Borrowing it
Nothing to install: this file belongs to Guepard-Corp/qwery-core. 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/Guepard-Corp/qwery-core/main/AGENTS.mdgit clone --depth 1 https://github.com/Guepard-Corp/qwery-coreWrote 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/guepard-corp/qwery-core/agents-md)<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/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/instructions/guepard-corp/qwery-core/agents-md"><img src="https://agentmods.dev/badge/instructions/guepard-corp/qwery-core/agents-md.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 | $0.01904 | $0.01904 |
| Opus 5.5 | $0.00762 | $0.00762 |
| Sonnet 5.5 | $0.00381 | $0.00381 |
| Haiku 4.5 | $0.00190 | $0.00190 |
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 2mo 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 — 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.
- Privacy boundary (ADR #28). The LLM never receives row-level data from any datasource.
runQueryaccepts aggregate-only SQL, single-row scalar output, validated locally.schemaanddescribeQueryreturn only column metadata.presentrenders 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.
- Tool minimalism (ADR-locked). Do not add a tool to the core agent unless it materially improves LLM reasoning. "Convenience" is not a justification.
- Hexagonal architecture (ADR #12).
domain/andapplication/never import fromadapters/orextensions/. Enforced bydependency-cruiser. - 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.
- No env vars for LLM config. Providers are configured via
/modelsin the TUI, stored at~/.qwery/config.json. Never re-introduce env-var fallbacks for provider credentials. - No code without unit tests. Every new module / feature / non-trivial change ships with
bun:testcoverage 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'ssimulateReadableStream/simulateStreamingMiddlewarerather than calling real models.
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.
- 2mo ago First seen · 165 lines · 1,904 tokens per session scan A d94579855005
qwery-core AGENTS.md is an instructions file published in the GitHub repository Guepard-Corp/qwery-core (135 stars, last pushed 3mo ago), licensed MIT. It adds 1,904 tokens to every session, about $0.0076 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 2026-08-30.
qwery-core AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| qwery-core AGENTS.mdGuepard-Corp/qwery-core | Instructions file | 135 | 3mo ago | MIT | A | 1,904 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |