ai-vendor-assessment
Skill2 starsChanged 3 months agoApache-2.0View on GitHub
Assess an AI vendor, model provider, or supplier relationship. Use for EU AI Act role and evidence checks, GDPR processor terms, security and resilience review, model-change controls, incident routes, audit rights, contractual redlines, or a go/no-go procurement recommendation.
In this repository5 other files it gives its agents.
- ai-act-classificationSkill
- ai-act-complianceSkill
- dpia-aiSkill
- governance-documentationSkill
- risk-managementSkill
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 10
When the file is incomplete, produce a provisional evidence matrix and hold pending evidence recommendation rather than inventing terms or …
- Distinctive: line 12
Follow LEGAL-SOURCE-PROTOCOL.md.
- Distinctive: line 32
Treat marketing pages and undated trust-centre statements as lower-grade evidence than signed terms, current technical documentation, and …
- Distinctive: line 44
Do not state that regulatory fines are automatically indemnifiable or insurable.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Assess an AI vendor
Assess the actual service, intended use, contract, DPA, technical material, and operating model. Never substitute a static reputation profile for current evidence.
When the file is incomplete, produce a provisional evidence matrix and hold pending evidence recommendation rather than inventing terms or withholding all analysis.
Follow LEGAL-SOURCE-PROTOCOL.md. Use the Lexbeam EU AI Act MCP to validate classification, actor duties, deadlines, Article 6(3), and decisive articles.
Establish roles and use case
Record the contracting entity, service, version, deployment mode, geography, intended use, decision effect, data, model chain, and customer modifications. Determine provider, deployer, importer, distributor, product-manufacturer, downstream provider, and GPAI model-provider roles. Check Article 25 role changes before assigning duties.
Build an evidence matrix
For every claim record provided, missing, conflicting, or not applicable, plus document, page or URL, date, and owner.
Review:
- AI Act classification and instructions: intended purpose, prohibited-use controls, Annex I/III analysis, Article 6(3) documentation, Article 50 duties, provider instructions, and high-risk documentation where applicable.
- Model-chain accountability: base model, fine-tuning, downstream modifications, GPAI evidence, value-chain support under Article 25(4), and change notices.
- Data protection: controller/processor roles, instructions, subprocessors, transfers, deletion, return, training use, purpose limits, rights support, and breach route.
- Security and resilience: independent assurance, access control, logging, vulnerability handling, business continuity, recovery, and service levels.
- Monitoring and incidents: performance thresholds, drift and bias monitoring, complaint flow, serious-incident triage, evidence preservation, immediate deployer-to-provider route under Article 26(5), and provider reporting under Article 73.
- Audit and evidence access: current reports, targeted information rights, regulator cooperation, retention, export, termination assistance, and transition.
- Commercial allocation: warranties tied to supplied facts, indemnities, liability, insurance evidence, suspension rights, change control, termination, and precedence between terms.
Treat marketing pages and undated trust-centre statements as lower-grade evidence than signed terms, current technical documentation, and independent assurance.
Redline discipline
For each redline provide:
- issue and practical risk
- current clause or missing term
- proposed language or negotiation objective
- legal duty, contractual control, or recommended practice label
- fallback position and owner
Do not state that regulatory fines are automatically indemnifiable or insurable. Flag enforceability and local-law review.
Report
Return an executive recommendation (approve, approve with conditions, hold, or reject), scope and assumptions, role map, evidence matrix, redlines ranked critical/high/medium/low, pre-signing conditions, operating controls, open questions, and source note.
For workplace deployments, flag fact-specific worker information and national co-determination analysis. Do not treat DACH as a single works-council regime.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

