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 skills add HoangNguyen0403/agent-skills-standard --skill system-design-data-architecturegit clone --depth 1 https://github.com/HoangNguyen0403/agent-skills-standardWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/hoangnguyen0403/agent-skills-standard/system-design-data-architecture)<a href="https://agentmods.dev/skills/hoangnguyen0403/agent-skills-standard/system-design-data-architecture"><img src="https://agentmods.dev/badge/skills/hoangnguyen0403/agent-skills-standard/system-design-data-architecture/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hoangnguyen0403/agent-skills-standard/system-design-data-architecture"><img src="https://agentmods.dev/badge/skills/hoangnguyen0403/agent-skills-standard/system-design-data-architecture.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What 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 5.1 | $0.00059 | $0.00779 |
| Opus 5 | $0.00030 | $0.00390 |
| Sonnet 5 | $0.00012 | $0.00156 |
| Haiku 4.5 | $0.00006 | $0.00078 |
Grade A, and why
system-design-data-architecture 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 13d 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Architecture
Priority: P1 (HIGH)
Access patterns choose the store. Ownership precedes schema. Shard last, not first.
Store Selection
- List every read and write access pattern with its QPS, latency target, and consistency need.
- Default to a relational store. It wins until a specific pattern proves it cannot serve.
- Move a pattern to a specialized store only when the relational store fails that named pattern: key-value for hot lookups, wide-column for massive ordered writes, document for schema-variant aggregates, graph for multi-hop traversal, search index for text and facets, object store for blobs.
- Every additional store adds sync lag, dual-write risk, and one more operational surface. Justify it.
- Blobs never live in the primary database; store bytes in object storage and keep the reference.
Ownership and Consistency
- One writer owns each entity. Cross-service reads use an API or an event stream, never a shared table.
- Classify each flow before choosing replication: money, stock, and identity need strong consistency; feeds, counters, and analytics tolerate eventual.
- Read replicas serve reads only, and replica lag is visible to users. Route read-after-write to the primary or pin the session.
- Cross-entity atomicity across services needs a saga with compensations, not a distributed transaction.
Scaling Order
Apply in order and stop as soon as headroom is sufficient: index and query fixes, then read replicas, then caching, then vertical scale, then partition or archive cold data, then shard. Sharding is last because it costs cross-shard queries, rebalancing, and a permanent partition key commitment.
Partitioning
- Choose a partition key that is high-cardinality, present in the hottest query, and evenly distributed.
- Hash partitioning spreads load but kills range scans; range partitioning keeps scans but creates a moving hot partition on time-ordered keys.
- Mitigate a celebrity key by salting the key, replicating the record, or serving it from a dedicated cache.
- Plan resharding before launch: virtual buckets mapped to physical shards let you move buckets without rewriting keys.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 13d ago First seen · 73 lines · 59 tokens per session scan A fd5551c23036
system-design-data-architecture is a skill published in the GitHub repository HoangNguyen0403/agent-skills-standard (565 stars, last pushed 3d ago), licensed MIT. It adds 59 tokens to every session and 779 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 2026-08-30.
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