「mining」の検索結果

Webサイトの通信をHARファイルに記録し、JSON取得に使われるAPIを読み解いてHTTPクライアントを作るスキル。検索などの処理をブラウザなしで再実行できます。

• Webサイト用のCLIを作りたいとき
• ブラウザなしで検索を繰り返したいとき
• 検索候補やフィードの通信を調べたいとき

Pythonの実行を途中で止め、変数や処理の流れを調べて不具合の原因を探ります。pdbとdebugpyを使い分け、失敗したテストや稼働中のプロセスも調査します。

• 失敗したテストの変数を調べたいとき
• 関数内のコレクションの変化を追う
• 例外発生地点の変数の確認

Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing tool calls, checking memory operations, or examining agent performance. Automatically fetches recent traces and analyzes execution patterns. Requires langsmith-fetch CLI installed.

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。

MemPalace — mine projects and conversations into a searchable memory palace. Use when the user asks about MemPalace, memory palace, mining memories, searching memories, palace setup, wings, rooms, or drawers; or when they want to recall past work that may already be filed in their palace.

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。

Install, configure, and operate MemPalace, including a private local palace, a shared-brain hub, or a client joining an existing hub. Use for first-time setup, MCP wiring, mining, status, palace audit and repair, wings, rooms, drawers, shared-brain identity, or logstream readiness.

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。

Estimates intracellular metabolic fluxes from steady-state carbon-13 isotope-tracing measurements using validated atom maps, mfapy isotope simulation, constrained multistart fitting, and flux-profile diagnostics. Use for 13C-MFA, carbon tracing, mass isotopomer distributions (MDVs/MIDs), positional isotopomers, parallel tracer experiments, and determining whether labeling data constrain a pathway flux. Distinguishes measured-label inference from COBRA flux balance analysis and flags experiments requiring nonstationary MFA.

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。

Design optimal team structures, hiring plans, compensation strategies, and equity allocation for early-stage startups from pre-seed through Series A. Use this skill when planning headcount, determining which roles to hire next, setting compensation or equity ranges, designing org structure, or building a hiring budget aligned to funding milestones.

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。

Detects typosquatting attacks in npm and PyPI package registries by analyzing package name similarity using Levenshtein distance and other string metrics, examining publish date heuristics to identify recently created packages mimicking established ones, and flagging download count anomalies where suspicious packages have disproportionately low usage compared to their legitimate targets. The analyst queries the PyPI JSON API and npm registry API to gather package metadata for automated comparison. Activates for requests involving package typosquatting detection, dependency confusion analysis, malicious package identification, or software supply chain threat hunting in package registries.

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。

Discover and inventory shadow API endpoints that operate outside documented OpenAPI/Swagger specs, using traffic analysis against API gateways (Kong, AWS API Gateway, Envoy), cloud configuration scanning, and source code repository mining for undocumented routes. Use when assessing API attack surface, auditing for forgotten test environments or deprecated API versions still running, or building an API registration governance policy.

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。

Detects unauthorized runtime drift in containers by monitoring binary execution, filesystem changes, and configuration deviation from the original immutable image, using Falco and Microsoft Defender for Containers. Use when validating immutable-infrastructure controls, hunting for unexpected package installs or binaries written inside a running container, or determining whether a container diverged from the image it was built from. Keywords: drift, immutable infrastructure, new binary executed, package install, image mismatch, Falco. Do not use for detecting breakout from the container to the host - use detecting-container-escape-attempts.

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。

Design identity governance and lifecycle (IGA) programs on platforms like SailPoint, Saviynt, or Entra ID Governance, covering joiner-mover-leaver (JML) automation, role mining, access requests, periodic recertification, and orphaned-account remediation sourced from an HR feed. Use when automating cross-system JML provisioning, remediating former-employee access, or building lifecycle processes for SOX, HIPAA, or GDPR 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。

Respond to malware infections across enterprise endpoints by identifying the malware family, determining infection vectors, assessing spread, and executing containment, analysis, eradication, and recovery procedures aligned to MITRE ATT&CK. Use when responding to a confirmed or suspected malware infection, including trojan/worm/ransomware outbreaks, malware triage, or infected endpoint remediation.

