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概要と使いどころ
Certifies that a feature achieves its original objectives via goal-backward verification (SAM Stage 7). Use when all tasks pass forensic review — starts from expected outcomes, works backwards to verify each was achieved, and returns CERTIFIED or NOT_CERTIFIED with specific gaps.
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One-line definitions of development-harness (dh) plugin terminology — RT-ICA, ARL, SAM, the S1-S7 pipeline stage names, Impact Radius — each with a pointer to its canonical source file. Use when a dh skill, agent, or workflow step references a term without defining it, before guessing what the term means from its observed outputs, or when asked what a dh concept or acronym stands for.
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Use when exploring unknown structured data files with dasel v3 — discover schema, list keys, find nested values, sample arrays, identify data types across JSON, YAML, TOML, XML, CSV, HCL, INI formats
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Shapes for running many sub-agents at once — fan-out with a barrier, maker/checker, generate-and-filter, tournaments for ranking, hypothesis fan-out for root cause, and loops that stop on a condition with a cap. Use when a phase has several independent targets, when a task is too large or too repetitive for one window, when the same edit applies across many files, when ranking or judging a large set, when several hypotheses compete, or when work must repeat until a signal says stop. Does not apply when units depend on each other's results or the cause is still unknown — investigate first, then parallelize.
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DRAFT. Build anonymizable host-prep one-pagers for must-meet guests at an in-person event: rank, enrich, light research, warm-intro angles, PDF pack. Not installed by deepline skills. No real customer data in repo samples.
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Use this skill when a human needs to review a Deepline Play result and hand feedback, labels, or approval back to the agent for revision, evaluation, comparison, or bounded iteration. Triggers on “put this run in a Sheet,” “review these results,” “read my feedback,” “make this a standing rule,” “never regress on this case,” “compare these runs,” “keep improving,” or “add the revised run to the same spreadsheet.” Skip ordinary Play authoring or execution with no human review loop, generic spreadsheet work, and one-off CSV export.
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。
Interviews a researcher in rounds until an idea, design, or draft has no unexamined decision — numbered questions, each with why it matters and a recommended answer, facts looked up rather than asked, and settled decisions written to a file. Stages are idea (topic or hunch to a falsifiable question and contribution claim), design (estimand, identification, sample and power, measurement, analysis plan, pre-registration, venue), and defend (reviewer objections to a finished design or draft). Use when the user says "grill me", asks to stress-test or poke holes in an idea, design, or plan, asks what they are assuming, or brings an idea that is not yet a design. --plan grills software or process plans.
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。
Runs several language models as independent coders on the same labeling or discovery task and reads their disagreement as data — panel assembly for model diversity, keeping votes independent, consensus rules, agreement statistics (Cohen's and Fleiss kappa, Krippendorff's alpha), the correlated-errors caveat that stops agreement being mistaken for validity, human validation beyond the panel, and reporting. Use when the user asks about a council, panel, ensemble, or jury of models, asks how to combine several models' labels, or asks what kappa or alpha to report for model coders. Single-model codebook and validation work goes to text-classification, per-item confidence to llm-calibration-logprobs.
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。
Audits fielded survey-response data for registered elements, data quality, bot and AI-automation screening, and sample integrity, and produces an appendix-ready quality report. Use at soft launch before full field, after fielding before outcomes are analyzed, or when asked what a study did about bots and AI respondents.
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Designs multi-country survey experiments: case selection, localization and TRAPD translation, stimulus calibration, per-country power, and pooled versus per-country analysis with measurement-equivalence checks. Use when fielding the same experiment in several countries.
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。
Audit fielded survey response data for registered elements, data quality, bot and AI-automation screening, and sample integrity, and emit an appendix-ready quality report. Use at soft launch or after fielding, before outcomes are analyzed.
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。
Delegates coding tasks from Codex to local Claude Code in print mode while preserving Claude's normal runtime customizations by default. Use when: (1) You want Codex to call Claude Code locally, (2) You need Claude-side skills, plugins, MCP servers, custom commands, CLAUDE.md rules, or workspace settings to stay active, (3) You want resumable Claude sessions from Codex via SESSION_ID, (4) You need thin `claude mcp` / `claude plugin` passthrough from the same bridge.
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。
Fixture for promote dry-run smoke
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。
The commit-R protocol: a test-driven rewrite of one compartment of Anabasis v2. Commit what is in flight, remove the compartment's tests in an "R:" commit, write them again from a stated hypothesis so the production code fails on purpose, remove the production files in a second "R:" commit, then write the production code again, rewrite the neighbouring functions the old shape bent, and delete what served only it. Use when the operator says "commit R", "commit-R protocol", "remove and rewrite the tests" or "rewrite from scratch", or asks for a test-first pass that looks for a faster, simpler path to the same outcome.
