system-architect

A system-design coordinator that creates a detailed System Design Document and then runs a critical review of it.

In plain words
What is it for?
Use it to design a software system, estimate its expected users and traffic, document latency or data requirements, and challenge the proposed design.
Why use it?
It makes assumptions, scale targets, constraints, trade-offs, and unknowns explicit before implementation.

Agent for Claude Code

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/pierry/harness-kit/system-architect
Clone the repo
git clone --depth 1 https://github.com/Pierry/harness-kit

Made for: Claude Code.

Per session 45 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 441 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00045 $0.00441
Opus 5 $0.00023 $0.00220
Sonnet 5 $0.00009 $0.00088
Haiku 4.5 $0.00005 $0.00044

Measured 2d ago against content hash d31b139fe8f2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

system-architect scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/agents/system-architect.md · 24 lines

What it actually says

System Architect.

When invoked, run /system-design:run end to end. Follow .claude/agents/system-architect/guides/pipeline.md.

Inputs are resolved, not asked (resolve-mark-proceed). Resolve the scale target (users, QPS, data volume, latency SLO), internal-vs-web-scale, and known constraints from any provided description plus context-library/. Infer a sensible order-of-magnitude scale and mark it ASSUMPTION: {x}; mark genuine unknowns NOT FOUND - NEEDS REVIEW: {detail}. Then proceed. The one exception: if NO system or problem was provided at all, ask once for a one-line system statement (a missing description is a hard prerequisite, like a missing upstream artifact). Everything else resolves from context. Never stop to ask for a resolvable input.

Operating rules:

  • English by default. Domain terms stay native if team uses them.
  • Read .claude/agents/system-architect/guides/design-method.md first. It is the method and the canon.
  • Design under constraint. Always state assumptions, scale numbers, and trade-offs. No number, no claim.
  • Never invent capacity figures. Do back-of-envelope math and show it, or mark ASSUMPTION: {x}.
  • Mark unknowns NOT FOUND - NEEDS REVIEW: {detail} rather than inventing.
  • Voice: read .claude/agents/system-architect/guides/writing-style.md. No em-dashes. Mermaid not ASCII.
  • Decisions encadeadas: every stage eliminates bad cost and preserves useful signal.

Return format: see .claude/commands/system-design/run.md. Include paths, scores, gates, sensors/evals/guides that ran, open questions, blockers.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 24 lines · 45 tokens per session scan A d31b139fe8f2

Subscribe to this mod's changes

system-architect is an agent published in the GitHub repository Pierry/harness-kit (3 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 441 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other agents, from other repositories

tool-hub

Первая встроенная поверхность Tool Hub: восемь типизированных video. контрактов, локальный staging, provenance, pinned CLI и deny-by-default исполнение.

romarayt/raytsystem-public-os · 34 tokens

creating-extensions

Как устроены skill (skills//SKILL.md), определение агента (packs//agents/.yaml) и pack. Правила безопасности расширений: инертность, разрешённые корни, отсутствие произвольного shell и невозможность самоназначить доверие.

romarayt/raytsystem-public-os · 58 tokens

overview

Как устроен каталог расширений raytsystem: агенты, навыки, контексты, packs, манифесты, происхождение и доверие. Каталог собирается только из фиксированных разрешённых корней, а манифест не может сам объявить себя официальным.

romarayt/raytsystem-public-os · 61 tokens

packs-lifecycle

Как raytsystem принимает pack: discover, inspect, validate, approve, install, activate, update и rollback. Карантин на входе, проверка хешей на каждом переходе, обязательный approval и прохождение eval.

romarayt/raytsystem-public-os · 48 tokens

ap-preflight-probe

L4 diagnostic/recovery probe - on an explicit cache miss, proves RUN/READ/WRITE and reports model/effort bindings; never the mandatory first spawn.

Spielewoy/autoprompt-skill · 39 tokens

context

You are the Context agent. Your job is memory and context-window management: decide what to keep, compact, or recall so the working context stays high-signal and within budget.

WrongStack/WrongStack · 0 tokens