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 Windows LNK shortcut files and Jump List artifacts with LECmd, JLECmd, and manual Shell Link Binary Format parsing to establish evidence of file access, program execution, and user activity that persists even after the target file is deleted. Use when investigating Windows user activity, reconstructing file-access or program-execution timelines, or examining recent/frequently-used file evidence in a forensic exam.

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 the NTFS Master File Table ($MFT) with MFTECmd, analyzeMFT, and X-Ways Forensics to recover metadata and content of deleted files by examining MFT record entries, $LogFile, $UsnJrnl, and MFT slack space. Use when recovering evidence of deleted files, reconstructing NTFS file-system timelines, or detecting anti-forensic timestomping during a Windows forensic examination.

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。

Perform comprehensive forensic analysis of raw (dd), E01, or AFF disk images with Autopsy and The Sleuth Kit, recovering deleted files, examining metadata and embedded artifacts, keyword searching, and building investigation timelines with visual reports. Use for structured analysis of a forensic disk image or when stakeholders need visual reports from evidence.

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。

Assess and classify legal risks using a severity-by-likelihood framework with escalation criteria. Use when evaluating contract risk, assessing deal exposure, classifying issues by severity, or determining whether a matter needs senior counsel or outside legal review.

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。

Operation-aware node configuration guidance. Use when configuring nodes, understanding property dependencies, determining required fields, choosing between get_node detail levels, or learning common configuration patterns by node type. Always use this skill when setting up node parameters — it explains which fields are required for each operation, how displayOptions control field visibility, and when to use patchNodeField for surgical edits vs full node updates.

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。

Expert guidance for security alert triage in Google SecOps. Use when investigating and triaging security alerts, determining false positives vs. true positives, assessing entity risk, adjusting alert severity or priority, and closing or escalating alerts and cases. Don't use for deep multi-hop incident investigations across host timelines (use secops-investigate), proactive threat hunting or retroactive IoC sweeps (use secops-hunt), or authoring new detection rules (use secops-detection-engineering).

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 diagnostic workflows and step-by-step root-cause analysis procedures for actively broken, failing, or slow BigQuery jobs, execution graph and query plan stage bottlenecks, system performance issues, or unexpectedly expensive workloads. Use when interpreting symptoms, isolating bottlenecks, diagnosing cost spikes (on-demand query spend, capacity slot autoscaling, storage growth), execution graph stages or substep variables, identifying root causes, and determining remediation steps. Don't use for writing or optimizing SQL, proactive capacity planning, or storage layout design (use bigquery-optimization), or when the user already knows which telemetry they want and just needs the query (use bigquery-observability).

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。

Weekly reusable-session ticket-to-KB loop. Reads recently resolved Plain threads, clusters them into recurring topics, cross-references {{kb_path}} of {{kb_repo}} and a durable ledger to find topics with real volume and no article, drafts the top gaps from the actual resolutions, and opens a PR only — never publishing or merging.

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。

Transforms product documentation into sales-ready packages — a story explanation, charcoal gestural sketch art, and talking points — via a narrative-arc pipeline. USE WHEN sales, proposal, pitch deck, value proposition, sales narrative, sales deck, sales package, turn this into a pitch, create a sales story, sales materials, product pitch, transform docs to sales, sales script. NOT FOR Hormozi $100M frameworks, value equation, irresistible offer, or VOC mining, standalone diagrams or illustrations (use Art), or platform social posts.

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。

Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing tool calls, checking memory operations, or examining agent performance. Automatically fetches recent traces and analyzes execution patterns. Requires langsmith-fetch CLI installed.

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 file-focused code review for correctness bugs. Unlike shallow-review which runs 6 specialists in parallel across the entire patch, deep-review focuses on user-specified files with full pattern catalogs (500+ patterns), codebase investigation, and source-level context gathering. Use when: the user specifies particular files for focused review, a shallow review flagged areas that need deeper investigation, reviewing critical-path code changes, examining complex serialization/lifecycle/state-machine changes. The user instructs which files to focus on (typically a subset of files in the patch).

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。