「without」の検索結果

Audit agent runtimes and their tests for lifecycle inference, capability overload, context pollution, correlated verification, prompt-only control, false success, dead compatibility paths, test-only seams, and complexity without contribution. Use for whole-repository agent audits, slop or dead-code triage, test contribution reviews, large refactors, tool/context simplification, and cleanup requests that need proof before deleting code or 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。

Implements one numbered sub-task from a task list at .ai/[feature]/tasks.md, running linters and tests, without staging, committing, or marking the task complete. Use when asked to carry out a specific sub-task by number, or as the inner step of a larger loop that handles commits separately. For the full loop including commits, use task-orchestration.

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。

Watch a CI run's jobs to completion without idling or hand-writing a poll loop. Use when a dispatched or pushed build takes minutes to finish and its per-job results decide the next step.

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。

Grind through ready beads serially in priority order, one at a time in the current worktree, without stopping between issues. Use when asked to work the beads queue, grind the backlog, keep working through ready issues, or make unattended progress overnight. For concurrent worktrees instead, use beads-parallel-grinding.

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。

Size the agent-browser Chromium window to fill its current screen, leaving a configurable bottom margin for the desktop panel. Use before any agent-browser automation that needs the full screen visible without elements overlapping or scrolling off (e.g. Xero, dense web apps).

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。

Creates a Beads issue for a requested piece of work, completes exactly that work, and closes the issue. Use when the user invokes `/bx` or `$bx`, or asks for a bead to be created and the described work done in the same go. For creating a bead without doing the work, use the `bc` 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。

Corrects output that refers to entities by bare identifier, restating it with a human-readable label beside every ID, and keeps that rule for the rest of the conversation. Use when the user invokes `/ids` or `$ids`, or complains that bead IDs, PR numbers, commit SHAs, or ticket keys were given without titles.

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。

Stage whole files, selected hunks, or selected lines in Git without interactive prompts. Use when preparing an exact commit boundary while preserving unrelated working-tree changes.

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。

Creates a Beads issue for a described problem or piece of work without doing the work itself. Use when the user invokes `/bc` or `$bc`, or asks to file, log, or record a bead for something. To also carry out the work, use the `bx` 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。

Root-causes one specific mistake the agent just made, such as not committing despite instructions to, by checking it against the loaded AGENTS.md, CLAUDE.md, skills, and Beads memories, delegating the investigation to a separate agent where the harness supports one; proposes concrete context improvements, and lets the user choose which to apply and how to remediate. Use when the user invokes `/learn` or `$learn`, with or without a description of the mistake, including `/learn /qs`-style shorthand naming the corrective command. For a broad end-of-session documentation sweep, use `documentation-updates` (`/reflect`) 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。

Drafts a Certificate of Trust (Abstract/Memorandum of Trust) that verifies trustee authority for third-party reliance without disclosing full trust terms. Use when preparing trust certificates for real estate closings, bank account openings, business transactions, or any context requiring trustee authority verification with UTC-compliant, privacy-preserving disclosure.

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。

Drafts code-compliant California responses to Requests for Production (CCP § 2031.010 et seq.) for Superior Court. Use when the user mentions California RFP responses, CCP 2031, discovery objections, compliance statements, inability to comply, privilege objections, Bates numbering, verification requirements, or responding to document requests in California state court. California Superior Court only — not for federal court without substantial modification.

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。

Verifies legal citations and retrieves source material using the case.dev Legal Research API and CLI. Use when validating a citation, confirming a case exists, pulling source text, finding related authorities, extracting citations from a brief or opinion, or building a filing-ready authority check without branded citator terminology.

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 for affordances, hierarchical control, nullspace composition, and information-seeking action selection in embodied agents. NOT for pure symbolic planning, generic RL tuning, or domains without sensorimotor grounding.

