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.
git 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/rules/arango-solutions/arango-sparql-py/200-testing)<a href="https://agentmods.dev/rules/arango-solutions/arango-sparql-py/200-testing"><img src="https://agentmods.dev/badge/rules/arango-solutions/arango-sparql-py/200-testing/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/rules/arango-solutions/arango-sparql-py/200-testing"><img src="https://agentmods.dev/badge/rules/arango-solutions/arango-sparql-py/200-testing.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 | $0.00000 | $0.00791 |
| Opus 5.5 | $0.00000 | $0.00316 |
| Sonnet 5.5 | $0.00000 | $0.00158 |
| Haiku 4.5 | $0.00000 | $0.00079 |
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 1mo 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Testing rules
Frameworks
pytestis the only test runner. Usepytest -q -ralocally.- Markers (declared in
pyproject.toml):integration— requires a running ArangoDB.w3c— W3C SPARQL 1.1 DAWG harness.cross— cross-validation againstpyoxigraphas the reference triplestore (the SPARQL analog of the Cypher project'scross/Neo4j marker).eval— NL→SPARQL eval harness (slow; gated behind env var).
Reference triplestore — pyoxigraph
- Use
pyoxigraphas 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
pyoxigraphand into ArangoDB (via the schema-mapper-defined mapping), execute the same SPARQL againstpyoxigraphdirectly and against ArangoDB viaarango-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 callpyoxigraphdirectly 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 amake fetch-w3cscript). tests/w3c/runner.pyenumerates manifests (mf:Manifest) viardfliband 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.mdlisting 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.
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.
- 1mo ago First seen · 63 lines · 0 tokens per session scan A ebf4d70485d1
200-testing is a cursor rule published in the GitHub repository arango-solutions/arango-sparql-py (2 stars, last pushed 10d 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.
Other cursor rules, from other repositories
20-testing-generated-and-structure
Testing expectations, generated-file boundaries, and CLI structure contract.
fuzzing
Fuzzing setup and guidelines for skia-rs.
testing-and-quality
The testcomprehensive.py provides systematic testing of all 31 MCP tools.
smoke-monkey-tester
Smoke tests for core functionality and monkey/chaos tests aiming to break the system with randomized inputs. / TR: Sistemin temel fonksiyonlarını kontrol eden smoke testler ve rastgele girdilerle sistemi çökertmeyi hedefleyen monkey/chaos testleri.
testing
Testing conventions for Ion Design System using Jest and Angular Testing Library.
STAGE_S5_TEST_POINTS
A staged workflow for turning approved requirements into a complete list of test points. It checks required earlier documents and records any requirement that has no matching test point.