Borrowing it
Nothing to install: this file belongs to Federico-Anastasi/DYLA-ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Federico-Anastasi/DYLA-ai/main/.agents/skills/data-model/SKILL.mdgit clone --depth 1 https://github.com/Federico-Anastasi/DYLA-aiWrote 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/federico-anastasi/dyla-ai/data-model)<a href="https://agentmods.dev/skills/federico-anastasi/dyla-ai/data-model"><img src="https://agentmods.dev/badge/skills/federico-anastasi/dyla-ai/data-model/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/federico-anastasi/dyla-ai/data-model"><img src="https://agentmods.dev/badge/skills/federico-anastasi/dyla-ai/data-model.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00036 | $0.02216 |
| Opus 5 | $0.00018 | $0.01108 |
| Sonnet 5 | $0.00007 | $0.00443 |
| Haiku 4.5 | $0.00004 | $0.00222 |
Grade A, and why
data-model 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 12d 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 — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/data-model — Data model
Reads the project brief and produces the validated data model.
UX: chat stays conversational. The deliverable is never presented as a markdown table
in chat — the user reads the table and the diagram in the viewer next to the chat, from
data_model.json. In chat you discuss it in words, citing elements by id (e.g. the
refund_request table). The user does not have to type ids: every element in the viewer
has a chat icon that sends you a ready-made [REFERENCE] — point them at that button
when it is unclear what they mean. When you cite a chapter of the brief, write
[[brief:Chapter title]]: it renders as a clickable reference that opens the document at
that point.
PROTOCOL
- Read context.md — where is the project? (Q&A already done? Data model already there?)
- Read the brief — find the brief file in the project folder
- If
data_model.jsonalready exists: ask "The data model already exists. Regenerate it from scratch, or edit it?" - If context.md has no Q&A: run the Q&A (BLOCKING — 5 to 7 questions, no more)
- Write data_model.json straight away with
meta.status: "draft" - Present a conversational summary (BLOCKING — wait for validation or edits)
- On confirmation: set
meta.status: "confirmed" - Update context.md
- Check consistency with the deliverables that already exist
Note: data_model.drawio and data_model.html are exports, generated on demand by
the backend from data_model.json (GET /api/projects/{project}/export/data_model.drawio
and .../data_model.html). This skill does not produce them.
PHASE 1 — READING
Read ALL of these before you go on:
- the brief:
projects/{project}/brief.json, or the input document (brief.md, or its extracted text under.extracted/if it is a PDF or a Word file) projects/{project}/meetings/*— if the project source isdiscovery: the real requirements are in the transcripts before they are in the briefprojects/{project}/docs/*— client documents (md, pdf, docx, xlsx, images; binaries have their text extracted under.extracted/)projects/{project}/context.mdprojects/{project}/data_model.json— if it existsprojects/{project}/estimate.json— if it existsknowledge/— if the folder exists: naming conventions, house patterns, client specifics. Nothing there is assumed: if a convention matters and the folder is silent about it, ask the user rather than inventing one
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.
- 12d ago First seen · 199 lines · 36 tokens per session scan A 175381e5730a
data-model is a skill published in the GitHub repository Federico-Anastasi/DYLA-ai (2 stars, last pushed 1mo ago), licensed MIT. It adds 36 tokens to every session and 2,216 once invoked, about $0.0002 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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