「pip」の検索結果

Drive CI with `odu` — one shared service, reached from a terminal (`odu surface`), from an agent (`odu mcp`), or from a browser. Trigger when the user asks to "run CI", "run the pipeline", "re-run a check", to run named lanes or recipes (e.g. "run fmt and nix", "just the e2e lane", bare selectors like `fmt`/`nix`/`e2e`), or names a recipe by `<recipe>@<platform>`. This skill — not a repo's local `just ci` / `just <recipe>` — is how an odu-run request is served, whichever face you are on.

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 an autonomous overnight campaign to find, prove, fix, and document CI flakes. Use when the user asks to stabilize CI through repeated full-pipeline runs and leave an evidence-backed draft 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 this repo's CI end-to-end — the kolu-specific procedure on top of the odu runner: the odu MCP front door, banned opt-out flags, linux-only platform pinning, venue-pool leasing, fail-fast surfacing, e2e timing evidence, and the green-gate. Triggers on "run CI", "drive CI", "re-run the pipeline", "close the red check", "warm the pool". Runner mechanics live in the `/odu` skill.

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。

Guidance for scaffolding new Rust projects. Use when: (1) starting a new Rust project or workspace, (2) configuring Cargo.toml best practices, (3) setting up CI pipelines for Rust, (4) organizing a multi-crate workspace, (5) configuring clippy, rustfmt, and linting.

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。

Reference for the DPI desync pipeline (ripdpi-config/-desync/-desync-runtime/-proxy-runtime). Use when changing TcpChainStep/UdpChainStep, offsets, fake-packet/TTL/TLS-prelude behavior, or a candidate's technique. Scheduling: diagnostics-system.

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。

Reference for the diagnostics pipeline (ripdpi-monitor-engine/ripdpi-diagnostics-* and core/diagnostics). Use when changing ScanRequest/ScanReport, ProbeTask families, probe scheduling, the catalog, or the wire contract. Techniques: desync-engine.

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。

Skill for building ActonOS: Web UI → Go binary → Docker image → ISO. Covers the entire build pipeline.

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 novel writing CLI agent with web workbench (JiaOS Studio) - use for creative fiction writing, standalone short-fiction packages, cover generation, novel generation, style imitation, chapter continuation/import, EPUB export, AIGC detection, and fan fiction. Native English support with 10 built-in English genre profiles (LitRPG, Progression Fantasy, Isekai, Cultivation, System Apocalypse, Dungeon Core, Romantasy, Sci-Fi, Tower Climber, Cozy Fantasy). Also supports Chinese web novel genres (xuanhuan, xianxia, urban, horror, other). Multi-agent pipeline, two-phase writer (creative + settlement), stronger long-form chapter craft rules, hook-ledger payoff checks, 33-dimension auditing, token usage analytics, creative brief input, structured logging (JSON Lines), multi-model routing, custom OpenAI-compatible provider support, and JiaOS Studio web UI for visual book management, short-fiction runs, cover generation, chapter review, real-time writing progress, market radar, and analytics.

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。

GitLab CI migration to GitHub Actions — syntax mappings and the migration report template for Pipelines, includes, Pages, environments, rules/only/except, parallel jobs, GitLab-specific variables. Load with `migration-core` when migrating GitLab CI sources to GitHub Actions.

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 migration to GitHub Actions — syntax mappings and the migration report template for YAML pipelines, templates, variable groups, service connections, deployment jobs, stages, conditional logic. Load with `migration-core` when migrating Azure DevOps sources to GitHub Actions.

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。

Jenkins migration to GitHub Actions — syntax mappings and the migration report template for Pipelines (declarative + scripted), shared libraries, Groovy scripts, credential bindings, agent labels, parallel stages, plugin replacements. Load with `migration-core` when migrating Jenkins sources to GitHub Actions.

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。

Advanced CV for infrastructure inspection including forest fire detection, wildfire precondition assessment, roof inspection, hail damage analysis, thermal imaging, and 3D Gaussian Splatting reconstruction. Expert in multi-modal detection, insurance risk modeling, and reinsurance data pipelines. Activate on "fire detection", "wildfire risk", "roof inspection", "hail damage", "thermal analysis", "Gaussian Splatting", "3DGS", "insurance inspection", "defensible space", "property assessment", "catastrophe modeling", "NDVI", "fuel load". NOT for general drone flight control, SLAM, path planning, or sensor fusion (use drone-cv-expert), GPU shader development (use metal-shader-expert), or generic object detection without inspection context (use clip-aware-embeddings).

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。

Process vehicle insurance Excel data using Pandas - file handling, data cleaning, merging, validation. Use when processing Excel/CSV files, handling data imports, implementing business rules (negative premiums, zero commissions), debugging data pipelines, or optimizing Pandas performance. Keywords: data_processor.py, Excel, CSV, Pandas, merge, deduplication, date normalization.

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。

Instructions for managing CI pipelines, GitHub Actions workflows, Airflow DAGs, and automation scripts in the insurance analytics 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。

Generates FluentValidation validators for commands and queries. Includes common validation rules, custom validators, async validation, and integration with MediatR pipeline behaviors.

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 a reporting pipeline — scheduled reports with SQL queries, delivery via Slack or email, threshold alerts, and historical comparison. Use when asked for "automated reports", "scheduled report", "email digest", or "Slack alerts for metrics".

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。

Analytics and BI engineer — dashboards, metrics design, reporting pipelines, and data storytelling. Use when asked to "build a dashboard", "design a metric", "write a report", or "audit our analytics".

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 performance management system - review cycles, calibration process, career ladder, and PIP framework. Use when asked to "build a performance review process", "design career levels", "how do we handle underperformers", or "run a review cycle".

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 a hiring pipeline - job description, sourcing strategy, interview scorecard, and offer process. Use when asked to "write a job description", "build an interview process", "design our hiring funnel", or "what should we look for in a [role]".

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。

People reconnaissance - audit org design, hiring pipeline, comp structure, onboarding, and performance systems to understand what is working and where the constraint is. Use when asked to "audit our people ops", "what is broken in our hiring", "review our org structure", or "before designing a comp framework".

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 and implement a feature engineering pipeline for a ML problem. Use when asked to "engineer features for this model", "what features should we build", or "design feature transformations".

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 a data cleaning and transformation pipeline — missing values, outliers, and deduplication. Use when asked to "clean this dataset", "handle missing values", or "deduplicate this data".

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。

ML reconnaissance — inventory all models, pipelines, data sources, and monitoring. Use when asked "what ML do we have", "model inventory", or "ML assessment".

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 a data validation pipeline — schema checks, range validation, and quality metrics. Use when asked to "validate incoming data", "add schema checks", or "define data quality metrics".

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。