Decides what content to make and why — topic territory, format mix, cadence, and how content connects to a business outcome rather than to traffic. Use this to plan a content program, choose topics, build an editorial calendar, decide which formats and platforms to commit to, or diagnose why content is producing audience but not results.
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A content program works when a defined audience learns to expect a specific kind of value from you. That requires a territory narrow enough to own: the intersection of what you know unusually well, what your buyer needs help with, and what nobody else is covering properly.
Test it: could a competitor publish your last ten pieces without anyone noticing? If yes, you have a topic list.
Every piece should have one job, and the job dictates the format:
Programs skew heavily to reach and then wonder why the audience does not convert. Budget across all four deliberately.
Pick a frequency sustainable at your worst week, not your best. Irregular publishing costs more than infrequent publishing, because the audience stops expecting you.
Two platforms done properly beat five done adequately. Choose by where the audience already is and which format you can actually sustain — not by reach numbers.
Every piece should be planned with its derivatives: the long piece is the source, and the short-form versions are extracted, not written separately.
Measure by job. Reach content is judged on reach; conversion content on conversion. Judging everything on traffic is why content programs drift toward the reach end and stay there.
Set a review point where a topic that is not working gets dropped. Content strategies fail by accumulation.
references/sources.md in this skill lists the outside authorities that settle the questions
here — what each one is authoritative for, and what you may do with it. Check them before
answering on anything they cover, and cite what you used. Most are free to read and not free
to reproduce; the use note on each is binding.
Territory, audience, the four-way format budget, cadence, platforms with rationale, first ten pieces with the job of each, and what you are choosing not to cover.
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概要と使いどころ
Designs and audits who can reach what — authentication, authorization models, privileged access, service credentials, and joiner-mover-leaver process. Use this to design a permissions model, run an access review, reduce standing privilege, handle offboarding, set up SSO or MFA, manage service and machine credentials, or diagnose why permissions have sprawled.
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Concentrates marketing and sales effort on a named set of accounts rather than on volume — qualifying whether the model fits your economics at all, building the account list and the buying group inside each, tiering effort against account value, coordinating so the account experiences one campaign rather than several, and measuring account progression instead of leads. Use this to decide whether to run an account-based program, build one, or work out why an existing one produces activity and no pipeline.
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。
Gets new users from signup to first real value — signup flow, onboarding, time-to-value, and the early experience that determines whether someone becomes a user or a lapsed account. Use this to design or fix signup and onboarding, diagnose why signups do not convert to active use, reduce time-to-value, or decide what a new user must accomplish first.
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。
Designs orchestrator-and-subagent hierarchies for a repository — splitting agents by exclusive write surface, pairing every producer with an independent auditor, and enforcing the split with a script that runs in CI. Use this whenever the user wants to set up, expand, audit, or fix a multi-agent or subagent structure for a codebase; asks how to divide work between agents; wants agent charters, roles, or a surface map written; or is hitting agents that collide on the same files, review their own work, or drift from their remit. Also use when sizing a roster or deciding whether a new agent is justified.
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Governs models and AI systems in production — intended use, evaluation, monitoring, human oversight, documentation, and the decision to deploy or retire. Use this before deploying a model or AI feature, when defining evaluation criteria, when a model's behavior has drifted, when assessing AI risk or regulatory exposure, or when deciding whether an AI system is fit for a consequential decision.
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Produces executive-level research — market sizing, competitor mapping, trend analysis, and strategic intelligence — grounded in cited sources with the confidence in each claim made explicit. Use this to analyze a market or industry, map competitors, evaluate a market-entry or build-versus-buy decision, produce a research brief, or assemble evidence for a decision. Also use when comparing options that need a structured, evidence-based verdict rather than an 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。