「gates」の検索結果

Step 3 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the literature search strategy from outline.json — discover candidate papers via web search, verify them through Semantic Scholar (Levenshtein > 70 fuzzy title match, temporal cutoff, dedup by paperId), build a BibTeX file, and draft Introduction + Related Work using ≥90% of the verified pool. Runs in parallel with the plotting-agent. TRIGGER when the orchestrator delegates Step 3 or when the user asks to "find citations for my paper", "draft the related work", or "build the bibliography".

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。

Step 5 of the PaperOrchestra pipeline (arXiv:2604.05018). Iteratively refine drafts/paper.tex by simulating peer review and applying targeted revisions, with strict accept/revert halt rules. Maintains a worklog and snapshots each iteration so revert is real, not symbolic. TRIGGER when the orchestrator delegates Step 5 or when the user asks to "refine the draft", "iterate on the paper", or "run peer review on this paper".

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。

Step 2 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the visualization plan from outline.json — render plots and conceptual diagrams from experimental_log.md and idea.md, optionally refine via VLM critique loop, and produce context-aware captions. Runs in parallel with the literature-review-agent. TRIGGER when the orchestrator delegates Step 2 or when the user asks to "generate the figures for my paper" or "render the plots from this experiment log".

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。

Step 1 of the PaperOrchestra pipeline (arXiv:2604.05018). Convert (idea.md, experimental_log.md, template.tex, conference_guidelines.md) into a strict JSON outline containing a plotting plan, literature search plan (Intro + Related Work), and section-level writing plan with citation hints. TRIGGER when the orchestrator delegates Step 1 or when the user asks to "outline a paper from raw materials" or "generate the paper structure".

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。

Step 4 of the PaperOrchestra pipeline (arXiv:2604.05018). ONE single multimodal LLM call that drafts the remaining paper sections (Abstract, Methodology, Experiments, Conclusion), extracts numeric values from experimental_log.md into LaTeX booktabs tables, splices the generated figures from Step 2, and merges everything into the template that already contains Intro + Related Work from Step 3. TRIGGER when the orchestrator delegates Step 4 or when the user asks to "write the methodology and experiments sections" or "fill in the rest of the paper".

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。

Validated Google Play release — runs the pre-flight checks and clears the Play policy gates, builds a signed app bundle with a git-stamped versionCode, uploads to a track, and walks staged rollout (with halt/roll-forward). Use when releasing an Android app to Play.

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。

Send, read, and respond to Telegram messages as Claudicle via the @claudicle_bot Bot API. Use this skill when sending Telegram messages (text, Markdown, inline keyboards), building approval gates with tappable buttons, checking the shared inbox for unhandled Telegram messages, answering callback queries, managing Telegram memory context, or checking bot and listener status. Five purpose-built scripts (send, check, status, callback, memory) wrap the python-telegram-bot v22 polling adapter at ~/.claudicle/adapters/telegram/ with REST-based senders (no asyncio). Pairs with /telegram-respond for the cognitive pipeline and with mazkir-callback-watcher.py for the Mazkir approval gate.

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。

Find and score legitimate external authority and backlink opportunities as a dry-run register, using relevance, platform rules, risk, target-page fit, and explicit user approval gates. Use this skill when the user asks where links to a target site could be placed effectively, but never post, submit, DM, email, open PRs, or edit external accounts without separate explicit approval.

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。

Builds, validates, packages, tests, and optimizes deployment-ready Skill files (SKILL.md + references/ + scripts/ + agents/) from design specifications. Three pre-build gates + 9-dimension quality gate (with D9a/b/c empirical evidence tiers) + behavioral iteration loop + automated description optimizer + blind version comparator. Use for building, reviewing, revising, testing, or optimizing Skills. Trigger on: "build this Skill," "review this Skill," "test my Skill," "optimize the description," "compare these Skill versions," "should this be a hook instead," "build a template first." Also: "my Skill doesn't activate," "my description truncates," "my SKILL.md is too long," "my Skill is overtriggering." Do NOT use when designing Skill methodology — that's design work, not packaging. Do NOT use for prompt compilation, project auditing, or prompt scoring (use rootnode-prompt-compilation, rootnode-project-audit, or rootnode-prompt-validation if available).

