662 件 ・ 関連度順
概要と使いどころ
Use when judging whether a manuscript's landing point is an ACCOUNTING issue (accounting information / disclosure / audit / standards) versus a corporate-finance mechanism, before drafting for 《会计研究》 (Accounting Research). Use this to decide fit and to re-route finance-mechanism papers to a finance journal before any other acr-* 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。
Use when scoping or sanity-checking a research question for an Academy of Management Journal (AMJ) manuscript — fit, theory-drivenness, and feasibility. Decides whether the idea can earn a theoretical contribution; it does not build the theory itself (use amj-theory-development) or position the literature (amj-literature-positioning).
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 judging whether a management/organization literature is an Academy of Management Annals (Annals)-scale review topic — mature, important, fragmented, and integrable into a new framework — rather than a narrow review. Decides fit and frames the review's animating problem; it does not gather the literature (amann-literature-synthesis) or write the proposal (amann-proposal-framing).
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。
Final QC gate for a rendered 9:16 video ad, run before it is published. One script checks what a machine can decide — exact 1080x1920 size, a hook that moves and speaks in the first second, no frozen stretches, no dead air, no black frames, the brand's real logo on the end card (never a favicon, never a redrawn or wrong logo), end-card colours near the brand palette — and builds one contact sheet (frames with the TikTok/Reels UI safe zones shaded, beside the logo, product images and a font specimen) for the checks that need eyes — font, product likeness, product consistency across scenes, safe zones. A declared silent-text profile covers silent, text-led formats such as kinetic text (no audio track needed, short blank beats between text beats allowed within fixed bounds). Exit 0 PASS / 2 FAIL / 3 ERROR. Use on every finished video master before pinning it.
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。
Generate 3-5 messaging variants for a value proposition, design structured A/B tests, and analyze results to determine which framing resonates most with ICP. Tests can run via LinkedIn organic posts, cold email subject line splits, or both. Pure reasoning for variant generation and analysis — the user deploys the tests through their own tools. Use when a team can't decide between messaging angles and needs data, not opinions.
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。
Turn a brand's facts, a campaign brief and the product into a one-minute Meta ad strategy with its reasoning — goal, audience, objective and placements, budget split, how many ads and how different they must be (generate 3x so the user can choose), the test frame, the success metric, and safety rules for the user to accept. Decides what launch-meta-ad-campaign then executes, and re-reads the strategy after a deep check to show which assumption changed. Use it after intake and before any creative is generated or any campaign is built.
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。
Turns Hi-C/Micro-C FASTQ into a deduplicated, filtered .pairs file with pairtools and decides whether the library worked. Covers the bwa mem -SP5M / bwa-mem2 / chromap --preset hic alignment idiom (mates mapped as independent single-end reads), pairtools parse vs parse2 and the walks-policy choice (5unique pairwise vs all for Pore-C/Micro-C concatemers), pair-type classification (keep UU and rescued UC), dedup (PCR vs optical/by-tile), select by pair_type/MAPQ/distance, restriction-fragment handling (restrict, Arima dual-enzyme, Micro-C/DNase fragment-free), and allele-specific phasing (pairtools phase to two coolers). The library-QC decision uses % long-range cis as the one-number quality metric, trans as the noise floor, orientation balance as fragment-map-free dangling-end/self-circle QC, and % duplicates as a complexity proxy. Use when processing Hi-C/Micro-C/Omni-C reads into pairs, judging library quality, handling multi-enzyme or restriction-agnostic protocols, or generating allele-specific contacts.
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。
Decides how to preprocess plasma cfDNA sequencing data so the recoverable signal survives - library-prep-aware fragment expectations (dsDNA vs ssDNA/adaptase prep), UMI/duplex consensus with fgbio (ExtractUmisFromBam, GroupReadsByUmi --strategy paired for duplex, CallMolecularConsensusReads vs CallDuplexConsensusReads, FilterConsensusReads min-reads "total s1 s2"), the align->group->consensus->RE-align ordering, and the cfDNA dedup trap where naive coordinate dedup collapses nucleosome-coincident independent molecules. Covers when single-strand consensus suffices vs when duplex is mandatory, the singleton/sensitivity tax at low input, and reading the insert-size histogram as a pre-analytical QC instrument. Use when processing plasma cfDNA reads before fragmentomics, ctDNA mutation calling, or tumor-fraction estimation.
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。
Decides whether and how to polish a draft genome assembly to raise consensus accuracy (QV) with read-type-matched tools - Racon and medaka (ONT consensus), dorado polish, Polypolish and pypolca (Illumina, repeat-aware), Pilon (legacy short-read), NextPolish/NextPolish2, Hapo-G (haplotype-aware), ntEdit, and DeepPolisher/PEPPER-Margin-DeepVariant for human. Covers the do-not-polish-HiFi rule, the medaka basecaller-model footgun, held-out Merqury QV as the only honest stop signal, and the haplotype-collapse trap. Use when correcting homopolymer indels or residual SNPs in a long-read assembly, deciding if a HiFi assembly needs polishing, or choosing an ONT vs hybrid vs short-read polishing chain.
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。
Batch effect correction for CRISPR screens covering ComBat empirical-Bayes, RUV, SVA, control-sgRNA normalization, and the model-based alternative of including batch as a covariate in MAGeCK MLE or Chronos. Covers screen-specific batch sources (passage cohort, library lot, infection day, sequencing run, Cas9 lot, FBS lot), PCA + variance-decomposition diagnostic to decide if correction is needed, when correction harms biology by over-correcting condition into batch, limma removeBatchEffect for visualization-only correction, and relationship to multi-condition design matrices. Use when combining screens for joint analysis, when passage cohort confounds biology, when DepMap-style panels need Chronos with batch covariates, when picking ComBat vs RUV, or when correction harms biology and should be replaced with explicit covariate modeling.
