Borrowing it
Nothing to install: this file belongs to hypertrial/data-control-center. 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/hypertrial/data-control-center/main/.agents/skills/pad-engineering/SKILL.mdgit clone --depth 1 https://github.com/hypertrial/data-control-centerWrote 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/hypertrial/data-control-center/pad-engineering)<a href="https://agentmods.dev/skills/hypertrial/data-control-center/pad-engineering"><img src="https://agentmods.dev/badge/skills/hypertrial/data-control-center/pad-engineering/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/hypertrial/data-control-center/pad-engineering"><img src="https://agentmods.dev/badge/skills/hypertrial/data-control-center/pad-engineering.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 | $0.00032 | $0.00821 |
| Opus 5.5 | $0.00013 | $0.00328 |
| Sonnet 5.5 | $0.00006 | $0.00164 |
| Haiku 4.5 | $0.00003 | $0.00082 |
Grade A, and why
pad-engineering 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 1mo 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pad Engineering
Use this skill for non-trivial local agentic engineering. Keep Pad's official pad skill for CLI/MCP mechanics. This skill overrides routing that would create Ideas or Tasks.
Git owns code. CI owns verification. Pad owns intent, scope, status, dependencies, decisions, evidence, and handoffs.
Collections
Use only:
work— Feature, Bug, Refactor, Investigation, Maintenanceplans— multi-ticket containers only
Never create Ideas, Tasks, Docs-as-tickets, chores, or extra default types unless the user is explicitly asking for a document. Do not run onboard.
Machine status values: backlog, ready, in-progress, blocked, review, done.
Risk: r0, r1, r2, r3.
Always pass --workspace <slug> from .pad.toml. Always reference items by issue ID.
Ticket body
New Work items MUST start from the canonical Work template. Plans use the Plan template. Required sections must be filled before ready. Dependencies are Pad blocked-by / blocks links, not a prose status field.
Before changing status, validate the status the ticket is about to enter:
PAD_UNIVERSAL_ROOT="${PAD_REPOS_ROOT:-/Volumes/Mac SSD}/pad-universal"
(cd "$PAD_UNIVERSAL_ROOT" && python3 -m pad_universal lint \
--ref WORK-1 --workspace <slug> --target-status <status>)
At task start, lint an existing ready or in-progress ticket once without
--target-status before material implementation. Do not repeat the lint before
each code edit. A ticket that fails the linter is not ready or done.
If linting fails to start, check
$PAD_UNIVERSAL_ROOT/pad_universal/__main__.py before claiming the checkout is
absent. No module named pad_universal means the canonical command was not used;
retry it. A loopback permission error means Pad server access must be allowed and
retried. Do not clone or search for another checkout unless the canonical path is
genuinely absent. Tooling failure blocks managed agent transitions, but direct
human Pad updates remain available for recovery.
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.
- 1mo ago Changed · +15 lines 3cb518511666
- 1mo ago First seen · 67 lines · 32 tokens per session scan A 07b6a8d22558
pad-engineering is a skill published in the GitHub repository hypertrial/data-control-center (4 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 821 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-08.
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