Performance capacity

Skill majiayu000/spellbook/skills/performance-capacity

Cross-runtime skills for Claude Code, Codex, and multi-agent workflows.

Install

npx -y skills add majiayu000/spellbook --skill performance-capacity

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What its author says it does

Copied from the file, not written here

Plan, diagnose, and verify performance budgets, latency targets, load tests, capacity estimates, bottleneck analysis, caching strategy, query efficiency, queue throughput, and regression gates. Use when a feature may be slow, a system must scale, a performance regression is suspected, or release readiness depends on throughput, cost, memory, CPU, or response time.

SKILL.md

2.0 KB, as published. Nobody here has run it

Performance Capacity

Purpose

Use this skill to make performance measurable before optimizing. It turns vague "make it faster" work into budgets, probes, bottleneck hypotheses, and regression gates.

Baseline First

Before changing code, capture:

User-facing operation or background job under test.
Current p50/p95/p99 latency or throughput.
Data size and concurrency assumptions.
Resource limits: CPU, memory, IO, network, database, queue.
Existing cache behavior and invalidation rules.
Cost or quota constraints.

If no baseline can be gathered, state the nearest measurable proxy and its limitations.

Budget Design

Define budgets by surface:

Surface	Examples
UI	TTI, interaction latency, bundle size, render count
API	p95 latency, error rate, DB query count, payload size
Jobs	throughput, max lag, retry cost, idempotency
Data	query plan, index coverage, backfill duration
Infra	CPU/RSS, concurrency, autoscaling, cost per request

Optimization Rules

Optimize the measured bottleneck, not the most familiar code.
Prefer algorithmic, query, batching, and cache correctness fixes before capacity-only fixes.
Define cache invalidation and stale-data tolerance.
Add a regression test, benchmark, or dashboard check for risky paths.
Do not trade correctness, authorization, or tenant isolation for speed.

Output Shape

operation:
baseline:
target_budget:
bottleneck_hypothesis:
measurement_plan:
optimization_options:
capacity_estimate:
regression_gate:
verification_commands:

Gives 0 of the 12 instructions most performance cost skills give

Counted across 803 of the 1,058 authors here whose files we hold, read 2026-08-06

keep skill files under 500 linesin 82 of 803, across 17 files
use imperative form in instructionsin 81 of 803, across 10 files
draft assertions while test runs are in progressin 75 of 803, across 9 files
create two to three realistic test promptsin 74 of 803, across 8 files
write skill descriptions to be pushyin 72 of 803, across 7 files
save test cases to evals jsonin 72 of 803, across 6 files
ask questions about edge cases and input formatsin 71 of 803, across 6 files
save timing data immediately when runs completein 70 of 803, across 5 files
include all trigger conditions in the skill descriptionin 69 of 803, across 3 files
launch all test runs in a single turnin 69 of 803, across 3 files
capture intent before writing a skillin 67 of 803, across 1 file
import directly instead of barrel filesin 52 of 803, across 15 files

Said here and by no other author read

state a measurable proxy if no baseline exists
define performance budgets by system surface
prefer algorithmic query batching and cache fixes
add a regression test for risky paths
produce the specified performance output document

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.