52건 · 관련도순
The alphabetical-sort invariants the hyperlane-registry CI / CodeRabbit enforces on warp route YAML (deploy.yaml and config.yaml) — top-level chain entries sorted by chain name, and keys within each entry in strict alphabetical order — plus the canonical per-file key orderings and a verification pass. Referenced by any warp deploy/update skill that writes or edits a registry YAML file.
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Draft replies to comments on your Facebook Page's posts, in your Page voice. Use when the user pastes the comments under one of their Page posts and wants on-brand replies that earn more comments and shares. Drafts 1-3 variants per comment using proven templates (answer, thank plus add value, handle the complaint, turn it into a share). Publora has no Facebook comment endpoint, so every draft returns as a copy-paste block to post yourself. Not for writing top-level posts (use fb-post-writer).
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Use REUSE when an agent needs file-level licensing clarity instead of guessing from a single top-level LICENSE file. The agent checks compliance, adds or verifies SPDX headers, pulls missing license texts into LICENSES/, and produces a concrete remediation list or SPDX export.
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Develop evidence-backed structural and architectural security hardening proposals from vulnerability disclosures, supplied findings, incident or assessment documents, source code, or a completed Codex Security scan. Use when a user asks for systemic improvements, alternatives beyond per-finding patches, before-and-after security architecture views, engineering tradeoff analysis, or an implementation-ready plan for a selected hardening option. Also use automatically after a Codex Security scan with reportable findings when the top-level scan workflow requests final-report hardening guidance.
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Draft a reply or a value-add quote post for a specific Threads (Meta) post from its URL. Use to reply in a conversation, answer a creator, or quote-post with added value. Parses the post URL, reads pasted context, decides reply vs quote post, and drafts 1-3 warm variants in your voice. A reply to another user is a separate post and Publora cannot target it, so the draft is returned as a copy-paste block to post yourself. Not for top-level posts (use threads-post-writer).
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Alternate /pr-review and /pr-address on a PR until the PR is truly mergeable — no new review findings, zero unresolved inline threads, zero unaddressed top-level reviews or issue comments, all CI checks green, and two consecutive quiet polls after CI settles. Use when the user wants a PR polished to merge-ready without setting a fixed number of rounds.
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Fix docker exec hanging when starting background processes (servers, daemons) inside containers. Use when: (1) docker exec never returns despite using & or nohup, (2) background server started in container causes docker exec to hang indefinitely, (3) env_startup_command in SWE-bench or similar frameworks times out, (4) setsid/disown needed for proper process detachment in Docker. Root cause: docker exec tracks ALL processes in the exec session, not just the top-level PID.
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Audit top-level documentation (README, SPEC, PRODUCT) against recent git history to find drift shipped features missing from docs or features listed as upcoming that already landed. Proposes minimal edits, creates a branch, and opens a PR. Use when asked to review docs for accuracy, after major feature merges, or on a periodic schedule.
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Build and audit PFC2D/PFC3D 5.0 model foundations for asphalt cases, including lifecycle, domain, balls, walls, clumps, groups, ranges, top-level cmat, staged saves, and source-version purity.
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Export top-level ai-gene-review `proposed_new_terms` entries to a deterministic TSV table.
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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.
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Top-level orchestrator for Flutter feature implementation. Runs the full uninterrupted pipeline: tasks → implement-tasks-sequence → build-verify → pr-review uncommitted. Use after a PRD and tech spec are complete. Trigger phrases: "start job", "start the job", "run the full pipeline", "do it all", "implement the feature end-to-end".
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Use when introducing, reviewing, or renaming a top-level type, table, or domain concept; or choosing where state lives (in-memory vs persistent)
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Top-level orchestrator for the Gaia Skill Tree evidence verification pipeline. Run this when you want to do a full evidence pass — collecting raw sources, verifying live GitHub star counts, running Phase 2B benchmark-source verification, adversarially auditing for quality/formatting issues, and checking that every URL is reachable — all in one coordinated sequence. Trigger phrases: "run the evidence pipeline", "full evidence pass", "verify evidence", "evidence verification pipeline", "run ev-pipeline", "check all evidence", "audit the data lake", "evidence quality sweep", "refresh evidence", "validate evidence sources". Also aliased as /evidence-verification-pipeline. Use the individual sub-skills (ev-collection, ev-star-verification, ev-adversarial-audit, ev-link-validation) only when you need to re-run one phase in isolation; for end-to-end work, always start here.
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Create and own the master game design document (GAME.md — the authored one-pager plus the generated [gen] system/flow maps) and the GD-IDS.yaml facts registry — the top-level, big-picture layer of the GDD and the machine interface the code side reads. Use it to write the master spec from a concept or dialogue, import an existing GDD (a file path or URL), edit GAME.md content ("change a pillar", "rework the monetization stance", "tweak the loop stack"), pitch the game ("pitch" → PITCH.md), re-decompose the systems ("remap"), and — importantly — to add a new system to the design map ("let's add a new system", "add a crafting system to the game design", "add this to the GDD"). This is the structural, map-level layer plus GAME.md content edits. To write or fill in the detailed parameters of one existing system, use /unikit-gd-system; to apply one edit spanning several zones at once use /unikit-gd-apply; to invent a brand-new game concept use /unikit-gd-brainstorm.
