agentmods.dev

200-testing

A set of project rules for testing a SPARQL implementation, a system that queries linked-data graphs. It uses pytest, an automated Python testing tool, and checks results against pyoxigraph and W3C standards.

In plain words
What is it for?
Use it to run unit, integration, standards-compliance, cross-validation, and natural-language-to-SPARQL evaluation tests.
Why use it?
It provides a consistent reference for deciding whether query results are correct, including tests against ArangoDB and its translated queries.

Cursor rule for Cursor

2 16d ago A scan 0 tokens original MIT
View the source file arango-solutions/arango-sparql-py
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 rules/arango-solutions/arango-sparql-py/200-testing
Clone the repo
git clone --depth 1 https://github.com/arango-solutions/arango-sparql-py

Made for: Cursor.

Per session 0 Nothing until a file matches its globs; then the whole rule loads.
When invoked 791 The whole file, excluding the scripts and references it only reads on demand.
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 $0.00000 $0.00791
Opus 5 $0.00000 $0.00396
Sonnet 5 $0.00000 $0.00158
Haiku 4.5 $0.00000 $0.00079

Measured 2d ago against content hash ebf4d70485d1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

200-testing 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 2d 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.

.cursor/rules/200-testing.mdc · 63 lines

How it starts

The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Testing rules

Frameworks

  • pytest is the only test runner. Use pytest -q -ra locally.
  • Markers (declared in pyproject.toml):
    • integration — requires a running ArangoDB.
    • w3c — W3C SPARQL 1.1 DAWG harness.
    • cross — cross-validation against pyoxigraph as the reference triplestore (the SPARQL analog of the Cypher project's cross/Neo4j marker).
    • eval — NL→SPARQL eval harness (slow; gated behind env var).

Reference triplestore — pyoxigraph

  • Use pyoxigraph as the embedded W3C-compliant ground truth for every SPARQL semantics test. It runs in-process (no Docker) so tests stay fast.
  • Cross-validation pattern: load the same RDF data into pyoxigraph and into ArangoDB (via the schema-mapper-defined mapping), execute the same SPARQL against pyoxigraph directly and against ArangoDB via arango-sparql-py's transpiled AQL, then assert the result bindings match — order-insensitive for SELECT, set-equality for ASK/CONSTRUCT.
  • Helpers live in tests/helpers/oxi.py (loader + binding-equality comparator). Do not call pyoxigraph directly from individual test files.

W3C DAWG harness (mirror tests/tck/)

  • Vendor the W3C SPARQL 1.1 Evaluation tests under tests/w3c/data/ (gitignored if large; provide a make fetch-w3c script).
  • tests/w3c/runner.py enumerates manifests (mf:Manifest) via rdflib and yields (query_file, data_files, expected_results) tuples.
  • Each test is a single pytest case parametrized over the manifest entry IRI so failures point back to the W3C test name.
  • Maintain a tests/w3c/SKIP_REASONS.md listing intentionally skipped tests with the reason (analog of the TCK skip file).

Golden tests for translation

  • Pattern: one test file per SPARQL feature — e.g. test_translate_optional_goldens.py, test_translate_filter_goldens.py.
  • Inputs and expected AQL/bind_vars live in YAML next to the test file (mirror Cypher's golden YAML format). Updates require explicit human review — never auto-regenerate goldens in CI.

Read the full file on GitHub · 63 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. 2d ago First seen · 63 lines · 0 tokens per session scan A ebf4d70485d1

Subscribe to this mod's changes

200-testing is a cursor rule published in the GitHub repository arango-solutions/arango-sparql-py (2 stars, last pushed 16d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 791 tokens. 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.

Testing
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