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/brendadeeznuts1111/betting-brain-v3Wrote 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/brendadeeznuts1111/betting-brain-v3/coverage-thresholds)<a href="https://agentmods.dev/rules/brendadeeznuts1111/betting-brain-v3/coverage-thresholds"><img src="https://agentmods.dev/badge/rules/brendadeeznuts1111/betting-brain-v3/coverage-thresholds/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/brendadeeznuts1111/betting-brain-v3/coverage-thresholds"><img src="https://agentmods.dev/badge/rules/brendadeeznuts1111/betting-brain-v3/coverage-thresholds.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 | $0.00780 |
| Opus 5 | $0.00000 | $0.00390 |
| Sonnet 5 | $0.00000 | $0.00156 |
| Haiku 4.5 | $0.00000 | $0.00078 |
Grade A, and why
coverage-thresholds 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 8d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Coverage Threshold Rules
Dual Threshold System
This codebase uses dual coverage thresholds to balance:
- Strict production standards
- Flexible analytics testing
Main Suite: 80% Coverage (Strict)
# bunfig.toml
coverage = false # coverage off by default
coverageThreshold = 0.8 # 80% for production code
Analytics Suite: 0% Coverage (Flexible)
# bunfig.analytics.toml
coverage = true
coverageThreshold = 0 # No threshold for analytics tests
Package.json Scripts
Main Suite Commands
{
"test": "bun test --randomize",
"test:coverage": "bun test --coverage --randomize"
}
Analytics Suite Commands
{
"analytics:test": "bun test tests/unit/analytics-testing-example.test.ts --randomize",
"analytics:test:coverage": "bun test --coverage --randomize tests/unit/analytics-testing-example.test.ts --config bunfig.analytics.toml",
"analytics:ci": "CI=true bun run analytics:test:coverage"
}
Why Dual Thresholds?
Production Code (80% threshold)
- Purpose: Ensure high-quality, well-tested production code
- Scope: All business logic, API endpoints, core functionality
- Enforcement: CI fails if coverage < 80%
Analytics Code (0% threshold)
- Purpose: Allow rapid iteration on analytics utilities
- Scope: Test helpers, stubs, analytics-specific utilities
- Enforcement: No coverage requirement, focus on functionality
Configuration Hierarchy
bunfig.toml (root)
↓ (always takes precedence for critical settings)
--config flag
↓ (limited override capability)
Environment variables
↓ (minimal support)
Best Practices
✅ Do These
- Keep main threshold at 80% for production quality
- Use analytics config only for analytics tests
- Document threshold rationale in commit messages
- Test both thresholds in CI
❌ Don't Do These
- Lower main threshold below 80%
- Use analytics config for production code
- Mix threshold configurations
- Ignore coverage failures in main suite
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.
- 8d ago First seen · 119 lines · 0 tokens per session scan A d4a42222041e
coverage-thresholds is a cursor rule published in the GitHub repository brendadeeznuts1111/betting-brain-v3 (8 stars, last pushed 11mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 780 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
workflow-deployment
Workflow testing and deployment process guide.
writing-tests
How to write tests in the monorepo.
manual-review
The main set of rules for manual review during an active project change. It defines different kinds of checks, who performs them, how results are recorded, and when supporting evidence is required.
manual-review.data-readiness
A set of rules for preparing manual checks before a proposed change is implemented. It requires each user-facing check to include exact sample data, clear steps, and any needed setup.
manual-review.evidence
A set of rules for writing and reviewing the evidence section of a task list. It defines a consistent checklist format and explains how to describe a user action together with the result that should follow.
testing-anti-patterns
Guidelines for avoiding misleading or weak tests. They say tests should check real application behavior, use mocks only when needed for isolation, and avoid adding code to production solely for testing.