ai-wrapper-product
Build Reliable AI API Products
Generic AI wrappers often lack clear value, reliable outputs, and cost controls. This skill guides focused product design, implementation patterns, and operational safeguards.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "ai-wrapper-product" from https://skillstore.io/skills/sickn33-ai-wrapper-product.md and its manifest at https://skillstore.io/api/skills/sickn33-ai-wrapper-product/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "ai-wrapper-product". Plan an AI assistant for independent property managers who answer tenant maintenance requests.
Expected outcome:
- Focus: classify requests, draft replies, and route urgent cases.
- Quality controls: require property context, validate urgency, and preserve human approval.
- Operations: use a fast model, track tokens per property, and queue burst traffic.
Using "ai-wrapper-product". Reduce costs for a summarization feature processing 50,000 documents monthly.
Expected outcome:
- Route standard documents to a lower-cost model and reserve stronger models for failed validation.
- Limit input size, cache repeated documents, and record token costs for each account.
- Set monthly account limits, anomaly alerts, and a provider spending ceiling.
Using "ai-wrapper-product". Review a generic chat interface that forwards every message directly to an AI provider.
Expected outcome:
The product is a thin wrapper. Add a specific workflow, domain context, validated outputs, usage controls, and an integration users already need.
Security Audit
SafeAll 56 static findings are false positives caused by Markdown fences, JavaScript template literals, illustrative error handling, ordinary prose, and a relative application API request. The skill is a documentation-only guide with no executable scripts, external command invocation, reconnaissance behavior, prompt injection attempt, or sensitive-data transfer.
Risk Factors
⚙️ External commands (47)
🌐 Network access (2)
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APA citation
sickn33. (2026). ai-wrapper-product security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-ai-wrapper-product/audits/5BibTeX citation
@techreport{sickn33-sickn33-ai-wrapper-product-2026,
author = {sickn33},
title = {ai-wrapper-product security audit report (audit version 5)},
institution = {Skillstore},
year = {2026},
number = {5},
url = {https://skillstore.io/skills/sickn33-ai-wrapper-product/audits/5},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "ai-wrapper-product security audit report (audit version 5)"
version: "unspecified"
type: report
authors:
- name: "sickn33"
date-released: "2026-07-23"
url: "https://skillstore.io/skills/sickn33-ai-wrapper-product/audits/5"
identifiers:
- type: other
value: "skillstore:sickn33-ai-wrapper-product:audit:5"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Define a Focused AI Product
Turn a specific customer problem into an AI-assisted workflow with clear value, model needs, and quality controls.
Plan a Production Integration
Structure prompts, provider calls, parsing, retries, streaming, caching, and usage metering for an existing application.
Control AI Operating Costs
Establish token budgets, plan limits, anomaly monitoring, and provider safeguards before launching an AI feature.
Try These Prompts
Define an AI product for [target user] that solves [problem]. Recommend the core workflow, model needs, validation rules, and success metrics.
Design the prompt architecture for [feature]. Include input validation, system instructions, user context, output format, parsing, and failure handling.
Review this usage forecast: [forecast]. Propose model routing, token limits, rate-limit handling, caching, monitoring, and an emergency spending cutoff.
Audit this AI product specification: [specification]. Identify thin-wrapper risks, quality gaps, cost exposure, latency issues, and defensible product improvements.
Best Practices
- Validate user input and AI output before using or displaying generated content.
- Track tokens, costs, failures, and latency for every provider request.
- Use the least expensive model that consistently meets measured quality requirements.
Avoid
- Do not expose provider API keys in browsers or client applications.
- Do not forward unbounded input directly to a model without limits or validation.
- Do not treat generated facts as reliable without domain-specific checks and user review.
Frequently Asked Questions
What products does this skill support?
Does it generate a complete application?
Can it help choose an AI model?
How does it address API costs?
How does it improve reliability?
Does it prevent inaccurate AI output?
Developer Details
Author
sickn33License
MIT
Skillstore revision
r2
Version notice
The author did not declare a version.
Repository
https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/ai-wrapper-productRef
ebdfe608f5de2b66ff37ab4af12af8ac4f5e8006
Maintenance freshness
7/26/2026
Usage
6 downloads · 100 views
File structure
📄 SKILL.md