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Agent skill

System Design Estimation

by HoangNguyen0403 in HoangNguyen0403/agent-skills-standard

Compute defensible capacity numbers before architecture: average and peak QPS, storage growth, bandwidth, working-set memory, latency and availability budgets.

MITAuto-check passedDevelopment

Install System Design Estimation

skills CLI
$ npx skills add HoangNguyen0403/agent-skills-standard --skill system-design-estimation -a claude-code

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

GitHub CLI
$ gh skill install HoangNguyen0403/agent-skills-standard system-design-estimation --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/HoangNguyen0403/agent-skills-standard.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/system-design/system-design-estimation .claude/skills/system-design-estimation && 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
system-design-estimation
GitHub stars
572
Token cost
~922 tokens
SKILL.md length
463 words
Files
3 (incl. references)
Skills in repo
211
Repo updated
First seen
Licence
MIT

At a glance

Compute defensible capacity numbers before architecture: average and peak QPS, storage growth, bandwidth, working-set memory, latency and availability budgets.

  • Works in 5 steps: Round every input to one significant… → Compute average, then peak, then… → Compare each result to a known ceiling… → …
  • Sizing a service
  • SKILL.md covers Priority: P1 (HIGH), Core Formulas, Method and Cost, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

System Design Estimation is an agent skill from HoangNguyen0403/agent-skills-standard. Compute defensible capacity numbers before architecture: average and peak QPS, storage growth, bandwidth, working-set memory, latency and availability budgets. Use when sizing a service, provisioning infrastructure, or checking that a design survives peak load.

Its SKILL.md is about 920 tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `evals/evals.json` and `references/estimation-numbers.md`).

It sits in Development, covering Software architecture. The repository describes itself as: A collection of Agent Skills Standard and Best Practice for Programming Languages, Frameworks that help our AI Agent follow best practies on frameworks and programming laguages. The licence is MIT.

When your agent uses it

  • Sizing a service
  • Provisioning infrastructure
  • Checking that a design survives peak load

Example prompts

  • “/system-design-estimation”

Workflow steps

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

  1. Round every input to one significant figure. Precision here is false precision.
  2. Compute average, then peak, then storage, then bandwidth, then memory.
  3. Compare each result to a known ceiling from estimation numbers: single-node QPS, disk IOPS, NIC throughput, RAM per instance.
  4. Name the shaping quantity - the first number that breaks a single-node ceiling. It dictates the first component added in high-level design.
  5. Restate every assumed input beside the result so a wrong assumption is visible, not buried.

What it can do on your machine

Read from SKILL.md and the folder at commit b529c2d. 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

System Design Estimation loads about 922 tokens when it runs, and up to ~1.7k if it reads all its reference files. Until then it costs about 72 tokens; SKILL.md has 463 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~72
When it runs · the whole SKILL.md, loaded when a task matches
~922
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.7k

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 HoangNguyen0403/agent-skills-standard at commit b529c2d, republished under its MIT licence (© HoangNguyen0403). 463 words, ~922 tokens.

Download SKILL.mdSave it as .claude/skills/system-design-estimation/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
system-design-estimation
description
Compute defensible capacity numbers before architecture: average and peak QPS, storage growth, bandwidth, working-set memory, latency and availability budgets. Use when sizing a service, provisioning infrastructure, or checking that a design survives peak load.

Capacity Estimation

Priority: P1 (HIGH)

Estimate before you architect. One order of magnitude decides cache, shard, and queue choices.

Core Formulas

  • average QPS = DAU x actions per user per day / 86,400
  • peak QPS = average QPS x peak factor (default 5x; 20-100x for flash sale, ticket drop, or scheduled push)
  • storage per year = writes per day x record size x 365 x replication factor
  • bandwidth = QPS x payload size (compute ingress and egress separately)
  • working set = hot records x record size, where hot is typically 20% of data serving 80% of reads
  • connections = concurrent users x connections per user; compare against pool and file-descriptor limits

Method

  1. Round every input to one significant figure. Precision here is false precision.
  2. Compute average, then peak, then storage, then bandwidth, then memory.
  3. Compare each result to a known ceiling from estimation numbers: single-node QPS, disk IOPS, NIC throughput, RAM per instance.
  4. Name the shaping quantity - the first number that breaks a single-node ceiling. It dictates the first component added in high-level design.
  5. Restate every assumed input beside the result so a wrong assumption is visible, not buried.

