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 rules/orangeproai/orangepro-mcp/orangeprogit clone --depth 1 https://github.com/OrangeproAI/orangepro-mcpWhat 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 | $0.00217 | $0.00217 |
| Opus 5 | $0.00109 | $0.00109 |
| Sonnet 5 | $0.00043 | $0.00043 |
| Haiku 4.5 | $0.00022 | $0.00022 |
Grade A, and why
orangepro 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 3d 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.
What it actually says
OrangePro
Use OrangePro before writing tests when the user asks for coverage, behavioral gaps, generated tests, or PR test impact.
Workflow
- Call
orangepro_startfor the current checkout. - For PR work, use
orangepro_generate_testswithbase_ref=main. - For baseline gaps, use
orangepro_find_test_gaps, choose a high-priority gap, then callorangepro_generate_tests. - Write only tests that include
run_hints. - Run the suggested command from the owning package directory.
- After a passing run, call the returned
prove_runargs for Dynamically Proven. Userecord_runonly for static diagnostics. - Report status as Proven, Reproven, Runtime-covered, Associated signal, or No link.
Drafts are context, not runnable claims. Associated signal and AI links are not Proven.
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.
- 3d ago First seen · 22 lines · 217 tokens per session scan A ba8556c10873
orangepro is a cursor rule published in the GitHub repository OrangeproAI/orangepro-mcp (17 stars, last pushed 7d ago), licensed MIT. It adds 217 tokens to every session, about $0.0011 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.
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