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/csoai-org/compression-ai-mcp/cursorrulesgit clone --depth 1 https://github.com/CSOAI-ORG/compression-ai-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 | $0.00069 | $0.00069 |
| Opus 5 | $0.00034 | $0.00034 |
| Sonnet 5 | $0.00014 | $0.00014 |
| Haiku 4.5 | $0.00007 | $0.00007 |
Grade A, and why
cursorrules 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 yesterday.
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
compression-ai-mcp - Auto-trigger Rules
When the user asks about compression, use compression-ai-mcp tools: estimate_ratio, suggest_algorithm, calculate_savings, benchmark_data
Data compression analysis and optimization tools powered by MEOK AI Labs.
Install: pip install compression-ai-mcp
By MEOK AI Labs — MIT licensed.
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.
- yesterday First seen · 10 lines · 69 tokens per session scan A 17c86a83274c
cursorrules is a cursor rule published in the GitHub repository CSOAI-ORG/compression-ai-mcp (0 stars, last pushed 1mo ago), licensed MIT. It adds 69 tokens to every session, about $0.0003 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 cursor rules, from other repositories
cursorrules
When the user asks about contract review, use contract-review-ai-mcp tools: analyzecontract, extractclauses, identifyrisks, comparecontracts, summarizecontract.
cursorrules
When the user asks about COBOL, legacy modernization, mainframe migration, banking IT, COBOL parser, use cobol-bridge-mcp tools.
cursorrules
When the user asks about churn predictor, use churn-predictor-ai-mcp tools: predictchurn, batchpredictchurn, getcustomerrisk, trackcustomer, updatecustomersignals.
cursorrules
When the user asks about ad copy, use ad-copy-ai-mcp tools: generateadcopy, generatevariants, createcampaign, getcampaign, addcreative.
cursorrules
When the user asks about accessibility, use accessibility-ai-mcp tools: checkcolorcontrast, suggestalttext, checkheadinghierarchy, ariavalidator.
cursorrules
When the user asks about api docs generator, use api-docs-generator-ai-mcp tools: generateendpoint, generateschema, generatefullspec, addauthtospec, validatespec.