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 evaluating whether a skill belongs in a library. Preview content, check frontmatter, validate structure, and decide whether to keep, curate, or remove.
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。
Bug → spec protocol. When a bug is found or a test fails, trace the cause, decide whether a new §V invariant would catch recurrence, append to §B. This is the one non-obvious thing SDD does that plan-then-execute doesn't. Triggers on test failure, bug report, post-mortem, or explicit user ask.
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。
Triage, repair, and close MCP attribution issues from the local report API with evidence-driven decisions and isolated Worktrunk worktrees. Use this skill when Codex needs to process `tool` attribution issues and skills-related attribution issues, inspect related runs, decide whether the issue is actionable in `mcp/src` or `config/source/skills`, update attribution fields as `owner=codex`, and then complete the fix loop through GitHub issue tracking, worktree-based code changes, PR submission, and follow-up iteration when the problem is repairable.
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 to pick the cheapest good-enough model or effort for a turn or a delegated task (lanes small to escalate), to decide continue/retry/verify/escalate/complete after each cycle, or to tune routing.
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 researching social posts, creators, reactions, or trends. Jev ranks discovery cards and decides when opened, source-linked evidence is enough for a bounded report.
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 all four review skills (investor, customer, operator, skeptic) on a business plan in sequence, then auto-decide where verdicts agree and surface only disagreements + taste decisions to the user. One command = full review gauntlet, intelligently filtered. Use when a plan is ready to be stress-tested before commit. Triggered by: 'panel review', 'review panel', 'run all reviews', 'review gauntlet', '审议会', '四方评审'.
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。
Weekly business retrospective. Reads all snapshots, learnings, skill-usage telemetry, and (if provided) revenue data from the past week. Outputs: what got decided, what shipped, what's stalled, skill activity, suggested next focus. Surfaces unused skills as activation prompts. Use at end of week or end of sprint. Triggered by: 'weekly retro', 'business retro', 'what did we ship', 'how's the week going', '周复盘', '业务回顾', '本周复盘'.
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。
When the user wants to plan website structure, decide which pages to build, or prioritize pages for a new or existing site. Also use when the user mentions "website structure," "site structure," "which pages do I need," "page planning," "sitemap planning," "Must Have pages," "website architecture," or "site hierarchy." For a specific page template (e.g. homepage), use homepage-generator or landing-page-generator as appropriate. Not for organic SEO roadmap alone; use seo-strategy.
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。
When the user wants to decide domain structure for multiple products or brands—subfolder vs subdomain vs independent domain. Also use when the user mentions "subfolder vs subdomain," "subdirectory vs subdomain," "multiple products domain," "multiple websites," "brand architecture," "branded house," "house of brands," "where to host product," "domain structure," or "hub-spoke domain." For brand SERP, use multi-domain-brand-seo.
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。
Map stakeholders, decision rights, influence and blockers from supplied evidence. Use when ownership is unclear or the stakeholder landscape 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。
Audit existing content across a site to decide what to keep, update, merge, redirect, or delete. Use this skill whenever the user wants to audit existing content, fix content decay, resolve keyword cannibalization, prune underperforming pages, prioritize content updates, or apply a keep/update/merge/redirect/delete framework to a content library. Triggers on content audit, content decay, content refresh, cannibalization, keyword cannibalization, prune content, delete pages, redirect old pages, content inventory, what to keep, what to update, content scorecard, evergreen refresh. Also triggers when traffic is dropping site-wide and the cause might be content quality, even if 'audit' is not said explicitly.
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。
Designing side-by-side comparison tools (plan-compare, product-compare, alternative-compare) that help users decide rather than just listing features. Axis selection, default-comparison logic, recommendation discipline. Honest about feature-list-dump (every feature in a row, no decision support), hidden-recommendation (biased comparison pretending to be neutral), and honest-comparison-with-guidance (genuine comparison plus opinionated recommendation) patterns. Triggers on comparison tool, plan compare, product compare, alternative compare, vs page, decision support tool. Also triggers when conversion through comparison stages is poor, when users are abandoning at the comparison step, or when a comparison tool is being scoped for the first time.
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。
Systematic content refresh discipline. Quarterly audits, refresh prioritization (which pieces, when, how deep), refresh-vs-merge-vs-delete decisions, the lifecycle that distinguishes intentional refresh from set-and-forget decay. Builds on the refresh sections of pillar-content-architecture and editorial-qa with a program-level discipline. Triggers on content refresh, content decay, content audit, refresh prioritization, content lifecycle, refresh strategy, traffic decay, ranking drop, content freshness, evergreen content, content maintenance. Also triggers when traffic is eroding silently across an aging content library, when teams cannot decide which pieces to refresh, or when refresh work is happening but the impact is unclear.
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。
Produce honest product reviews and buying guides without fabricated first-hand experience, using disclosed evidence tiers: verified specs, owner-experience synthesis at scale, expert triangulation, and hands-on only when true. Use this skill whenever the user wants to write product reviews or buying guides without hands-on access, set up a review methodology, add evidence disclosure to review content, align reviews with Google's reviews system or FTC affiliate disclosure expectations, or decide when Review and Product schema are honest to use. Triggers on product review, buying guide, best-of list, review methodology, evidence basis, hands-on testing, we tested, affiliate review site, review disclosure, methodology block, original research, reviews system. Also triggers when review content claims testing that did not happen, or when an affiliate site needs a trust mechanism that survives scrutiny.
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。