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.
npx skills add xuanhieu2611/build-your-own-agents-skill --skill production-agent-architecturegit clone --depth 1 https://github.com/xuanhieu2611/build-your-own-agents-skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/xuanhieu2611/build-your-own-agents-skill/production-agent-architecture)<a href="https://agentmods.dev/skills/xuanhieu2611/build-your-own-agents-skill/production-agent-architecture"><img src="https://agentmods.dev/badge/skills/xuanhieu2611/build-your-own-agents-skill/production-agent-architecture/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/xuanhieu2611/build-your-own-agents-skill/production-agent-architecture"><img src="https://agentmods.dev/badge/skills/xuanhieu2611/build-your-own-agents-skill/production-agent-architecture.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00034 | $0.00448 |
| Opus 5.5 | $0.00014 | $0.00179 |
| Sonnet 5.5 | $0.00007 | $0.00090 |
| Haiku 4.5 | $0.00003 | $0.00045 |
Grade A, and why
production-agent-architecture 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 1mo 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.
What it actually says
Production Agent Architecture
When To Use This Skill
Use this skill when the task is to:
- design a new AI agent
- turn a chatbot idea into a real agent system
- hand off an agent build to developers or another AI coding agent
- adapt coding-agent architecture patterns to another domain
Core Rule
Do not design the system as a one-shot chatbot unless the user explicitly asks for that.
Default to a loop-based runtime with:
- controller loop
- context builder
- tool registry
- tool executor
- session state
- permissions and approvals
- observability
- evaluation
- reliability rules
- rollout phases
Design Workflow
- define the user goal and success condition
- define the controller loop
- define 2 to 5 domain tools
- define context inputs
- define session state
- define permissions and approval rules
- define observability minimums
- define evaluation plan
- define reliability and retry rules
- define rollout phases
Required Output
Always produce all of the following:
# Agent Build Spec
## Domain
## User goal
## Success condition
## Core workflow
## Controller loop
## Context inputs
## Tools
## Session state
## Permissions and approvals
## Stop conditions
## Observability
## Evaluation
## Reliability and failure handling
## Rollout phases
## Future extensions
After the spec, also produce:
- controller loop pseudocode
- tool contract table with input, output, side effects, timeout, and permission level
- session state schema
- approval matrix
- failure and retry strategy
- minimum logs and metrics
Guardrails
- separate tool schemas from executors
- treat permissions as runtime policy, not prompt text
- make approval flows explicit
- do not pretend a vague idea is production-ready
- explain the design plainly if the user is learning
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 78 lines · 34 tokens per session scan A e757e34dd19c
production-agent-architecture is a skill published in the GitHub repository xuanhieu2611/build-your-own-agents-skill (23 stars, last pushed 6mo ago), licensed MIT. It adds 34 tokens to every session and 448 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
Other skills, from other repositories
postgresql-table-design
Use this skill when designing or reviewing a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features.
istio-traffic-management
Configure Istio traffic management including routing, load balancing, circuit breakers, and canary deployments. Use when implementing service mesh traffic policies, progressive delivery, or resilience patterns.
event-store-design
Design and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns.
workflow-orchestration-patterns
Design durable workflows with Temporal for distributed systems. Covers workflow vs activity separation, saga patterns, state management, and determinism constraints. Use when building long-running processes, distributed transactions, or microservice orchestration.
explain-for
Explain a topic, code, error or design decision for one named audience (a 5-year-old, a manager, a designer, a grad student, a parent). Resolves who it is for, pins the ground truth first, then tunes vocabulary, analogy, tone and depth to that audience. Use when an audience is named.
papyrus-latex-suggestions
Propose inline replacement text (old -> new) as accept/reject suggestions, LaTeX 'suggesting mode' / track changes, rendered in the PDF. Use when the author wants concrete edit proposals to accept or reject. For remarks ABOUT the text rather than replacements, use papyrus-latex-comments.