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Performance Capacity · majiayu000 | DecimalAI

devopsby majiayu000

Performance Capacity

majiayu000/performance-capacity

Source majiayu000/spellbook ↗License MIT

Plan, diagnose, and verify performance budgets, latency targets, load tests, capacity estimates, bottleneck analysis, caching strategy, query efficiency, queue throughput, and regression gates.

SkillScore91Maintained

Automatic

DevOps & SRE pack

Last verified 8/27/2026

What it changes

Passed 20 of 22 test cases with the skill, and 8 of 22 without it.

Without skill36%

With skill91%

Checks it passed that the model alone missed

The response specifies cache invalidation rules.
The response states the limitations of the proxy.
The response uses the output shape block key baseline:

and 11 more in the full report

12 fixed8 passed either way2 still failing0 broke

Pass-rate lift: +55 pp
Tokens: -18%
Agent turns: 0%
Response time: -24%

Model gemini-3.6-flashMeasured 8/27/2026v120 of 22 cases passed with skill

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/majiayu000-performance-capacity/SKILL.md https://app.decimal.ai/s/majiayu000-performance-capacity/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add majiayu000-performance-capacity, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/majiayu000-performance-capacity/ and pins it in .decimal/skills.lock

decimalai skills add majiayu000-performance-capacity

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/majiayu000-performance-capacity/SKILL.md https://app.decimal.ai/s/majiayu000-performance-capacity/SKILL.md

Raw file: /s/majiayu000-performance-capacity/SKILL.md ↗ · machine-readable summary at /s/majiayu000-performance-capacity.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 12 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 12

Prompt

Our order search endpoint `/api/v2/orders/search` is slowing down significantly during peak traffic hours. I need a structured performance capacity plan for this API before we start writing any fix code. Please lay out the specific operation, document the current baseline metrics, set clear budget targets, formulate a bottleneck hypothesis, and provide a measurement plan. Additionally, list candidate optimization options, capacity estimates under higher load, a regression gate to catch future performance drops, and command-line verification instructions.

What was checked, without and with the skill
Checked	Without skill	With skill
The response uses the output shape block key operation:	Missed	Passed
The response uses the output shape block key target_budget:	Missed	Passed
The response uses the output shape block key regression_gate:	Missed	Passed

case-01 · gemini-3.6-flash · 8/27/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md52 linessingle file

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

Track record

Benchmark

20 / 22

test cases passed, vs 8 / 22 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

majiayu000 / spellbook

skills/performance-capacity/SKILL.md

View on GitHub ↗

License MITImported 8/3/2026Version v1

Other skills for the same job

Published skills whose descriptions closely match this one, with their headline benchmark lift.

sickn33/performance-engineerExpert performance engineer specializing in modern observability,Close match0 pp pass-rate lift

More skills from the same source and nearby in the registry, with their headline benchmark lift.

Ready to supercharge your AI agents?

See it in action

What's inside

Performance Capacity

Purpose

Baseline First

Budget Design

Optimization Rules

Output Shape

Track record

Benchmark

Adoption

SkillSafety

Source

Other skills for the same job

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