本文へ移動
cccskills
無料GitHub で公開

vendor-management

Selects, contracts, and manages suppliers and vendors — requirements, evaluation, negotiation support, onboarding, performance management, and exit. Use this to choose a vendor, run a selection process, structure a service agreement's operational terms, manage an underperforming supplier, plan an exit or migration, or assess concentration and continuity risk.

インストール方法を見る

含まれるファイル(2)

  • SKILL.md3.5 KB
  • references/sources.md1.8 KB

SKILL.md(原文)

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。

Vendor management

Define requirements before looking at options

Written before any demo: what the vendor must do, the volume and service level required, what must integrate with what, and the constraints that are genuinely non-negotiable.

Requirements written after seeing a product describe that product. This is the most common way selections are decided before they are run.

Separate must-have from nice-to-have and weight them in advance. Weighting after scoring is how a preferred vendor wins a process designed to be objective.

Evaluating

  • Reference checks with customers of your size and use case. A reference running a tenth of your volume tells you nothing about whether it scales.
  • Test the actual failure modes, not the demo path. What happens when data is malformed, volume spikes, or an integration times out?
  • Assess the vendor, not just the product — financial stability, roadmap direction, support responsiveness, and whether you are a meaningful customer to them. Being a rounding error to your critical supplier is a risk in itself.
  • Total cost including your side: implementation, integration, migration, training, and the ongoing effort to operate it. License cost is frequently the smaller half.

Terms that matter operationally

Beyond the legal review: service levels with real remedies, support response times by severity, data export in a usable format on demand, notice periods that give you time to migrate, and price protection at renewal. The absence of the last two is what makes exit expensive later.

Managing

  • One named owner on your side. Vendors without an internal owner drift and renew automatically.
  • Review on a schedule against the service levels, with evidence. Vendor-supplied performance reports mark their own work.
  • Log issues. At renewal, a documented pattern is leverage; a recollection is not.
  • Diarize renewals well before the notice deadline. Auto-renewal past an unnoticed deadline is the most common and most avoidable vendor loss.

Concentration and exit

Know which vendors you could not operate without and what happens if one fails, is acquired, or triples its price. For each, know the exit path and roughly what it costs — an exit plan that has never been thought through is not an option, it is a hope.

Maintain your own copy of your data continuously where the vendor holds anything critical.

Sources

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.

Never

  • Sign before you know what leaving costs — data export, notice period, transition support.
  • Let the vendor write the requirements you evaluate them against.
  • Reach a renewal date without having started the renewal. The auto-renew clause is their leverage.
  • Concentrate a critical dependency on one vendor without saying so out loud and pricing the risk.

レビュー

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。

同じリポジトリのスキル

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。

cbrock84/headcount2,0332026年9月18日 更新

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。

cbrock84/headcount2,0332026年9月18日 更新

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。

cbrock84/headcount2,0332026年9月18日 更新

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。

cbrock84/headcount2,0332026年9月18日 更新

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。

cbrock84/headcount2,0332026年9月18日 更新

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。

cbrock84/headcount2,0332026年9月18日 更新

cbrock84 のスキルをすべて見る

このスキルの問題を報告する