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-provider deliberation panel for COMPLEX, multi-view questions — architecture, strategy, market research, and codebase sweeps. Runs a 4-stage deliberation across the provider fleet (diverge → contrarian red-team → adversarial verify → cited synthesis), the same multi-perspective rigour the plan-gate already applies to plan reviews, generalised to arbitrary questions. Use when one model's answer isn't enough and you want convergence THROUGH disagreement + verification, not a single opinion.
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 MotherDuck databases, tables, columns, shares, and sample data to understand an available dataset.
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Run the oncall handoff for a rotation window — the whole handoff, not just a document: build the summary (what the incoming oncall needs first, what's still open, incidents with impact numbers, alert and page counts, hygiene suggestions, every number traceable to a source), post it for the outgoing oncall to correct, walk the incoming oncall through the open items in the thread, update the list as they respond, and note when they acknowledge. Runs mainly in the team's standing oncall / monitoring channel, normally as a scheduled routine firing at rotation change so the report is waiting when the shift turns over; can also be run by hand and works from an incident channel. Use when a handoff routine fires, or on "handoff", "hand over", "oncall summary", "weekly oncall report", "what happened this shift / this week". Re-running for the same window updates the report rather than duplicating it. Unattended runs carry a run-summary block and at least one chart.
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Expert FinOps guidance for cloud, AI, and SaaS technology spend. Covers AI cost management, agentic FinOps, GenAI capacity planning, self-hosted vs managed inference, Anthropic billing, open-weight vendor APIs (DeepSeek, Qwen, Kimi, GLM), AWS (EC2, Bedrock, SageMaker, Savings Plans, CUR), Azure (reservations, AHB, OpenAI PTUs), GCP (Vertex AI, BigQuery), OCI, Kubernetes cost allocation, data platforms (Databricks, Fabric F-SKUs, Snowflake), tagging governance, SaaS management (SAM, shadow IT), AI coding tools (Cursor, Claude Code, Copilot, Codex), ITAM, allocation, showback, chargeback, anomaly management, KPIs and benchmarking, waste detection playbooks, workload onboarding and M&A, and GreenOps (cloud carbon, CSRD). Use for any question about technology cost or waste in your estate - expiring commitments or RIs, NAT gateway bills, idle VMs, snapshot sprawl - and for commitment sizing, rightsizing, allocation, SaaS sprawl, AI dev tool spend, or connecting spend to business value. Built by OptimNow.
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。
Maintain the pure-Go SQLite single-use ticket identity provider, public parser, trusted issuance API, HTTP login capability, cookie and realm binding, portal signing, and TLS consumer tests. Excludes OAuth/SAML protocols and anonymous ticket issuance services.
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。
Apply when you catch yourself writing the same instruction a second time, or notice a recurring correction. Encode the rule as a lint, metadata flag, runtime check, or script instead of more text.
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Use before opening a PR, or whenever asked to self-review a diffusers contribution. Applies the same rubric as the `@claude` CI (checks the diff against references/review-rules.md, traces call paths for dead code). Reports findings grouped by severity, flagging what to fix before submitting (blocking issues + dead code) vs what to leave for the actual review. Report-only — does not edit files.
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。
Review changes in samples/book-app-web for accessibility, responsive layout, tests/build validation, and small beginner-safe 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。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for reverse engineering, malware, DFIR, firmware, pwnable, and native exploit challenges. Use when the user asks to reverse a binary, unpack a sample, inspect a memory dump or PCAP, recover malware behavior, debug a crash, or build or verify an exploit chain under sandbox assumptions. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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。
实战 SRC / 众测 / Bug bounty 漏洞挖掘工作流 skill。包含：5 阶段方法论（intake → recon → enum → hunt → report）、19 个攻击类 playbook（SQLi/XSS/RCE/SSRF/IDOR/CSRF/Path Traversal/File Upload/SSTI/XXE/Race/HTTP Smuggling/OAuth/JWT/SAML/GraphQL/Mobile/LLM/DoS）、305 个结构化 payload、263 个 WAF/EDR 绕过变体、2887 份 HackerOne 真实 High/Critical 已披露案例、77,000+ WooYun 案例统计、国产 OA / 中间件指纹库、银行 / 电信行业垂直 playbook。当用户提到 "src 挖洞 / src 漏洞挖掘 / bug bounty / 众测 / hackerone / 漏洞赏金 / SRC / 任意 X 漏洞 / 渗透测试" 或问"如何挖某个目标 / 怎么测某个 API / 如何绕过 WAF" 时触发。
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。