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Decompose an IP requirement into submodules, define interfaces, and generate an architecture document plus per-module requirement files and a top-level skeleton
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Use this skill when running local AI models with Docker Model Runner — the `docker model` CLI — e.g. "run an LLM locally with Docker", "pull a model from the ai/ namespace", "connect my app to a local model", "use a local model as backend for the Drupal AI module", or when wiring the `models:` top-level element into a compose.yaml. Covers pulling/running models, OpenAI-compatible endpoints, and Compose integration.
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Use when designing, reviewing, or implementing a sidebar for an Apple-platform app — top-level navigation only, grouped sections, NavigationSplitView, consistent SF Symbols, and safe compact-width behavior.
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Use this skill when a company needs its information security policy set written or rebuilt, or asks "write our security policies", "draft the information security policy", "we need policies for the audit", "policy pack for a startup", "our template policies are 40 documents nobody reads" or "which policies do we actually need". Maps the policy set to the company's size and owners, drafts the top-level policy and the topic policies in testable language that reflects what the company does, flags commitments that need a decision, and prepares the approval and communication record for leadership.
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Top-level router for Exasol work. Use for any Exasol database, exapump, SQL, BucketFS, extension, integration, UDF, Script Language Container, or Exasol Personal setup task, then route to the narrowest specialized Exasol skill.
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Given the product offering and existing page inventory, create new core landing and resource pages (homepage refresh, features, solutions, pricing, comparison, resource hubs, about) that capture core product intent using the query-fanout pattern. Use this skill whenever the user asks to "spawn pages", "generate landing pages", "create marketing pages", "build a pricing page", "add a solutions page", "build out the site", "fill in missing pages", or wants new top-level marketing/product pages. Output is one new page per route in the project's native file format (component or markdown), matching the existing page style and framework idiom.
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Flat page switching with AdwViewStack + AdwViewSwitcher (3-5 top-level views) and ViewSwitcherBar on narrow widths. Use when an app needs tabs/views in the header bar.
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Identifies differential m6A methylation between conditions from MeRIP-seq paired IP/input data using exomePeak2 with `bam_ip` + `bam_input` (control arm) and `bam_treated_ip` + `bam_treated_input` (treatment arm) for integrated GC-bias-aware differential calling (Liu 2022 *NAR Genom Bioinform* 4:lqac046), QNB beta-binomial test (Liu 2017 *BMC Bioinformatics* 18:387), MeTDiff HMM-based differential bundled with MeTPeak, RADAR (Zhang 2019 *Genome Biol* 20:294) with its `filterBins -> diffIP -> reportResult` workflow, and the defensible paired-symmetric case of edgeR / DESeq2 on featureCounts-on-peaks matrices when batch / lot covariates need explicit fixed-effect handling (exomePeak2's top-level API does NOT accept arbitrary covariates). Covers paired vs unpaired vs interaction designs, batch confounding (antibody lot, RNA prep, sequencing run) and the per-lot meta-analysis strategy when exomePeak2 is the primary caller, the stoichiometry-vs-expression-vs-IP-efficiency confound that all MeRIP differential methods inherit, normalisation choice (size factor on IP, on input, on per-sample IP/input ratio), the McIntyre 2020 reproducibility caveat, effect-size filtering as a guardrail against under-powered N=2 designs, and orthogonal-validation routes for absolute stoichiometry (GLORI / SAC-seq / m6Anet `mod_ratio`). Use when comparing m6A levels across two or more conditions, choosing between exomePeak2 / QNB / RADAR / MeTDiff for a given design, handling batch confounding when exomePeak2's API is too rigid, normalising against input properly, distinguishing real hyper- / hypo-methylation from expression-level shifts, applying effect-size thresholds, interpreting volcano plots of differential peaks, or planning a follow-up orthogonal stoichiometry validation.
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Identifies differential m6A methylation between conditions from MeRIP-seq paired IP/input data using exomePeak2 with `bam_ip` + `bam_input` (control arm) and `bam_treated_ip` + `bam_treated_input` (treatment arm) for integrated GC-bias-aware differential calling (Liu 2022 *NAR Genom Bioinform* 4:lqac046), QNB beta-binomial test (Liu 2017 *BMC Bioinformatics* 18:387), MeTDiff HMM-based differential bundled with MeTPeak, RADAR (Zhang 2019 *Genome Biol* 20:294) with its `filterBins -> diffIP -> reportResult` workflow, and the defensible paired-symmetric case of edgeR / DESeq2 on featureCounts-on-peaks matrices when batch / lot covariates need explicit fixed-effect handling (exomePeak2's top-level API does NOT accept arbitrary covariates). Covers paired vs unpaired vs interaction designs, batch confounding (antibody lot, RNA prep, sequencing run) and the per-lot meta-analysis strategy when exomePeak2 is the primary caller, the stoichiometry-vs-expression-vs-IP-efficiency confound that all MeRIP differential methods inherit, normalisation choice (size factor on IP, on input, on per-sample IP/input ratio), the McIntyre 2020 reproducibility caveat, effect-size filtering as a guardrail against under-powered N=2 designs, and orthogonal-validation routes for absolute stoichiometry (GLORI / SAC-seq / m6Anet `mod_ratio`). Use when comparing m6A levels across two or more conditions, choosing between exomePeak2 / QNB / RADAR / MeTDiff for a given design, handling batch confounding when exomePeak2's API is too rigid, normalising against input properly, distinguishing real hyper- / hypo-methylation from expression-level shifts, applying effect-size thresholds, interpreting volcano plots of differential peaks, or planning a follow-up orthogonal stoichiometry validation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.