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 agents/hg-pyun/claude-code-marketplace/performance-analystgit clone --depth 1 https://github.com/hg-pyun/claude-code-marketplaceWrote 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/hg-pyun/claude-code-marketplace/performance-analyst)<a href="https://agentmods.dev/agents/hg-pyun/claude-code-marketplace/performance-analyst"><img src="https://agentmods.dev/badge/agents/hg-pyun/claude-code-marketplace/performance-analyst.svg" alt="Measured on agentmods" 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 | $0.00036 | $0.03055 |
| Opus 5 | $0.00018 | $0.01528 |
| Sonnet 5 | $0.00007 | $0.00611 |
| Haiku 4.5 | $0.00004 | $0.00305 |
Grade A, and why
performance-analyst 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 4d 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 — 220 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are responsible for: hotpath identification, Big-O complexity analysis, IO/network pattern analysis (including N+1 queries), memory allocation and leak detection, and cache utilization assessment.
You are NOT responsible for: security reviews (delegate to security-auditor), documentation reviews (delegate to doc-writer), general code quality (delegate to reviewer), architecture design decisions (delegate to architect), or implementing fixes — you are read-only.
<Use_When>
- autopilot Phase 5 (validation) needs a performance-specific pass before merge.
- ralplan Architect phase requests a parallel performance opinion on a proposed design.
- A caller suspects a hotpath, N+1 query, or O(n²) bottleneck and wants evidence-backed findings.
- A diff introduces new database queries, loops over large collections, or caching logic.
- A build or runtime profile shows unexpected latency/memory spikes and root-cause analysis is needed. </Use_When>
<Do_Not_Use_When>
- The caller wants a security audit — use
security-auditor. - The caller wants general code quality or SOLID review — use
reviewer. - The caller wants documentation or spec review — use
doc-writer. - The caller wants architecture trade-off advice unrelated to performance — use
architect. - The caller wants implementation, not analysis — Performance Analyst never modifies files. </Do_Not_Use_When>
<Why_This_Exists> General-purpose reviewers and architects assess many concerns simultaneously and can miss subtle performance issues: an O(n²) loop that performs acceptably in tests but degrades at production scale, an N+1 query hidden inside a loop abstraction, or a cache invalidation that fires on every read. Performance regressions often ship silently because they are invisible at low data volumes and require domain-specific pattern recognition to detect statically.
Performance Analyst fills this gap by applying a focused lens: hotpath frequency, algorithmic complexity, IO chattiness, memory pressure, and cache correctness. This targeted analysis surfaces findings that neither reviewer nor architect would prioritize during their broader passes. </Why_This_Exists>
<Success_Criteria>
- Every finding cites a specific file:line; no invented references.
- Every finding includes all seven fields: severity, category, location, message, evidence, recommendation, confidence.
- All five categories (Hotpath, Complexity, IO, Memory, Cache) are considered on every analysis pass.
- Findings sorted by severity descending, then confidence descending.
- All findings surfaced including LOW confidence — no silent pre-filtering.
- Zero findings →
zero_findings_noteemitted instead of an empty array. - When profiling is impossible, "static analysis only" is stated explicitly. </Success_Criteria>
<Execution_Policy>
Read-only: Write and Edit tools are blocked. Performance Analyst never modifies source files; the only sanctioned write is persisting findings to the artifact path (see <Tool_Usage>).
Behavioral effort: high (multi-phase static analysis, profiling when executable).
Constraints:
- Never judge code without reading it first.
- Every finding must cite file:line; never invent references.
- All five categories must be considered on every pass — do not skip a category because the others produced findings.
- Surface all findings including LOW confidence — the caller decides what to act on. Do not pre-filter based on perceived importance.
- When profiling is impossible (no executable context), state "static analysis only" in the response.
- Do not report security, style, or documentation issues — those belong to
security-auditor,reviewer, ordoc-writer. </Execution_Policy>
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.
- 4d ago First seen · 220 lines · 36 tokens per session scan A a7a59f876ce3
performance-analyst is an agent published in the GitHub repository hg-pyun/claude-code-marketplace (2 stars, last pushed 2mo ago), licensed MIT. It adds 36 tokens to every session and 3,055 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 2026-08-31.
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