qwery-core AGENTS.md

qwery-core AGENTS.md is an instructions file for Codex, OpenCode from Guepard-Corp/qwery-core. It costs 1,904 tokens per session, scanned A, original, MIT.

Contributor rules for qwery-agent, an AI data-analysis application with a text-based interface. They define privacy, tool-use, and architectural boundaries, including keeping row-level database data away from the language model.

In plain words
What is it for?
Adding analysis tools, querying data with aggregate results, rendering results locally, and organising code across domain, application, adapter, and extension areas.
Why use it?
They prevent sensitive records from leaving the local application and stop changes from breaking the project’s approved architecture.

Instructions file for CodexOpenCode

Install

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.

agentmods
npx agentmods add instructions/guepard-corp/qwery-core/agents-md
Clone the repo
git clone --depth 1 https://github.com/Guepard-Corp/qwery-core

Made for: Codex, OpenCode.

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 qwery-core AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/guepard-corp/qwery-core/agents-md.svg)](https://agentmods.dev/instructions/guepard-corp/qwery-core/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/guepard-corp/qwery-core/agents-md"><img src="https://agentmods.dev/badge/instructions/guepard-corp/qwery-core/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,904 This file is loaded in full into every session.
When invoked 1,904 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
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 $0.01904 $0.01904
Opus 5 $0.00952 $0.00952
Sonnet 5 $0.00381 $0.00381
Haiku 4.5 $0.00190 $0.00190

Measured 5d ago against content hash d94579855005, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

qwery-core 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 5d 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.

AGENTS.md · 165 lines

How it starts

The opening of the file, as written. The whole thing — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — Strict rules for AI contributors

You are contributing to qwery-agent, an AI data analyst with a TUI. This file is the machine-oriented contract. README.md is for humans.

If you don't read this end-to-end, you will violate an invariant. Decisions live in memory/ADR/decisions.md and memory/ADR/ui-decisions.md. Architecture diagrams live in memory/diagrams/.


1. Non-negotiable invariants

These hold before anything else. Breaking them blocks a PR.

  1. Privacy boundary (ADR #28). The LLM never receives row-level data from any datasource.
    • runQuery accepts aggregate-only SQL, single-row scalar output, validated locally.
    • schema and describeQuery return only column metadata.
    • present renders results locally via Mustache + helpers — only { ok, rowCount } goes upstream.
    • The privacy invariant test (tooling/privacy-check.ts) is enforced in pre-push and CI.
  2. Tool minimalism (ADR-locked). Do not add a tool to the core agent unless it materially improves LLM reasoning. "Convenience" is not a justification.
  3. Hexagonal architecture (ADR #12). domain/ and application/ never import from adapters/ or extensions/. Enforced by dependency-cruiser.
  4. English only. All code, comments, identifiers, commit messages and documentation are in English. Chat with the user can be in other languages; the project file content cannot.
  5. No env vars for LLM config. Providers are configured via /models in the TUI, stored at ~/.qwery/config.json. Never re-introduce env-var fallbacks for provider credentials.
  6. No code without unit tests. Every new module / feature / non-trivial change ships with bun:test coverage in the same turn. A code change without tests is incomplete. Cover happy path + at least one edge case + at least one failure mode. For LLM-dependent code, inject a stream function or use Vercel AI SDK's simulateReadableStream / simulateStreamingMiddleware rather than calling real models.

Read the full file on GitHub · 165 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. 5d ago First seen · 165 lines · 1,904 tokens per session scan A d94579855005

Subscribe to this mod's changes

qwery-core AGENTS.md is an instructions file published in the GitHub repository Guepard-Corp/qwery-core (134 stars, last pushed 1mo ago), licensed MIT. It adds 1,904 tokens to every session, about $0.0095 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.