# Send AI Readiness Assessment to your agent
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
## Fast path
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
## Suggested prompts
### New install

```text
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
```
### Upgrade existing

```text
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
```
## Machine-readable fields
```json
{
  "schemaVersion": "1.0",
  "item": {
    "slug": "afrexai-ai-readiness",
    "name": "AI Readiness Assessment",
    "source": "tencent",
    "type": "skill",
    "category": "其他",
    "sourceUrl": "https://clawhub.ai/1kalin/afrexai-ai-readiness",
    "canonicalUrl": "https://clawhub.ai/1kalin/afrexai-ai-readiness",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadUrl": "/downloads/afrexai-ai-readiness",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=afrexai-ai-readiness",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "packageFormat": "ZIP package",
    "primaryDoc": "SKILL.md",
    "includedAssets": [
      "README.md",
      "SKILL.md"
    ],
    "downloadMode": "redirect",
    "sourceHealth": {
      "source": "tencent",
      "slug": "afrexai-ai-readiness",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-04-24T12:58:39.799Z",
      "expiresAt": "2026-05-01T12:58:39.799Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=afrexai-ai-readiness",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=afrexai-ai-readiness",
        "contentDisposition": "attachment; filename=\"afrexai-ai-readiness-1.0.0.zip\"",
        "redirectLocation": null,
        "bodySnippet": null,
        "slug": "afrexai-ai-readiness"
      },
      "scope": "item",
      "summary": "Item download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this item.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/afrexai-ai-readiness"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    }
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/afrexai-ai-readiness",
    "downloadUrl": "https://openagent3.xyz/downloads/afrexai-ai-readiness",
    "agentUrl": "https://openagent3.xyz/skills/afrexai-ai-readiness/agent",
    "manifestUrl": "https://openagent3.xyz/skills/afrexai-ai-readiness/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/afrexai-ai-readiness/agent.md"
  }
}
```
## Documentation

### AI Readiness Assessment

Run a structured AI readiness audit for any organization. Scores 8 dimensions, identifies gaps, produces a prioritized 90-day action plan with budget ranges.

### When to Use

Before investing in AI/automation tools
Board or leadership requesting AI strategy
Evaluating build vs buy decisions
Annual technology planning

### How It Works

Score each dimension 1-5 (1=not started, 5=optimized):

### 1. Data Infrastructure (Weight: 3x)

Centralized data warehouse or lakehouse operational
 Data quality monitoring automated (freshness, completeness, accuracy)
 API-first architecture for core systems
 Data governance policy documented and enforced
 PII/PHI classification and access controls active

Score 1: Spreadsheets and siloed databases
Score 3: Warehouse exists, some pipelines automated
Score 5: Real-time streaming, quality >99%, full lineage

### 2. Process Documentation (Weight: 2x)

Top 20 revenue-impacting processes mapped end-to-end
 Decision trees documented for each process
 Exception handling paths defined
 Time-per-task benchmarks established
 Process owners assigned

Score 1: Tribal knowledge, nothing written down
Score 3: Major processes documented, some outdated
Score 5: Living documentation, updated quarterly, covers 80%+ of operations

### 3. Technical Talent (Weight: 2x)

At least 1 person understands ML/AI concepts at implementation level
 Engineering team comfortable with APIs and integrations
 DevOps/infrastructure person can deploy and monitor services
 Data analyst can query and interpret model outputs
 Security team understands AI-specific attack surfaces

Score 1: No technical staff beyond basic IT
Score 3: Good engineering team, AI knowledge is theoretical
Score 5: Dedicated AI/ML engineer, cross-functional AI literacy program

### 4. Budget & ROI Framework (Weight: 2x)

AI budget allocated (not pulled from "innovation" slush fund)
 ROI measurement criteria defined before project starts
 Kill criteria established (when to stop a failing project)
 Total cost of ownership model includes maintenance, retraining, monitoring
 Benchmarks set against current manual process costs

Budget Reality by Company Size:

Company SizeYear 1 InvestmentExpected ROI Timeline15-50 employees$24K-$80K4-8 months50-200 employees$80K-$300K3-6 months200-1000 employees$300K-$1.2M6-12 months1000+ employees$1.2M-$5M+8-18 months

### 5. Change Management (Weight: 1.5x)

Executive sponsor identified and actively involved
 Communication plan for affected teams drafted
 Training budget allocated
 Pilot team identified (volunteers, not voluntolds)
 Success metrics shared openly with organization

Score 1: Leadership says "just do AI" with no plan
Score 3: Exec sponsor exists, some team buy-in
Score 5: Change management playbook active, regular town halls, feedback loops

