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 skills add 0xMassi/claude-skills --skill performance-audit-standardgit clone --depth 1 https://github.com/0xMassi/claude-skillsWrote 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/skills/0xmassi/claude-skills/performance-audit-standard)<a href="https://agentmods.dev/skills/0xmassi/claude-skills/performance-audit-standard"><img src="https://agentmods.dev/badge/skills/0xmassi/claude-skills/performance-audit-standard/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/skills/0xmassi/claude-skills/performance-audit-standard"><img src="https://agentmods.dev/badge/skills/0xmassi/claude-skills/performance-audit-standard.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 | $0.00076 | $0.02362 |
| Opus 5 | $0.00038 | $0.01181 |
| Sonnet 5 | $0.00015 | $0.00472 |
| Haiku 4.5 | $0.00008 | $0.00236 |
Grade A, and why
performance-audit-standard 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 11d 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 — 288 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Audit Standard
Methodology for identifying and fixing performance bottlenecks.
Audit Process
Step 1: Identify Hot Paths
Find code that runs frequently or processes large datasets:
- Request handlers (every HTTP request)
- Event processors (every WebSocket message)
- Loop bodies processing collections (per-item)
- Interval timers (every N seconds)
- Middleware/interceptors (every request)
Ask: "How many times per second does this code execute?" and "What's the typical input size?"
Step 2: Analyze Complexity
For each hot path, determine actual Big O:
| Pattern | Complexity | Example |
|---|---|---|
array.includes(x) |
O(n) | Linear scan per check |
array.find(x => ...) |
O(n) | Linear scan |
array.filter().map().filter() |
O(3n) + 3 allocations | Multiple passes |
Object.entries().find() |
O(n) | Linear scan of object |
array.sort() to find min/max |
O(n log n) | Overkill for single value |
| Nested loops with includes | O(n*m) | Quadratic |
Step 3: Apply Fixes
Common Performance Anti-Patterns
1. O(n) Membership Test → Use Set
// BAD: O(n) per check, O(n*m) in a loop
const newIds = currentIds.filter(x => !savedIds.includes(x));
// GOOD: O(1) per check, O(n+m) total
const savedSet = new Set(savedIds);
const newIds = currentIds.filter(x => !savedSet.has(x));
Impact: 1000x on large collections (1000 items: 1M comparisons → 1K).
2. O(n log n) Selection → Single-Pass
// BAD: filter + sort + take first = O(n) + O(n log n) + O(1)
const available = tokens.filter(t => !t.expired);
available.sort((a, b) => a.lastUsed - b.lastUsed);
const best = available[0];
// GOOD: Single O(n) pass
let best = null;
for (const t of tokens) {
if (t.expired) continue;
if (!best || t.lastUsed < best.lastUsed) best = t;
}
Impact: 10-50x faster, zero intermediate arrays.
3. Linear Lookup → Map Index
// BAD: O(n) per lookup
function findToken(value) {
return tokens.find(t => t.value === value);
}
// GOOD: O(1) per lookup
const tokenIndex = new Map(tokens.map(t => [t.value, t]));
function findToken(value) {
return tokenIndex.get(value);
}
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.
- 11d ago First seen · 288 lines · 76 tokens per session scan A 4372cce8d028
performance-audit-standard is a skill published in the GitHub repository 0xMassi/claude-skills (7 stars, last pushed 4mo ago), licensed MIT. It adds 76 tokens to every session and 2,362 once invoked, about $0.0004 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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