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。

Generalised autonomous optimisation loop — soft RLVR for any artifact a user can measure. Use this skill whenever a user wants to iteratively improve an artifact — code, prompts, documents, configs, designs, content — by running structured experiments, evaluating results against a multi-dimensional rubric, and learning from each attempt. Triggers include: "optimise this", "keep improving until it's good", "run experiments on", "autoresearch", "iterate on this overnight", "try different approaches and pick the best", or any request implying repeated evaluate-and-improve cycles. Also use when the user wants to improve a system prompt, a data pipeline, a writing style, or any artifact where quality can be decomposed into measurable tracks. For inference optimisation tasks (model latency, throughput, quantization, GPU deployment), a* delegates the low-level tuning to AITune while maintaining quality tracking and learning.

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。

Direct a claim-driven research experiment project from post-Idea intake through method realization, prioritized evidence collection, Human Gates, and Evidence Freeze. Use for scientific planning, state transitions, queues, budgets, or recovery; not for running code or independently auditing results.

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。

Plan a software release cycle with milestones, feature freezes, release candidates, and go/no-go criteria. Covers calendar-based and feature-based release strategies. Use when starting planning for a major or minor version release, transitioning from ad-hoc to structured release cadence, coordinating a release across multiple teams or components, defining quality gates for a regulated project, or planning the first public release (v1.0.0) of a 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。

Implement GitOps continuous delivery using Argo CD or Flux with app-of-apps pattern, automated sync policies, drift detection, and multi-environment promotion. Manage Kubernetes deployments declaratively from Git with automated reconciliation. Use when implementing declarative infrastructure management, migrating from imperative kubectl commands to Git-driven deployments, setting up multi-environment promotion workflows, enforcing code review gates for production, or meeting audit and compliance requirements.

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 multi-stage CI/CD pipelines using GitHub Actions with matrix builds, dependency caching, artifact management, and secret handling. Create workflows that span linting, testing, building, and deployment stages with parallel execution and conditional logic. Use when setting up automated testing and deployment for a new project, migrating from Jenkins or CircleCI to GitHub Actions, implementing matrix builds across platforms, adding build caching, or creating multi-stage pipelines with security scanning and quality gates.

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Parallel SDLC batch runner. Analyzes a list of independent task descriptions, groups them by heuristic file-conflict prediction, dispatches one worktree-isolated background agent per task (each running the full pipeline-orchestrator: BA → Dev → QA → Sec → Docs), and aggregates results into a single batch summary. Use when: - `/sdlc:batch` invokes this skill after parsing its arguments (Step 2 of commands/batch.md) - You have 2+ independent feature/fix descriptions to run through the SDLC pipeline in parallel Do NOT use for: - A single task (use pipeline-orchestrator directly via /sdlc:start) - Tasks that must share a single working tree (this skill isolates each task in its own git worktree)

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 setting up or modifying CI/CD pipelines, quality gates, test runners, or deployment pipeline configuration through workflow files. Not for triggering a deployment.

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 a repository needs Git safety controls: guard destructive commands, set up gitignore or fix gitignore when untracked files keep appearing, or install or repair a repository-local pre-commit hook from project gates, including package-manager-native commit-time checks. Not for remote, credential, publish, deploy, or irreversible 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。

Use when a parser, protocol, or file format fuzzer stalls at fixed-token validation gates and needs a coverage dictionary. Not for patching the SUT: use fuzzing-obstacles.

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 filing an approved task spec as a GitHub issue with a local archive and optional worktree implementer. Don't use for spec drafting without human interrogation and redaction gates.

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 a strict multi-iteration Reflex Loop with phases (PLAN, PRODUCE||PREPARE, EVALUATE, CRITIQUE, REFINE) to improve an artifact until quality gates pass or iteration limits are reached. Use when user asks for iterative refinement, quality-gated generation, or "generate -> critique -> refine" loops.

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。

Execute governed implementation workflow with work items, RFC/ADR checks, phase gates, testing, and closure. Use when: (1) User invokes /gov, (2) A non-trivial change needs work item tracking, (3) Implementation may require RFC/ADR handling

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。

Multi-angle code and plan review with security, scope, and UI profiles. Use when reviewing code, plans, PRs, or running pre-merge quality gates.

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 a strict multi-iteration Reflex Loop with phases (PLAN, PRODUCE||PREPARE, EVALUATE, CRITIQUE, REFINE) to improve an artifact until quality gates pass or iteration limits are reached. Use when user asks for iterative refinement, quality-gated generation, or "generate -> critique -> refine" loops.

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。

Finish NowStack Mobile Google Play setup and internal Android releases. Use for signed AAB upload, gpc/browser fallback, privacy/app-content gates, or gpc commit failures.

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。