### 6. Security & Compliance (Weight: 2.5x)

AI-specific data handling policy written
 Vendor security assessment process includes AI criteria
 Model output logging and audit trail planned
 Regulatory requirements mapped (GDPR, HIPAA, SOX, SOC 2, EU AI Act)
 Incident response plan covers AI failures

Score 1: No AI-specific security considerations
Score 3: General security strong, AI gaps identified
Score 5: AI governance framework active, regular audits, compliance automated

### 7. Integration Readiness (Weight: 1.5x)

Core systems have APIs (CRM, ERP, HRIS, etc.)
 Authentication/authorization supports service accounts
 Webhook or event-driven architecture available
 Test/staging environment mirrors production
 Rollback procedures documented

Score 1: Legacy systems, no APIs, manual data entry
Score 3: Major systems have APIs, some manual bridges
Score 5: API-first architecture, event-driven, CI/CD for integrations

### 8. Strategic Alignment (Weight: 1x)

AI initiatives map to specific business objectives (not "innovation")
 3-year technology roadmap includes AI milestones
 Competitive landscape analysis includes AI adoption by rivals
 Board/leadership educated on AI capabilities and limitations
 Failure tolerance defined (acceptable experiment failure rate)

Score 1: AI is a buzzword, no concrete strategy
Score 3: Strategy exists, loosely connected to business goals
Score 5: AI embedded in strategic plan, quarterly reviews, competitive moat building

### Scoring

Weighted Total = Sum of (Score × Weight) / Max Possible × 100

RangeRatingRecommendation0-25🔴 Not ReadyFix foundations first. 6-12 months of groundwork before AI projects.26-50🟡 Early StagePick ONE high-impact, low-risk pilot. Build muscle.51-75🟢 ReadyDeploy 2-3 agents in validated use cases. Scale what works.76-100🔵 AdvancedMulti-agent deployment, autonomous operations, competitive moat.

### 90-Day Action Plan Template

Days 1-30: Foundation

Complete this assessment with honest scores
Document top 5 processes by time spent × error rate
Audit data infrastructure gaps
Set budget and kill criteria

Days 31-60: Pilot

Select highest-scoring use case (high data readiness + clear ROI)
Deploy single agent or automation
Measure daily: time saved, error rate, cost
Weekly review with stakeholders

Days 61-90: Scale or Kill

If pilot ROI > 2x: plan 2 more deployments
If pilot ROI < 1x: diagnose root cause, pivot or kill
Document learnings regardless of outcome
Update 3-year roadmap based on reality

### 7 Assessment Mistakes

Scoring yourself too high — External validation beats internal optimism
Ignoring data quality — AI on bad data = faster wrong answers
Skipping change management — Technical success + team rejection = failure
No kill criteria — Zombie projects drain budget and credibility
Buying before understanding — Tool purchases before process documentation = shelfware
Ignoring security until audit — Retrofitting AI security costs 3-5x more than building it in
Comparing to tech companies — Your readiness bar is YOUR industry, not Silicon Valley

### Industry Benchmarks (2026)

IndustryAvg ScoreTop QuartileFirst AI WinFintech6278+Fraud detection, KYCHealthcare4158+Clinical documentation, schedulingLegal3852+Contract review, researchConstruction2944+Safety monitoring, estimationEcommerce5874+Personalization, inventorySaaS6582+Support, onboarding, churn predictionReal Estate3548+Lead scoring, valuationRecruitment4562+Screening, outreachManufacturing4256+QC, predictive maintenanceProfessional Services4864+Proposal generation, time tracking

Get your industry-specific context pack ($47) → https://afrexai-cto.github.io/context-packs/

Calculate your AI revenue leak → https://afrexai-cto.github.io/ai-revenue-calculator/

Set up your first AI agent → https://afrexai-cto.github.io/agent-setup/

Bundles: Pick 3 for $97 | All 10 for $197 | Everything Pack $247
## Trust
- Source: tencent
- Verification: Indexed source record
- Publisher: 1kalin
- Version: 1.0.0
## Source health
- Status: healthy
- Item download looks usable.
- Yavira can redirect you to the upstream package for this item.
- Health scope: item
- Reason: direct_download_ok
- Checked at: 2026-04-24T12:58:39.799Z
- Expires at: 2026-05-01T12:58:39.799Z
- Recommended action: Download for OpenClaw
## Links
- [Detail page](https://openagent3.xyz/skills/afrexai-ai-readiness)
- [Send to Agent page](https://openagent3.xyz/skills/afrexai-ai-readiness/agent)
- [JSON manifest](https://openagent3.xyz/skills/afrexai-ai-readiness/agent.json)
- [Markdown brief](https://openagent3.xyz/skills/afrexai-ai-readiness/agent.md)
- [Download page](https://openagent3.xyz/downloads/afrexai-ai-readiness)