Aipom platform dependency audit
Skill deanpeters/ai-product-operating-model-skills/skills/aipom-platform-dependency-audit
Assess model, vendor, data, infrastructure, integration, talent, switching, and portability dependencies that can change an AI investment decision.From its SKILL.md
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SKILL.md
4.7 KB, 735 tokens by cl100k_base, as published. Nobody here has run it
AIPOM Platform Dependency Audit
What Is It
Map and test the external and internal dependencies that shape value, reliability, control, and exit: models, vendors, data, infrastructure, integrations, talent, contracts, pricing, evaluation, and operational knowledge.
Why Use It
A technically successful pilot can become economically or operationally fragile when one provider changes price, behavior, access, terms, region, or service. Dependency is not automatically bad; unmanaged dependency is the problem.
When to Use It
Use before material procurement, scale, renewal, architecture lock-in, sensitive-data transfer, or increased autonomy. Scope the audit to the decision rather than producing a generic vendor inventory.
What It Produces
- Dependency, ownership, and concentration map
- Change, outage, degradation, and exit scenarios
- Portability evidence and switching cost
- Accept, mitigate, diversify, constrain, renegotiate, or exit recommendation
Who Should Participate
Include the investment owner, architecture and engineering, product, procurement, finance, security, data, operations, and governance partners.
Evidence to Bring
Bring architecture, data flows, contracts, service terms, pricing, usage, evaluations, incidents, operational runbooks, portability tests, skills, and migration estimates. Contract language without tested operations is partial evidence.
How to Do It
- Name the investment decision and critical capabilities.
- Map upstream, runtime, downstream, organizational, and contractual dependencies.
- Record owner, substitutability, concentration, data movement, and failure consequence.
- Test price, model change, outage, quality regression, access loss, policy change, and provider-exit scenarios.
- Examine portability of prompts, context, data, evaluations, integrations, logs, and operating knowledge.
- Estimate switching time, cost, downtime, retraining, revalidation, and control changes.
- Identify dependencies that constrain scale, autonomy, geography, or data use.
- Recommend accept, mitigate, diversify, constrain, renegotiate, or exit actions.
- Assign owners, evidence tests, monitoring, and decision triggers.
Key Concepts
- Portability is demonstrated through tests, not architecture diagrams.
- Multi-vendor designs can add complexity without reducing critical concentration.
- Organizational expertise is a dependency.
- Dependency exposure belongs in economics and stage gates.
Organizational Applications
Use for foundation-model providers, cloud and vector infrastructure, data vendors, orchestration platforms, evaluation services, and internal shared platforms.
Common Pitfalls
- Treating vendor availability as portability
- Mapping technology but not contracts or skills
- Ignoring model behavior changes
- Assuming multi-cloud eliminates concentration
- Omitting re-evaluation and migration cost
- Creating mitigations with no trigger or owner
Combine With
Use aipom-economic-case-builder to price exposure, aipom-investment-stage-gates to constrain funding, and aipom-initiative-readiness-review to integrate critical gaps.
Assets and Templates
Sources
- NIST AI Resource Center, AI RMF Core. Manage 3 addresses monitoring third-party AI resources and applying documented controls. Accessed July 17, 2026. NIST notes that AI RMF 1.0 is under revision.
What ships with it: 3 files
1.4 KB alongside SKILL.md
examples/
- weak-example.md252 B
- worked-example.md536 B
- template.md663 B
Gives 0 of the 12 instructions most dependency audit skills give in 735 tokens
Counted across 162 of the 192 authors here whose files we hold, read 2026-09-06
- Verify the gh tool is installed before startingin 10 of 162, across 6 files
- Find git repositories for all direct dependenciesin 9 of 162, across 5 files
- Evaluate every dependency against the risk criteriain 9 of 162, across 5 files
- Normalize repository names to full URLsin 9 of 162, across 5 files
- Query exact star and issue counts using ghin 9 of 162, across 5 files
- Ask the user to install gh if missingin 7 of 162, across 3 files
- Omit low-risk dependencies from the reportin 7 of 162, across 3 files
- Run the full test suite after each changein 7 of 162
- Flag dependencies matching any risk criterion with clear reasonsin 6 of 162, across 2 files
- Commit lockfiles and pin exact dependency versionsin 6 of 162, across 5 files
- Detect package managers from manifest filesin 6 of 162
- Review the changelogs for breaking changesin 5 of 162, across 2 files
Said here and by no other author read
- Name the investment decision and critical capabilities
- Map upstream, runtime, downstream, organizational, contractual dependencies
- Record owner, substitutability, concentration, data movement, failure consequence
- Test price, outage, quality, access, policy, provider-exit scenarios
- Examine portability of prompts, data, evaluations, integrations, logs
- Estimate switching time, cost, downtime, retraining, revalidation
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.