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/arango-solutions/arango-sparql-py/agents-mdgit clone --depth 1 https://github.com/arango-solutions/arango-sparql-pyWrote 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/arango-solutions/arango-sparql-py/agents-md)<a href="https://agentmods.dev/instructions/arango-solutions/arango-sparql-py/agents-md"><img src="https://agentmods.dev/badge/instructions/arango-solutions/arango-sparql-py/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 | $0.01561 | $0.01561 |
| Opus 5 | $0.00781 | $0.00781 |
| Sonnet 5 | $0.00312 | $0.00312 |
| Haiku 4.5 | $0.00156 | $0.00156 |
Grade A, and why
arango-sparql-py 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.
How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — shared agent contract for arango-sparql-py
This file is the single, model-agnostic contract for any AI coding agent
operating in this repository (Cursor, Claude Code, Codex CLI, GitHub
Copilot Workspace, etc.). It complements — but does not replace — the
project rules under .cursor/rules/.
If you are an agent reading this for the first time, read this file fully before making any edit, then consult the rule files referenced below as needed.
Mission
Build arango-sparql-py, a Python microservice that transpiles
SPARQL 1.1 queries into ArangoDB AQL, with an NL→SPARQL pipeline,
a Vite/React UI, and a W3C-compliant test harness. It modernizes the
legacy JavaScript Foxx service arango-sparql and is the sister
project to arango-cypher-py.
Hard rules (memorize)
- Use
rdflibfor SPARQL parsing. Never ANTLR, never a custom parser. Entry point isrdflib.plugins.sparql.parser.parseQuery→rdflib.plugins.sparql.algebra.translateQuery. - Use the AQL query builder for all AQL emission. Bind variables only — never inline literals or hand-concatenate AQL strings.
- Port translation semantics from
references/arango-sparql/src/lib/, not from your training data. When in doubt, read the JS first. - Mirror
references/arango-cypher-py/'s structure. FastAPI app factory, route modules, pydantic models, multitenancy guards,pyproject.tomlshape,tests/layout — all should be a one-to-one analog so cross-repo navigation is trivial. pyoxigraphis the W3C ground truth for tests. Cross-validation tests run the same SPARQL againstpyoxigraphand against the transpiled AQL, then compare bindings.
Where to look
| Concern | Source of truth |
|---|---|
| Always-on identity & guardrails | .cursor/rules/000-project-context.mdc |
| Backend Python conventions | .cursor/rules/100-backend-python.mdc |
| Testing rules + W3C harness | .cursor/rules/200-testing.mdc |
| NL→SPARQL pipeline | .cursor/rules/300-nl2sparql.mdc |
| Frontend UI | .cursor/rules/400-frontend-ui.mdc |
| Spec, vision, ADRs, roadmap | docs/architecture/PRD.md (single source of truth; vision = App. C, ADRs = App. B) |
| Work tracking (WP status) | docs/architecture/implementation_plan.md (living plan; PRD = spec, this = status) |
| SPARQL→AQL porting recipe | .cursor/skills/sparql-to-aql/SKILL.md |
| Architecture template | references/arango-cypher-py/ |
| Translation semantics (legacy) | references/arango-sparql/src/lib/ |
| OWL/Turtle schema generator | references/arango-schema-mapper/ |
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.
- 5d ago First seen · 120 lines · 1,561 tokens per session scan A da0b729d7f00
arango-sparql-py AGENTS.md is an instructions file published in the GitHub repository arango-solutions/arango-sparql-py (2 stars, last pushed 18d ago), licensed MIT. It adds 1,561 tokens to every session, about $0.0078 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.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).