Runs performance systems that change behavior — expectations, feedback, review cycles, calibration, and handling underperformance. Use this to design or fix a review process, run calibration, write or coach on feedback, address sustained underperformance, or work out why reviews consume weeks and change nothing.
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Most review systems are an expensive annual ritual that surprises nobody and improves nothing. The work happens in the ordinary week; the cycle should record it, not discover it.
Performance documentation carries legal weight, particularly around termination, discrimination and accommodation. Employment law varies by jurisdiction — involve qualified counsel before acting on sustained underperformance.
Nobody can be fairly assessed against a standard they were not given. Expectations need to be specific to the level, written down, and shared before the period rather than produced during review as justification.
Separate two axes deliberately, because conflating them is the most common structural flaw:
Someone who delivered through a collapsing market and someone who delivered by scorching the earth around them are different cases. A single blended rating hides both.
Feedback is useful proportional to its proximity to the event. Specific, immediate, and about the work: what happened, what the effect was, what to do differently.
The annual cycle should contain nothing new. A review that surprises someone is a reporting failure by their manager, and the surprise is the finding.
Managers rate differently — some systematically generously, some harshly — and the differences are invisible until ratings sit side by side. Calibration exists to make comparison possible, not to fit a distribution.
Forced distributions are the failure mode here. On small teams they are statistically meaningless, and they reliably destroy exactly the collaboration the values section claims to reward.
Calibrate on evidence: what was delivered, at what level, against what expectation. A rating that cannot be defended with an example is a preference.
Address it early and directly. Late intervention is worse for everyone, most of all the person, who has been allowed to believe they were fine.
Establish which it is first, because the remedies do not overlap: unclear expectations, missing capability, a role mismatch, or something outside work. Treating a role mismatch as a capability problem produces a performance plan that fails for reasons nobody named.
Where a formal plan is warranted it needs specific outcomes, a real timeframe, defined support, and a stated consequence. A plan that is only a paper trail for a decision already taken is recognized as such and does damage well beyond the individual.
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.
Review and feedback: Lattice, Culture Amp, 15Five, Leapsome, Workday Talent, and similar.
Engagement measurement usually ships in the same platforms, which is convenient and creates a temptation worth resisting: engagement data and performance data should not be joined at the individual level, because people answer honestly only while that is true.
The tool cannot fix a process problem. If reviews are late, unspecific, or a surprise to the person receiving them, changing platforms will produce the same reviews on a nicer form.
まだレビューはありません。使ってみた感想をお寄せください。
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.
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。
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.
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。
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.
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。
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。