Agent skill

Scale Benchmarks

by sickn33 in sickn33/agentic-awesome-skills

Reference document for monopoly scale-benchmarks. An agent skill from sickn33/agentic-awesome-skills.

MITAuto-check passedDatabases

Install Scale Benchmarks

skills CLI

$ npx skills add sickn33/agentic-awesome-skills --skill scale-benchmarks -a claude-code

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

GitHub CLI

$ gh skill install sickn33/agentic-awesome-skills scale-benchmarks --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/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/monopoly/scale-benchmarks .claude/skills/scale-benchmarks && 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/

Paste into Claude Code

Install the "scale-benchmarks" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/monopoly/scale-benchmarks into .claude/skills/scale-benchmarks/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scale-benchmarks", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/monopoly/scale-benchmarks

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add sickn33/agentic-awesome-skills --skill scale-benchmarks -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install sickn33/agentic-awesome-skills scale-benchmarks --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/monopoly/scale-benchmarks .agents/skills/scale-benchmarks && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "scale-benchmarks" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/monopoly/scale-benchmarks into .agents/skills/scale-benchmarks/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scale-benchmarks", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add sickn33/agentic-awesome-skills --skill scale-benchmarks -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install sickn33/agentic-awesome-skills scale-benchmarks --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/monopoly/scale-benchmarks .cursor/skills/scale-benchmarks && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "scale-benchmarks" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/monopoly/scale-benchmarks into .cursor/skills/scale-benchmarks/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scale-benchmarks", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/sickn33/agentic-awesome-skills.git --path skills/monopoly/scale-benchmarks

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add sickn33/agentic-awesome-skills --skill scale-benchmarks -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install sickn33/agentic-awesome-skills scale-benchmarks --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/monopoly/scale-benchmarks .gemini/skills/scale-benchmarks && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "scale-benchmarks" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/monopoly/scale-benchmarks into .gemini/skills/scale-benchmarks/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scale-benchmarks", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install sickn33/agentic-awesome-skills scale-benchmarks

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add sickn33/agentic-awesome-skills --skill scale-benchmarks -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/monopoly/scale-benchmarks .github/skills/scale-benchmarks && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "scale-benchmarks" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/monopoly/scale-benchmarks into .github/skills/scale-benchmarks/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scale-benchmarks", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add sickn33/agentic-awesome-skills --skill scale-benchmarks -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install sickn33/agentic-awesome-skills scale-benchmarks --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/monopoly/scale-benchmarks .opencode/skills/scale-benchmarks && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "scale-benchmarks" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/monopoly/scale-benchmarks into .opencode/skills/scale-benchmarks/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scale-benchmarks", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: scale-benchmarks
GitHub stars: 47k
Used in: 1 other repo
Token cost: ~1.4k tokens
SKILL.md length: 281 words
Files: 1
Skills in repo: 1,354
Repo updated: Oct 7, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Reference document for monopoly scale-benchmarks. An agent skill from sickn33/agentic-awesome-skills.

Tasks that involve Site reliability engineering
SKILL.md covers When to Use, Quick Estimation Formulas, Known Scale Limits of Common… and Capacity Planning by User Scale, plus 3 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Scale Benchmarks is an agent skill from sickn33/agentic-awesome-skills. Reference document for monopoly scale-benchmarks.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Databases, covering Site reliability engineering. It works with Redis. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

When your agent uses it

Tasks that involve Site reliability engineering

Example prompts

“/scale-benchmarks”

What it can do on your machine

Read from SKILL.md and the folder at commit ec02547. 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

Scale Benchmarks loads about 1.4k tokens when it runs. Until then it costs about 17 tokens; SKILL.md has 281 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~17
When it runs · the whole SKILL.md, loaded when a task matches: ~1.4k

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 sickn33/agentic-awesome-skills at commit ec02547, republished under its MIT licence (© sickn33). 281 words, ~1,367 tokens.

