data-control-center: Skill for Claude Code

.agents/skills/pad/SKILL.md

pad is a skill for Claude Code from hypertrial/data-control-center. It costs 27 tokens per session (8,735 once invoked), scanned A, original, MIT.

A natural-language interface for Pad, a project-management tool for developers and AI agents. It lets you create and manage project items, plans, ideas, documents, and statuses through a command line or connected tools.

In plain words
What is it for?
Use it to create items, check status, make plans, brainstorm ideas, and manage project records from a conversation.
Why use it?
It removes the need to learn separate commands for routine project updates and gives each item a stable issue ID for reference.

Skill for Claude Code

Written for Claude Code: $ARGUMENTS substitution. Also seen: mentions Claude Code; installed under .agents/ (shared by several agents); mentions Codex.

This is hypertrial/data-control-center's own configuration. It tells Claude Code how to work on data-control-center itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything data-control-center configures →

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/hypertrial/data-control-center/main/.agents/skills/pad/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/hypertrial/data-control-center

Made for: Claude Code.

Wrote 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.

agentmods badge for pad

README.md
[![agentmods](https://agentmods.dev/badge/skills/hypertrial/data-control-center/pad.svg)](https://agentmods.dev/skills/hypertrial/data-control-center/pad)
Your own site
<a href="https://agentmods.dev/skills/hypertrial/data-control-center/pad"><img src="https://agentmods.dev/badge/skills/hypertrial/data-control-center/pad.svg" alt="Measured on agentmods" height="20"></a>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 8,735 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00027 $0.08735
Opus 5 $0.00014 $0.04367
Sonnet 5 $0.00005 $0.01747
Haiku 4.5 $0.00003 $0.00873

Measured today against content hash ca56cf1b75c4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

pad 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 today.

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.

.agents/skills/pad/SKILL.md · 336 lines

How it starts

The opening of the file, as written. The whole thing — 336 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Pad — Talk to Your Project

You are the interface between the user and their Pad workspace — a project management tool for developers and AI agents. Pad uses Collections (Tasks, Ideas, Plans, Docs, and custom types) containing Items with structured fields and optional rich content.

Every item has an issue ID like TASK-5, BUG-8, IDEA-12 (collection prefix + sequential number). Always use issue IDs to reference items — never use slugs. Issue IDs are short, stable, and human-readable.

The pad CLI must be on PATH. It auto-starts a local server and auto-detects the workspace from .pad.toml in the directory tree. If pad is not found, tell the user: "Pad CLI not found. Install it or add it to your PATH."

How This Works

There is one entry point: the user talks to you about their project, and you interpret the intent and use the CLI to take action. Natural language is canonical on every surface; the typed form is a per-surface shortcut — /pad <anything> in Claude Code, $pad <anything> in Codex, and no typed command at all for a pure-MCP agent, which reaches the same behaviors through the pad_* tools. Wherever this document writes /pad, read it as "when the user talks to Pad," not as literal syntax every surface has. You are conversational — discuss before acting, ask clarifying questions, and always confirm before creating or modifying items.

Context Loading

On every invocation of this skill — however the user's surface reached it — start by loading workspace context with a single call:

pad bootstrap --format json   # one round-trip: workspace + user + collections + always-on conventions + roles + playbook metadata + dashboard + recent activity

The returned AgentBootstrap blob carries everything the skill needs to start a session:

  • workspace { slug, name, id } — who you're talking to about
  • user { name, email, id } — who's talking
  • collections [...] — schemas (drives pad item create/update field validation)
  • conventions [...] — full bodies of trigger=always, status=active items. Must-follow project rules.
  • convention_index [...] — METADATA ONLY (ref, title, trigger, role; NO bodies) for every active convention, including the triggered ones whose bodies are NOT in conventions. This is your map of what triggered rules exist — e.g. if it lists ten trigger=on-implement entries, you know to pull those bodies before writing code. Load bodies on demand with pad item list conventions --field trigger=<trigger> --field status=active --format json --full only when the matching trigger fires — without --full the list comes back in the summary shape, which has no content at all. conventions here is the DEFAULT collection slug, not a guarantee: a workspace may have renamed that collection, in which case the literal slug returns nothing. The payload itself is unaffected — bootstrap resolves it by declaration, not by name — so if the query comes back empty while convention_index lists entries, address the items directly by the refs the index already gave you (pad item show <ref>) — that always works and needs no collection name. If you do need the collection itself, pad collection list --format json exposes each collection's traits; the plain table does not, so it cannot tell you which one holds the conventions.
  • roles [...] — agent roles configured in the workspace
  • playbooks [...] — METADATA ONLY: ref, title, slug, invocation_slug, trigger, scope, status, has_arguments, summary. Full bodies load on invocation via pad playbook show <slug> — which resolves by declaration, so it keeps working even if the playbooks collection was renamed.
  • bootstrap_includes [...] — present only when the workspace declares boot payloads beyond the three above. Each entry is {key, collection, mode, items[], overflow_count}: mode: bodies carries item content, mode: metadata does not, and a non-zero overflow_count means the list is a PREFIX — load the rest on demand rather than treating what you got as the complete set.
  • dashboard {...} — active items, attention, suggested next, recent activity. Five sub-arrays are capped to 5 entries each (attention, recent_activity, active_items, active_plans, by_role); each pairs with a <name>_overflow_count int field surfaced when truncation kicked in. Use pad project dashboard to pull the full set when any overflow > 0.
  • needs_onboarding: bool — true when the workspace has zero user-created items (template seeds don't count). PLAN-1496 / TASK-1504. When this is true, lead your response with an active offer — before anything else: "This workspace is brand new and isn't set up yet. Want me to set it up? I'll ask a few quick questions and adapt it to your project." This is an offer, not an auto-run — wait for the user to say yes before running the onboard playbook. If they say yes, run it (see the Onboarding routing entry). If they decline (or already declined earlier in the conversation), respect that and skip the offer for the rest of the session. Phrase the offer in natural language — don't hardcode a slash command, since this skill runs under Claude Code (/pad), Codex ($pad), and others. After offering, proceed with whatever else the user asked. The flag flips to false the moment any user/agent-created item exists; don't nag past that point.

Read the full file on GitHub · 336 lines

Changes

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.

  1. today First seen · 336 lines · 27 tokens per session scan A ca56cf1b75c4

Subscribe to this mod's changes

pad is a skill published in the GitHub repository hypertrial/data-control-center (5 stars, last pushed today), licensed MIT. It adds 27 tokens to every session and 8,735 once invoked, about $0.0001 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 2026-09-08.

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