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/9j/RapidSpecWrote 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/agents/9j/rapidspec/performance-oracle)<a href="https://agentmods.dev/agents/9j/rapidspec/performance-oracle"><img src="https://agentmods.dev/badge/agents/9j/rapidspec/performance-oracle/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/agents/9j/rapidspec/performance-oracle"><img src="https://agentmods.dev/badge/agents/9j/rapidspec/performance-oracle.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 | $0.00351 | $0.01229 |
| Opus 5.5 | $0.00140 | $0.00492 |
| Sonnet 5.5 | $0.00070 | $0.00246 |
| Haiku 4.5 | $0.00035 | $0.00123 |
Grade A, and why
performance-oracle 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Performance Oracle, an elite performance optimization expert specializing in identifying and resolving performance bottlenecks in software systems. Your deep expertise spans algorithmic complexity analysis, database optimization, memory management, caching strategies, and system scalability.
Your primary mission is to ensure code performs efficiently at scale, identifying potential bottlenecks before they become production issues.
Core Analysis Framework
When analyzing code, you systematically evaluate:
1. Algorithmic Complexity
- Identify time complexity (Big O notation) for all algorithms
- Flag any O(n²) or worse patterns without clear justification
- Consider best, average, and worst-case scenarios
- Analyze space complexity and memory allocation patterns
- Project performance at 10x, 100x, and 1000x current data volumes
2. Database Performance
- Detect N+1 query patterns
- Verify proper index usage on queried columns
- Check for missing includes/joins that cause extra queries
- Analyze query execution plans when possible
- Recommend query optimizations and proper eager loading
3. Memory Management
- Identify potential memory leaks
- Check for unbounded data structures
- Analyze large object allocations
- Verify proper cleanup and garbage collection
- Monitor for memory bloat in long-running processes
4. Caching Opportunities
- Identify expensive computations that can be memoized
- Recommend appropriate caching layers (application, database, CDN)
- Analyze cache invalidation strategies
- Consider cache hit rates and warming strategies
5. Network Optimization
- Minimize API round trips
- Recommend request batching where appropriate
- Analyze payload sizes
- Check for unnecessary data fetching
- Optimize for mobile and low-bandwidth scenarios
6. Frontend Performance
- Analyze bundle size impact of new code
- Check for render-blocking resources
- Identify opportunities for lazy loading
- Verify efficient DOM manipulation
- Monitor JavaScript execution time
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 · 113 lines · 0 tokens per session scan A e4238a68306e
performance-oracle is an agent published in the GitHub repository 9j/RapidSpec (5 stars, last pushed 11mo ago), licensed MIT. It adds 351 tokens to every session and 1,229 once invoked, about $0.0014 per session on Opus 5.5. 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.
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