Download SKILL.mdSave it as .claude/skills/scale-benchmarks/SKILL.md (or your agent's skills folder).

name: scale-benchmarks
description: Reference document for monopoly scale-benchmarks.
source: community
date_added: 2026-09-04
risk: safe
reports-to: monopoly

MONOPOLY — Scale Benchmarks & Estimation Formulas

When to Use

Use this skill when the task matches this description: Reference document for monopoly scale-benchmarks.

Quick Estimation Formulas

User → RPS Conversion

Requests per second (avg) = DAU × avg_requests_per_user_per_day / 86400
Requests per second (peak) = avg_RPS × peak_multiplier

Peak multipliers by app type:
  Social media:      5–10×
  E-commerce:        3–5× (higher during sales)
  News / media:      10–20× (breaking news spike)
  B2B SaaS:          2–3× (business hours spike)
  Gaming:            5–15× (event-driven)

Storage Estimation

Storage per day    = requests_per_day × avg_payload_size
Storage per year   = storage_per_day × 365
With replication   = storage_per_year × replication_factor (3× typical)
With CDN/cache     = reduce by cache_hit_ratio (80% hit = 20% origin load)

Common payload sizes:
  Tweet / short text:    500B
  Social post with text: 2KB
  Profile data:          5KB
  Image (compressed):    200KB–2MB
  Video (per minute):    50MB (720p), 150MB (1080p)
  API JSON response:     1–20KB

Bandwidth Estimation

Inbound bandwidth  = avg_request_size × RPS
Outbound bandwidth = avg_response_size × RPS

Convert: 1 Gbps = 125 MB/s
         10 Gbps = 1.25 GB/s

Known Scale Limits of Common Technologies

Databases

Technology	Single Node Writes	Reads (with replicas)	Recommended Shard/Cluster Trigger
PostgreSQL	~5K–20K writes/s	~50K–200K reads/s	>5TB data or >20K writes/s
MySQL	~10K–25K writes/s	~60K–250K reads/s	>5TB or >25K writes/s
MongoDB	~20K–50K writes/s	~50K–100K reads/s	>100GB or >50K writes/s
Cassandra	~200K–1M writes/s	~200K–500K reads/s	Almost never needs explicit sharding
DynamoDB	Unlimited (managed)	Unlimited (managed)	Use provisioned capacity mode
Redis	~500K–1M ops/s	Same	>50GB data or cluster needed
Elasticsearch	~10K–50K docs/s	~1K–10K queries/s	>100M documents per index

Queues / Streams

Technology	Max Throughput	Max Consumers	Retention
Kafka	1M+ msgs/s per cluster	Unlimited consumer groups	Configurable (days–forever)
RabbitMQ	~50K–100K msgs/s	Limited by connections	Until consumed
SQS Standard	Unlimited (AWS-managed)	Unlimited	14 days
SQS FIFO	3K msgs/s per queue	Per group	14 days
Redis Pub/Sub	~1M msgs/s	Limited by subscribers	None (fire-and-forget)

Caching

Technology	Max Memory (single)	Max Throughput	Latency
Redis	~1TB RAM	~1M ops/s	<1ms
Memcached	~64GB RAM	~1M ops/s	<1ms
In-process (Caffeine/Guava)	JVM heap	Unlimited (local)	<0.1ms

Capacity Planning by User Scale

1K DAU

Avg RPS:       ~1–5 RPS
Peak RPS:      ~10–50 RPS
DB size/year:  ~10–50GB
Infra needed:  Single server, managed DB (RDS t3.medium), basic CDN
Monthly cost:  $50–200

10K DAU

Avg RPS:       ~10–50 RPS
Peak RPS:      ~100–500 RPS
DB size/year:  ~100–500GB
Infra needed:  2–4 app servers, RDS r5.large, Redis t3.medium, CDN
Monthly cost:  $300–800

