Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add rules/contentstack/contentstack-agent-skills/04-cms-data-modeling-best-practicesgit clone --depth 1 https://github.com/contentstack/contentstack-agent-skillsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00060 | $0.01267 |
| Opus 5 | $0.00030 | $0.00633 |
| Sonnet 5 | $0.00012 | $0.00253 |
| Haiku 4.5 | $0.00006 | $0.00127 |
Grade A, and why
04-cms-data-modeling-best-practices scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Contentstack Data Modeling Best Practices
Description
Guide developers to model content in Contentstack using the simplest reusable structure. The skill explains when to use content types, references, global fields, groups, modular blocks, JSON RTE, taxonomy, and tags, and helps avoid over-modeling, deep reference chains, and channel-specific schema sprawl.
When to Use
Use when designing, reviewing, or refactoring Contentstack content models before creating or changing schemas.
User Problem
Developers need a practical way to choose the right Contentstack construct so editors can work efficiently, delivery code stays simple, and schemas stay reusable, governed, and easy to query.
Success Criteria
Recommend the simplest valid model, explain tradeoffs clearly, preserve editorial usability, avoid unnecessary abstraction, and keep the schema stable, shallow, and aligned with localization and governance needs.
Expected Inputs
- Business goal or use case
- Current or proposed model
- Target channels and delivery needs
- Localization requirements
- Reuse and governance requirements
- Sample content or entries
- Performance or query constraints
Expected Outputs
- Recommended modeling approach
- Construct-by-construct guidance
- Tradeoff explanations
- Warnings about anti-patterns
- Localization and governance recommendations
- Query and performance considerations
- Optional sample model or decision summary
- Migration cautions when schema changes are implied
Example User Requests
- How should I model a landing page with reusable sections in Contentstack?
- Should this data be a global field, group, or content type?
- Review this content model and tell me what to simplify.
- What is the best way to handle localization for shared content?
- How do I model product categories for filtering and reuse?
Workflow Summary
- Identify the domain concept, editorial workflow, delivery channels, localization needs, reuse requirements, and query constraints.
- Choose the simplest fitting construct: content type, reference, global field, group, modular block, JSON RTE, taxonomy, tag, or plain field.
- Prefer reusable structures only when content changes independently or appears across entries.
- Check reference depth, API contract stability, and query impact.
- Review localization and naming conventions.
- Call out anti-patterns and suggest simpler alternatives.
- Return a concise recommendation with migration cautions if needed.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 139 lines · 60 tokens per session scan A 898324f8b2bf
04-cms-data-modeling-best-practices is a cursor rule published in the GitHub repository contentstack/contentstack-agent-skills (5 stars, last pushed 15d ago), licensed MIT. It adds 60 tokens to every session and 1,267 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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