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 skills/d4rkninja/arcforge/data-storagenpx skills add d4rkNinja/arcforge --skill data-storagegit clone --depth 1 https://github.com/d4rkNinja/arcforgeWrote 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/d4rkninja/arcforge/data-storage)<a href="https://agentmods.dev/skills/d4rkninja/arcforge/data-storage"><img src="https://agentmods.dev/badge/skills/d4rkninja/arcforge/data-storage.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00075 | $0.02558 |
| Opus 5 | $0.00037 | $0.01279 |
| Sonnet 5 | $0.00015 | $0.00512 |
| Haiku 4.5 | $0.00007 | $0.00256 |
Grade A, and why
data-storage 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 3d 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 — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Think Through Data & Storage
Overview
Production guidance for data modeling and storage. Each reference paper captures the correctness work that schema-first drafts miss: precision hazards, constraint-race conditions, index design from real predicates, soft-delete interactions with uniqueness, file-handling abuse, derived-store rebuilds, and retention obligations.
Core principle: Data outlives code. Every column, identifier, file, and derived index is a durable decision with invariants, an owner, and a lifecycle — not a convenient shape for today's feature.
Domain Law
NO DATA OR STORAGE CHANGE WITHOUT:
1. the minimum required primary paper(s) for the data being modeled selected from the context table;
2. the paper's pre-change questions
answered, or each open point labeled as an assumption;
3. "Existing-codebase checks" run when changing an existing schema or store;
4. every applicable MUST mapped to a decision (constraint, index, policy),
a test, or a documented exception — never silently downgraded.
When to Use
Use this skill when thinking through, reviewing, changing, or verifying:
- tables, documents, relationships, denormalization, and metadata modeling;
- identifier generation, exposure, and migration (auto-increment, UUIDv4/v7, ULID, snowflake);
- timestamps, timezones, DST, scheduling, and clock-skew handling;
- money and numeric precision, rounding modes, and serialization fidelity;
- primary/foreign/unique/check constraints and constraint race conditions;
- indexes (composite, partial, covering) and query plans, N+1 elimination;
- soft delete, restore, purging, and unique-constraint interaction;
- retention, archival, expiration, anonymization, and legal hold;
- immutable/append-only records, correction records, and tamper evidence;
- file upload/download, MIME and signature validation, signed URLs, orphan cleanup;
- image/video processing pipelines and original preservation;
- full-text/vector search and index synchronization;
- record versioning, provenance, source-of-truth boundaries, reconciliation, and cleanup jobs.
What ships with it
21 files 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.
- agents/openai.yaml 273 B
- examples/worked-example-product-pricing-schema.md 4.2 KB
- references/papers/018-identifiers.md 31 KB
- references/papers/019-time-and-date-handling.md 31 KB
- references/papers/020-money-numeric-precision.md 43 KB
- references/papers/021-database-modeling.md 31 KB
- references/papers/022-database-constraints.md 36 KB
- references/papers/026-data-integrity.md 32 KB
- references/papers/027-indexing.md 38 KB
- references/papers/028-query-design.md 33 KB
- references/papers/032-soft-delete-hard-delete.md 35 KB
- references/papers/033-data-lifecycle.md 32 KB
- references/papers/034-immutable-data.md 34 KB
- references/papers/040-file-handling.md 38 KB
- references/papers/041-media-processing.md 35 KB
- references/papers/042-search.md 34 KB
- references/papers/069-data-versioning.md 32 KB
- references/papers/122-data-provenance.md 31 KB
- references/papers/123-source-of-truth.md 32 KB
- references/papers/124-data-reconciliation.md 30 KB
- references/papers/125-cleanup-jobs.md 31 KB
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.
- 3d ago First seen · 158 lines · 75 tokens per session scan A 3c71bd334ef7
data-storage is a skill published in the GitHub repository d4rkNinja/arcforge (16 stars, last pushed 7d ago), licensed MIT. It adds 75 tokens to every session and 2,558 once invoked, about $0.0004 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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