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 Kafka consumer groups that survive rebalances, hit the right delivery guarantee (at-most/at-least/exactly-once), and handle poison messages without stalling the topic. Use when picking a partition assignment strategy (Range vs Sticky vs Cooperative-Sticky vs the new KIP-848 protocol), tuning heartbeat / session / max.poll.interval timeouts, choosing manual vs auto offset commits, designing dead-letter or retry topics, or migrating from Classic to the next-gen Consumer protocol. NOT for Kafka cluster ops (broker tuning, partition reassignment), schema design (Avro/Protobuf/Schema Registry), or stream processing topology (use a kafka-streams 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。

Prepares for hiring manager rounds at Staff+ (L6+) level — scope of impact, influence without authority, ambiguity navigation, mentorship, strategic thinking. Use when practicing HM rounds or calibrating story depth for target level. Activate on "hiring manager round", "HM screen", "staff level", "scope of impact". NOT for coding interviews, system design, behavioral/values rounds, or resume 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。

Design deployment-focused distillation systems that balance model size, accuracy, calibration, and cascade escalation under real resource limits. Best for teacher-student compression, threshold design, and failure-aware deployment. Activate on "model compression", "teacher- student", "distillation score", "cascade model", "edge deployment", or "model calibration". NOT for generic deep-learning overviews, prompt optimization, or training work without a concrete distillation objective.

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。

Professional network graph analyst identifying Gladwellian superconnectors, mavens, and influence brokers using betweenness centrality, structural holes theory, and multi-source network reconstruction. Activate on 'superconnectors', 'network analysis', 'who knows who', 'professional network', 'influence mapping', 'betweenness centrality'. NOT for surveillance, discrimination, stalking, privacy violation, or speculation without 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。

Heart rate variability biometrics and emotional awareness training. Expert in HRV analysis, interoception training, biofeedback, and emotional intelligence. Activate on 'HRV', 'heart rate variability', 'alexithymia', 'biofeedback', 'vagal tone', 'interoception', 'RMSSD', 'autonomic nervous system'. NOT for general fitness tracking without HRV focus, simple heart rate monitoring, or diagnosing medical conditions (only licensed professionals diagnose).

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 running analytical SQL over Parquet/CSV/JSON without a warehouse, replacing pandas for data wrangling, joining S3 data in-place, building local data marts, or embedding OLAP into an app. Triggers: read_parquet/read_csv setup, partitioned dataset queries, hive partitioning, glob patterns for S3, COPY TO export, attach Postgres/MySQL, UDFs in Python/R, MotherDuck cloud sync, columnar performance vs row stores. NOT for OLTP workloads (concurrent writes), distributed analytics at petabyte scale (use Spark/Trino), or vector search (use pgvector/Lance).

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 in drone systems, computer vision, and autonomous navigation. Specializes in flight control, SLAM, object detection, sensor fusion, and path planning. Activate on "drone", "UAV", "SLAM", "visual odometry", "PID control", "MAVLink", "Pixhawk", "path planning", "A*", "RRT", "EKF", "sensor fusion", "optical flow", "ByteTrack". NOT for domain-specific inspection tasks like fire detection, roof damage assessment, or thermal analysis (use drone-inspection-specialist), GPU shader optimization (use metal-shader-expert), or general image classification without drone 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。

Use when designing matrix builds (OS x version x dimension), composing reusable workflows, gating jobs on conditions, doing OIDC to AWS/GCP/Cloudflare without long-lived secrets, sharding tests across runners, or fixing cache invalidation. Triggers: workflow_call between repos, fail-fast: false tradeoffs, exclude/include matrix surgery, environment protection rules, OIDC trust policy setup, concurrency cancellation on duplicate pushes, artifact reuse across jobs, conditional job matrices computed at runtime. NOT for GitLab CI / CircleCI / Jenkins (different yaml dialects), self-hosted runner administration, or local act dev.

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。

Prepare high-quality datasets for LLM fine-tuning with filtering, deduplication, augmentation, and RLHF data formatting. Activate on: fine-tuning data, training data curation, RLHF dataset, data quality filtering, SFT dataset. NOT for: model training infrastructure (ai-engineer), prompt engineering without fine-tuning (prompt-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。