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 instructions/hypertrial/data-control-center/agents-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/instructions/hypertrial/data-control-center/agents-md)<a href="https://agentmods.dev/instructions/hypertrial/data-control-center/agents-md"><img src="https://agentmods.dev/badge/instructions/hypertrial/data-control-center/agents-md.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 | $0.00864 | $0.00864 |
| Opus 5 | $0.00432 | $0.00432 |
| Sonnet 5 | $0.00173 | $0.00173 |
| Haiku 4.5 | $0.00086 | $0.00086 |
Grade A, and why
data-control-center AGENTS.md 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Project Overview
Data Control Center is a local-only workstation app for uploading, profiling, exploring, and querying local datasets.
- Frontend:
frontend/uses React, Vite, TypeScript, TanStack Query/Table, Zustand, ECharts, Tailwind, and shadcn-style primitives. - Backend:
backend/uses FastAPI, DuckDB, Polars, Pydantic, anduv. - Keep the product local-only. Do not introduce hosted, multi-user, shared-LAN, tenancy, or account-auth assumptions without an explicit user request.
Setup and validation
Run commands from the repository root unless noted. Canonical commands and CI parity:
CONTRIBUTING.md (setup, Makefile targets, validation, coverage).
Quick reference:
make install/make dev— dependencies and local dev serversmake check— full validation before finishing workmake check-ci— after frontend lockfile changescd backend && uv sync --extra dev— after backenduv.lock/ pyproject changes, thenmake checkmake clean-local— discard local workspace and uploads
Use Node 22 from .nvmrc (matches CI). Use Python 3.11+ with uv.
If a required tool is missing or a network-dependent audit cannot run, state the exact blocker and any fallback checks performed.
Code Style
- Follow existing module boundaries and naming before adding new abstractions.
- Backend API routes live in
backend/app/api/; Pydantic models inbackend/app/models/; service logic inbackend/app/services/. - Frontend API client/types live in
frontend/src/api/; feature UI lives infrontend/src/features/; reusable primitives live infrontend/src/components/. - Add or update tests with behavior changes. Backend coverage is expected to remain at 100%; frontend coverage must satisfy the configured Vitest baseline.
- Keep generated artifacts, coverage output, local databases, uploads, caches, and private datasets out of commits.
- Prefer small, focused changes over broad refactors. Do not rewrite unrelated code while fixing a local issue.
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 · 84 lines · 864 tokens per session scan A 2a822908e64b
data-control-center AGENTS.md is an instructions file published in the GitHub repository hypertrial/data-control-center (5 stars, last pushed 1mo ago), licensed MIT. It adds 864 tokens to every session, about $0.0043 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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