100K DAU

Avg RPS:       ~100–500 RPS
Peak RPS:      ~1K–5K RPS
DB size/year:  ~1–5TB
Infra needed:  ASG (5–10 app servers), RDS r5.xlarge + 2 replicas, Redis cluster, CDN, ALB
Monthly cost:  $2K–8K

1M DAU

Avg RPS:       ~1K–5K RPS
Peak RPS:      ~10K–50K RPS
DB size/year:  ~10–50TB
Infra needed:  ASG (20–50 servers), DB sharding or Aurora, Redis cluster, Kafka, CDN, WAF
Monthly cost:  $20K–80K

10M DAU

Avg RPS:       ~10K–50K RPS
Peak RPS:      ~100K–500K RPS
DB size/year:  ~100–500TB
Infra needed:  Multi-region, microservices, distributed DB (Cassandra/CockroachDB), full CDN, dedicated SRE
Monthly cost:  $200K–2M+

Common SLO Targets

Tier	Availability	Monthly Downtime Allowed
99%	Basic	7.2 hours/month
99.9% (three nines)	Standard production	43.8 minutes/month
99.95%	Important services	21.9 minutes/month
99.99% (four nines)	Critical services	4.38 minutes/month
99.999% (five nines)	Telecom / payments	26 seconds/month

Achieving four nines requires: Multi-AZ deployment, automated failover, zero-downtime deploys, chaos engineering, 24/7 on-call.

Latency Budget Guidelines

User perceived latency targets:
  < 100ms  → Feels instant
  100–300ms → Acceptable for most interactions
  300ms–1s → Noticeable; optimize if possible
  > 1s     → Frustrating; unacceptable for critical paths

Network latency by distance (approximate):
  Same datacenter:    0.5ms
  Same region (AZ):   1–2ms
  Cross-region US:    30–60ms
  US to Europe:       80–120ms
  US to Asia:         150–250ms

Database query targets:
  Simple key-value:   < 1ms (cache)
  Simple DB query:    < 5ms
  Complex query:      < 50ms
  Reporting query:    < 500ms (async if > 1s)

Limitations

This is a reference document and may not cover all edge cases. Always verify architectures before production.

Files

Just SKILL.md in skills/monopoly/scale-benchmarks of sickn33/agentic-awesome-skills.

Open the folder on GitHubat commit ec02547

Used in 1 other repository

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

lingxling/awesome-skills-cnantigravity-awesome-skills/skills/monopoly/scale-benchmarks antigravity-awesome-skills/plugins/agentic-awesome-skills/skills/monopoly/scale-benchmarks+1 more

Compare with similar skills

Scale Benchmarks 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.

Scale Benchmarks compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Scale Benchmarks this skillsickn33/agentic-awesome-skills	47k	1 repos	~1.4k	Automated safety check: Pass	MIT	yesterday
Mail Timeveliovgroup/mail-time	143	—	~1k	Automated safety check: Pass	BSD-3-Clause	today
Tgf Server Devthkhxm/tgf	128	—	~1.3k	Automated safety check: Notes	MIT	2 mo ago
Commandkit Cacheneplexlabs/commandkit	165	—	~506	Automated safety check: Pass	MIT	12 days ago
Cloudrun DevelopmentTencentCloudBase/CloudBase-AI-Toolkit	1.1k	1 repos	~7.2k	Automated safety check: Pass	MIT	yesterday
Infra AuditSethGammon/Citadel	922	—	~2.1k	Automated safety check: Notes	MIT	7 days ago