Cost

  • Convert the sized capacity into monthly spend before recommending it: compute, storage plus egress, managed-service premiums, and the multiplier any redundancy applies.
  • Cost is a design constraint, not an afterthought. A topology the budget cannot hold is not a design, it is a proposal to be rejected later.
  • State cost per unit of value where it clarifies: cost per 1k requests, per GB retained, per nine of availability added.
Show full SKILL.md (206 more words)Show less

Latency Budget

  • Build the p95 budget as a sum of hops; every remote call spends from one fixed budget.
  • Use order-of-magnitude anchors: memory 100ns, SSD read 100us, same-DC round trip 500us, cross-region round trip 100ms+.
  • A synchronous fan-out of N calls costs the slowest call, not the average. Budget with p99, not the mean.

Availability Math

  • Serial dependencies multiply: three 99.9% services in one path yield 99.7%.
  • Redundant replicas add nines only when failure modes are independent; a shared store or config plane cancels the gain.
  • Convert the target into an error budget in minutes per month before promising it.

Anti-Patterns

  • No design before numbers: never pick a database or cache before QPS and storage exist.
  • No average-only sizing: capacity is provisioned for peak, cost is modeled on average.
  • No hidden units: state units and time windows on every number (QPS, GB/day, GB/year).
  • No unverified precision: do not report 4,873 QPS from an assumed DAU; report ~5k QPS.

Verify

  • Average and peak QPS both stated, with the peak factor named
  • Storage projected over the retention window including replication
  • Shaping quantity identified and mapped to a design consequence
  • Every assumed input labeled beside the result

References

  • Estimation Numbers - powers of two, latency table, single-node ceilings, worked examples

© HoangNguyen0403, 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 2 other files (references) in skills/system-design/system-design-estimation of HoangNguyen0403/agent-skills-standard.

  • SKILL.md
  • evals/evals.json
  • references/estimation-numbers.md

Open the folder on GitHubat commit b529c2d

Compare with similar skills

System Design Estimation 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.

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Backend Code Reviewlanggenius/dify158k—~676Automated safety check: PassCustom licence
Dark Architecture Diagram BuilderCocoon-AI/architecture-diagram-generator7.4k1 repos~2.1kAutomated safety check: PassMIT
SVG Diagram GeneratorJimLiu/baoyu-skills27k1 repos~3.1kAutomated safety check: PassMIT

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Categories

Questions about System Design Estimation

What does System Design Estimation do?

Compute defensible capacity numbers before architecture: average and peak QPS, storage growth, bandwidth, working-set memory, latency and availability budgets. System Design Estimation is an agent skill from HoangNguyen0403/agent-skills-standard. Compute defensible capacity numbers before architecture: average and peak QPS, storage growth, bandwidth, working-set memory, latency and availability budgets.

When should I use System Design Estimation?

System Design Estimation fits situations like: sizing a service; provisioning infrastructure; checking that a design survives peak load.

How do I install System Design Estimation in Claude Code?

Run `npx skills add HoangNguyen0403/agent-skills-standard --skill system-design-estimation -a claude-code`. Or copy the skill folder (skills/system-design/system-design-estimation in HoangNguyen0403/agent-skills-standard) into .claude/skills/system-design-estimation in your project. Claude Code loads it when a task matches its description.

How do I install System Design Estimation in Codex?

Run `npx skills add HoangNguyen0403/agent-skills-standard --skill system-design-estimation -a codex`. Or copy the skill folder (skills/system-design/system-design-estimation in HoangNguyen0403/agent-skills-standard) into .agents/skills/system-design-estimation in your project. Codex loads it when a task matches its description.

Can I use System Design Estimation 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 HoangNguyen0403/agent-skills-standard --skill system-design-estimation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/system-design-estimation, .gemini/skills/system-design-estimation, .github/skills/system-design-estimation and .opencode/skills/system-design-estimation in your project.

What does System Design Estimation need to run?

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

Does System Design Estimation 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 System Design Estimation 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 System Design Estimation use?

System Design Estimation 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 System Design Estimation use?

About 922 tokens (SKILL.md is roughly 3.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 742 tokens, read only when the agent opens those files.

What are the alternatives to System Design Estimation?

Skills that share tags, products or a category with System Design Estimation: Archify Diagrams (tt-a1i/archify, 82k stars), Electron Multi-Process Architecture (iOfficeAI/AionUi, 33k stars), Backend Code Review (langgenius/dify, 158k stars) and Dark Architecture Diagram Builder (Cocoon-AI/architecture-diagram-generator, 7.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains System Design Estimation?

HoangNguyen0403 (a GitHub user) maintains it in HoangNguyen0403/agent-skills-standard, which has 572 GitHub stars. The repository holds 211 skills in this directory. The repository was last updated on October 9, 2026.

Source: HoangNguyen0403/agent-skills-standard on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.