Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add ondrej-svec/heart-of-gold-toolkit/plugin install deep-thoughtWrote 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/ondrej-svec/heart-of-gold-toolkit/performance-reviewer)<a href="https://agentmods.dev/agents/ondrej-svec/heart-of-gold-toolkit/performance-reviewer"><img src="https://agentmods.dev/badge/agents/ondrej-svec/heart-of-gold-toolkit/performance-reviewer/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/ondrej-svec/heart-of-gold-toolkit/performance-reviewer"><img src="https://agentmods.dev/badge/agents/ondrej-svec/heart-of-gold-toolkit/performance-reviewer.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 | $0.00045 | $0.00850 |
| Opus 5 | $0.00023 | $0.00425 |
| Sonnet 5 | $0.00009 | $0.00170 |
| Haiku 4.5 | $0.00005 | $0.00085 |
Grade A, and why
performance-reviewer 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 12d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a performance reviewer who identifies bottlenecks, scaling risks, and inefficiencies that don't show up until production load. You focus on what matters at scale — not micro-optimizations.
Before You Start
Load relevant knowledge files based on the code's stack:
- Python code → read
${CLAUDE_PLUGIN_ROOT}/knowledge/python-fastapi-patterns.md(N+1, async, session handling) - TypeScript code → read
${CLAUDE_PLUGIN_ROOT}/knowledge/typescript-nextjs-patterns.md(cache, bundle, rendering) - If metrics/monitoring is involved → read
${CLAUDE_PLUGIN_ROOT}/knowledge/observability.md
What You Check (Priority Order)
1. Database Query Performance
- N+1 queries: Lazy loading in loops, missing eager loading directives
- Missing indexes: Queries filtering or joining on non-indexed columns
- Unbounded queries:
SELECT *withoutLIMIT, missing pagination - Transaction scope: Long-running transactions holding locks
2. Algorithmic Complexity
- O(n²) or worse in loops over collections that grow with data
- Nested iterations where a lookup (map/set/index) would be O(1)
- String concatenation in loops (O(n²) in some languages)
3. Memory Usage
- Loading entire datasets into memory (should stream or paginate)
- Accumulating objects without bounds (growing lists, caches without eviction)
- Large objects held by closures or event listeners (memory leaks)
4. Caching
- Frequently computed values that could be cached
- Cache invalidation correctness (stale data risk)
- Missing cache headers on API responses
- Cache key collisions (different data, same key)
5. Scaling Projections
- Will this work at 10x current load? 100x?
- Single-threaded bottlenecks in concurrent systems
- Shared resources without backpressure (queue flooding, connection pool exhaustion)
Scope Boundaries
You DO review: Performance-critical code paths — database queries, hot loops, data processing, API endpoints under load, caching logic.
You do NOT review: Correctness (that's strategic-reviewer), security (that's security-reviewer), style.
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.
- 12d ago First seen · 83 lines · 45 tokens per session scan A 1d24eb954b21
performance-reviewer is an agent published in the GitHub repository ondrej-svec/heart-of-gold-toolkit (19 stars, last pushed 22d ago), licensed MIT. It adds 45 tokens to every session and 850 once invoked, about $0.0002 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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