Similar skills

Mail Time
veliovgroup/mail-time
A skill your agent uses when building, wiring, reviewing, or debugging MailTime and ostrio:mailer email queues for horizontally scaled Node.js, Bun, or Meteor apps.
143 GitHub stars~1k tokensUpdated today
DatabasesAuto-check passed
Tgf Server Dev
thkhxm/tgf
基于 tgf v2（github.com/thkhxm/tgf/v2）用确定性的 tgfctl 工作流创建、验证和维护 Go 游戏服务器项目。
128 GitHub stars~1.3k tokensUpdated 2 mo ago
DatabasesAuto-check: notes
Commandkit Cache
neplexlabs/commandkit
Implement deterministic caching with @commandkit/cache. An agent skill from neplexlabs/commandkit.
165 GitHub stars~506 tokensUpdated 12 days ago
DatabasesAuto-check passed
Cloudrun Development
TencentCloudBase/CloudBase-AI-Toolkit
CloudBase Run backend development rules (Function mode/Container mode).
1.1k GitHub starsUsed in 1 repo~7.2k tokens
DatabasesAuto-check passed
Infra Audit
SethGammon/Citadel
Reads docker-compose, env files, ORM configs, and connection strings to map current infrastructure.
922 GitHub stars~2.1k tokensUpdated 7 days ago
DatabasesAuto-check: notes
Bump Test Image
redis/node-redis
Official
Bump the default Redis docker test image (redislabs/client-libs-test) in the shared DEFAULTDOCKERCONFIG and the CI matrix, then force-push the bump-test-image branch and open a PR against upstream.
18k GitHub stars~1.4k tokensUpdated yesterday
DatabasesAuto-check passed

Questions about Scale Benchmarks

What does Scale Benchmarks do?

Reference document for monopoly scale-benchmarks. An agent skill from sickn33/agentic-awesome-skills. Scale Benchmarks is an agent skill from sickn33/agentic-awesome-skills. Reference document for monopoly scale-benchmarks.

When should I use Scale Benchmarks?

Scale Benchmarks fits situations like: tasks that involve Site reliability engineering.

How do I install Scale Benchmarks in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill scale-benchmarks -a claude-code`. Or copy the skill folder (skills/monopoly/scale-benchmarks in sickn33/agentic-awesome-skills) into .claude/skills/scale-benchmarks in your project. Claude Code loads it when a task matches its description.

How do I install Scale Benchmarks in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill scale-benchmarks -a codex`. Or copy the skill folder (skills/monopoly/scale-benchmarks in sickn33/agentic-awesome-skills) into .agents/skills/scale-benchmarks in your project. Codex loads it when a task matches its description.

Can I use Scale Benchmarks 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 sickn33/agentic-awesome-skills --skill scale-benchmarks -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scale-benchmarks, .gemini/skills/scale-benchmarks, .github/skills/scale-benchmarks and .opencode/skills/scale-benchmarks in your project.

What does Scale Benchmarks need to run?

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

Does Scale Benchmarks 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 Scale Benchmarks 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 Scale Benchmarks use?

Scale Benchmarks 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 Scale Benchmarks use?

About 1.4k tokens (SKILL.md is roughly 5.5k 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 Scale Benchmarks?

Skills that share tags, products or a category with Scale Benchmarks: Mail Time (veliovgroup/mail-time, 143 stars), Tgf Server Dev (thkhxm/tgf, 128 stars), Commandkit Cache (neplexlabs/commandkit, 165 stars) and Cloudrun Development (TencentCloudBase/CloudBase-AI-Toolkit, 1.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Scale Benchmarks?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,343 GitHub stars. The repository holds 1,354 skills in this directory. The repository was last updated on October 7, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Scale Benchmarks

Facts

At a glance

What it does

When your agent uses it

Example prompts

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

MONOPOLY — Scale Benchmarks & Estimation Formulas

When to Use

Quick Estimation Formulas

User → RPS Conversion

Storage Estimation

Bandwidth Estimation

Known Scale Limits of Common Technologies

Databases

Queues / Streams

Caching

Capacity Planning by User Scale

1K DAU

10K DAU

100K DAU

1M DAU

10M DAU

Common SLO Targets

Latency Budget Guidelines

Limitations

Files

Used in 1 other repository

Compare with similar skills

Similar skills

More from sickn33/agentic-awesome-skills

Related

Questions about Scale Benchmarks