value of Claude Code", or runs `/receipts`.

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。

Trade execution modeling (backtest only) — slippage formulas (linear / square-root impact), VWAP/TWAP execution logic, market-impact cost estimation, and execution-assumption configuration.

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。

Conduct a defensible cybersecurity risk assessment using the NIST SP 800-30 Rev 1 methodology: prepare scope and a risk model, identify threat sources and threat events, identify vulnerabilities and predisposing conditions, determine likelihood and impact, compute risk, and communicate results as a prioritized risk register. Use when an organization needs an actual risk *assessment* (not a maturity score), when a control framework (CSF, ISO 27001, RMF, SOC 2, PCI) requires a documented risk analysis as input, when leadership asks "what are our top risks and how bad are they", when assessing risk for a new system or major change, or when building a risk register from scratch. This is the methodology that feeds framework selection, ATO packages, and treatment decisions. Keywords: risk assessment, NIST 800-30, threat modeling, likelihood and impact, risk register, risk analysis, threat sources, vulnerabilities, risk determination, qualitative risk, risk matrix, residual risk, risk treatment.

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。

Transform weak resume bullets into achievement-focused statements with metrics and impact. Use when the user wants to rewrite bullets, strengthen accomplishments, or add action verbs and impact to their resume.

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。

Summarizes data lineage graphs on Google Cloud to help users debug data quality issues and understand data provenance for BigQuery and Cloud Storage. Use when summarizing upstream and downstream data flows, and presenting complex lineage data as an intuitive Markdown report. Don't use for generic BigQuery queries, editing lineage relationships, or downstream deprecation. Don't use for downstream blast-radius impact analysis (use datalineage-bigquery-asset-impact-analysis skill 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。

This skill should be used when the user asks to "share memory between agents", "KV cache compaction for multi-agent", "orchestrator worker context", "latent briefing", "reduce worker tokens", "cross-agent memory without summarization", or discusses Attention Matching compaction, recursive language models with workers, or token explosion in hierarchical agents.

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 an MCP-connected agent should use Memori tools for targeted recall, summaries, post-compaction briefs, durable memory augmentation, quota checks, signup, feedback, preferences, prior context, or cross-session continuity.

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。