Agent skill

Performance Capacity

by majiayu000 in majiayu000/spellbook

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

MITAuto-check passedProduct & Project Management

Install Performance Capacity

skills CLI
$ npx skills add majiayu000/spellbook --skill performance-capacity -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install majiayu000/spellbook performance-capacity --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/majiayu000/spellbook.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/performance-capacity .claude/skills/performance-capacity && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
performance-capacity
GitHub stars
287
Token cost
~501 tokens
SKILL.md length
186 words
Files
2
Skills in repo
97
Repo updated
First seen
Licence
MIT

At a glance

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

  • Works in 6 steps: User-facing operation or background job… → Current p50/p95/p99 latency or throughput. → Data size and concurrency assumptions. → …
  • A feature may be slow
  • SKILL.md covers Purpose, Baseline First, Budget Design and Optimization Rules, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Performance Capacity is an agent skill from majiayu000/spellbook. 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.

Its SKILL.md is about 500 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

It sits in Product & Project Management, covering Web performance, Load testing and Feature launches and release readiness. The repository describes itself as: Cross-runtime skills for Claude Code, Codex, and multi-agent workflows. The licence is MIT.

When your agent uses it

  • A feature may be slow
  • A system must scale
  • A performance regression is suspected
  • Release readiness depends on throughput

Example prompts

  • “/performance-capacity”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

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

What it can do on your machine

Read from SKILL.md and the folder at commit ed52af7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Performance Capacity loads about 501 tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 186 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~97
When it runs · the whole SKILL.md, loaded when a task matches
~501

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from majiayu000/spellbook at commit ed52af7, republished under its MIT licence (© majiayu000). 186 words, ~501 tokens.

Download SKILL.mdSave it as .claude/skills/performance-capacity/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
performance-capacity
description
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.

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:

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

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

Budget Design

Define budgets by surface:

SurfaceExamples
UITTI, interaction latency, bundle size, render count
APIp95 latency, error rate, DB query count, payload size
Jobsthroughput, max lag, retry cost, idempotency
Dataquery plan, index coverage, backfill duration
InfraCPU/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

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

© majiayu000, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/performance-capacity of majiayu000/spellbook.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit ed52af7

Compare with similar skills

Performance Capacity next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Performance Capacity compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Performance Capacity this skillmajiayu000/spellbook287—~501Automated safety check: PassMIT
Solo Business Idea Reviewmanor-os/manor-ai162—~3.1kAutomated safety check: PassCustom licence
Convex Launch Readinessopenclaw/clawhub9.5k—~1.2kAutomated safety check: PassMIT
Scaling Load Assumptionshashgraph-online/awesome-codex-plugins1.3k—~2.3kAutomated safety check: PassApache-2.0
Schematicblader/schematic241—~2.2kAutomated safety check: PassMIT
Production Auditaffaan-m/ECC276k1 repos~1.9kAutomated safety check: PassMIT

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Questions about Performance Capacity

What does Performance Capacity do?

Plan, diagnose, and verify performance budgets, latency targets, load tests, capacity estimates, bottleneck analysis, caching strategy, query efficiency, queue throughput, and regression gates. Performance Capacity is an agent skill from majiayu000/spellbook. Plan, diagnose, and verify performance budgets, latency targets, load tests, capacity estimates, bottleneck analysis, caching strategy, query efficiency, queue throughput, and regression gates.

When should I use Performance Capacity?

Performance Capacity fits situations like: A feature may be slow; A system must scale; A performance regression is suspected; release readiness depends on throughput.

How do I install Performance Capacity in Claude Code?

Run `npx skills add majiayu000/spellbook --skill performance-capacity -a claude-code`. Or copy the skill folder (skills/performance-capacity in majiayu000/spellbook) into .claude/skills/performance-capacity in your project. Claude Code loads it when a task matches its description.

How do I install Performance Capacity in Codex?

Run `npx skills add majiayu000/spellbook --skill performance-capacity -a codex`. Or copy the skill folder (skills/performance-capacity in majiayu000/spellbook) into .agents/skills/performance-capacity in your project. Codex loads it when a task matches its description.

Can I use Performance Capacity in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add majiayu000/spellbook --skill performance-capacity -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/performance-capacity, .gemini/skills/performance-capacity, .github/skills/performance-capacity and .opencode/skills/performance-capacity in your project.

What does Performance Capacity need to run?

SKILL.md names no scripts, command-line tools or credentials: Performance Capacity is instructions for the agent only.

Does Performance Capacity access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Performance Capacity safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Performance Capacity use?

Performance Capacity is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Performance Capacity use?

About 501 tokens (SKILL.md is roughly 2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Performance Capacity?

Skills that share tags, products or a category with Performance Capacity: Solo Business Idea Review (manor-os/manor-ai, 162 stars), Convex Launch Readiness (openclaw/clawhub, 9.5k stars), Scaling Load Assumptions (hashgraph-online/awesome-codex-plugins, 1.3k stars) and Schematic (blader/schematic, 241 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Performance Capacity?

majiayu000 (a GitHub user) maintains it in majiayu000/spellbook, which has 287 GitHub stars. The repository holds 97 skills in this directory. The repository was last updated on October 8, 2026.

Source: majiayu000/spellbook on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.