「pip」の検索結果

Design lightweight CI quality gates—lint, test tiers, security scans, and merge policies. Use when setting up or improving pipelines without tying to one stack only.

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。

"Implement a web crawler pipeline covering URL discovery, fetching, parsing, and storage. Use this skill when the user needs to build a site crawler, audit website structure, or collect web data systematically — even if they say 'scrape a website', 'crawl all pages', or 'site audit spider'.".

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。

"Optimize e-commerce search relevance across the full pipeline from query understanding to result presentation. Use this skill when the user needs to improve search quality, implement query processing features, or diagnose search relevance issues — even if they say 'search results are bad', 'improve product search', or 'search relevance 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。

"Implement text summarization using extractive and abstractive approaches. Use this skill when the user needs to condense long documents, build an automatic summarization pipeline, or compare summarization strategies — even if they say 'summarize this document', 'TLDR', or 'key points extraction'.".

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。

"Combine multiple forecasting models into ensemble predictions for improved accuracy. Use this skill when the user needs to improve forecast reliability, combine ARIMA/Prophet/ETS outputs, or build a robust forecasting pipeline — even if they say 'combine forecasts', 'model averaging', or 'which forecast should I trust'.".

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 hybrid recommendation systems combining multiple strategies for improved accuracy. Use this skill when the user needs to overcome single-method limitations, combine collaborative and content-based filtering, or build a production recommendation pipeline — even if they say 'combine recommendation approaches', 'best recommendation architecture', or 'cold start plus personalization'.".

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。

Write a durable feature spec before touching code. Reads the codebase map, reads related models/migrations to ask technical questions (not generic ones), then produces a structured spec doc in docs/specs/. Designed to pipeline with /implementation --issue N. Use before any feature implementation.

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。

Orchestrates the full law interpretation pipeline: MvT research, machine_readable generation with validation/BDD testing, and reverse validation. Invokes /law-mvt-research, /law-generate, and /law-reverse-validate sequentially. Use this skill proactively when: user wants to make a law executable, add machine_readable sections, or mentions "interpret" in the context of a Dutch law YAML file. Activate automatically when user opens a corpus YAML file without machine_readable sections and wants to make it executable.

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。

Idiomatic Go concurrency - sync primitives, channel semantics, the select statement, and the standard channel patterns (cancellation/done-channel, fan-out/fan-in, pipeline, or-done, context, worker-pool). Use when writing or reviewing Go that spawns goroutines, shares state, or coordinates over channels, even if the user never says "concurrency" - e.g. data races, deadlocks, goroutine leaks, sync/context/select usage, or "make this parallel". Distilled from luk4z7/go-concurrency-guide.

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 planning a source-grounded method overview, architecture, pipeline, system/data-flow, mechanism, or agent-workflow figure for a CS or deep-learning paper. Produces an editable figure brief before image generation or manual redrawing; not for plots, tables, or general 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。

Write balanced, evidence-based performance reviews for employees. Covers achievements, development areas, and goal setting using the SBI (Situation-Behavior-Impact) feedback model. Produces reviews that are fair, legally defensible, and growth-oriented. Use during annual or semi-annual review cycles. Do not use for disciplinary actions, PIPs, or compensation calculations.

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 production-ready analytical SQL queries using CTEs, window functions, aggregations, and data transformations. Translates business questions into well-documented, performant queries. Use when writing reporting queries, building data pipelines, or answering ad-hoc business questions with SQL.

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 sales pipeline, historical revenue, conversion rates, and assumptions to produce forecast scenarios. Use for sales reviews, RevOps planning, and founder revenue forecasting.

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。

Detection engineering skill for writing, testing, and tuning Sigma, YARA, YARA-L, Suricata, Snort, Zeek, KQL, SPL, EQL, Chronicle, and Elastic detection rules. Covers ATT&CK coverage mapping, telemetry gap analysis, false-positive tuning, detection-as-code pipelines, and validation with Atomic Red Team and Caldera. Use to design durable detections backed by tests.

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。

Natural-language orchestration of security tools through Gemini. Translates intent ("scan this scope for exposed admin panels") into safe, parameterized tool pipelines using nmap, masscan, naabu, httpx, nuclei, ffuf, gobuster, subfinder, amass, dnsx, katana, gau, semgrep, trivy, checkov, gitleaks, syft, grype, and custom scripts. Use when the user wants Gemini to drive a chain of CLI tools end to end with guardrails.

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。

HTTP request smuggling and desynchronization testing. Use when front proxies, CDNs, or load balancers disagree with the origin on message framing (Content-Length vs Transfer-Encoding), on HTTP/2→HTTP/1 translation, or when exploring client-side desync via browser fetch pipelines.

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 testing file upload endpoints for unrestricted file upload, MIME type bypass, magic byte spoofing, polyglot files, SVG XSS, XXE via Office documents, ZIP slip, and path traversal in filenames. Trigger on: multipart/form-data endpoints, avatar/document upload flows, import-from-file features, profile image, CSV/Excel import, DOCX/XLSX parsing, image resizing pipelines, archive extraction, and any endpoint that stores or serves user-supplied files. Detects extension bypass (shell.php.jpg), null byte injection, double extension, ImageMagick exploits, and content-type confusion.

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。

Supply-chain testing via package-manager dependency confusion: when internal package names resolve to attacker-controlled public registries, leading to malicious install and script execution. Use for npm/pip/gem/Maven/Composer/Docker manifest review and authorized red-team supply-chain exercises.

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。

Entry P1 category router for file access and upload workflows. Use when testing download endpoints, file paths, local file inclusion, upload flows, preview pipelines, archive extraction, or storage and sharing boundaries.

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。

Simulate supply chain and adversarial machine learning attacks by injecting poisoned data or targeted backdoors into training and fine-tuning datasets. Use this skill when assessing the integrity controls of MLOps pipelines or evaluating the resilience of AI models against highly targeted, stealthy manipulation intended to alter model behavior on specific triggers.

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。

Command injection playbook. Use when user input may reach shell commands, process execution, converters, import pipelines, or blind out-of-band command sinks.

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。

OS command injection occurs when user input is passed unsanitized to a system shell via dangerous APIs: Java `Runtime.exec()`, Python `os.system/subprocess`, PHP `system/shell_exec/exec/proc_open`, C `system/exec`. Detect via pipe `|`, semicolon `;`, `&&`, `||`, backtick, `$()` operators, and time-delay payloads (`sleep 5`). Tools: Commix, Burp Suite, OWASP WebGoat.

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 this agent when you need to perform custom bioinformatics analyses on genes or proteins that go beyond standard database lookups. This includes situations where existing domain/family annotations from UniProt are insufficient, when you need to verify dubious annotations, or when you need to perform comparative analyses across gene sets. The agent creates reproducible analysis pipelines with proper dependency management and documentation.

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。

Top-level orchestrator for Flutter feature specification. Runs the full uninterrupted pipeline: prd → techspec → tasks in one shot. Use when the user says "spec a feature", "write a spec for", "start feature spec", "plan a feature", or wants to go from idea to implementation-ready tasks without typing three separate commands.

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。