agentic-systems

A design and delivery helper for systems that use language models and AI agents. It covers work such as retrieval-augmented generation, where a model uses retrieved documents, tool use, workflow coordination, monitoring, security, cost, and testing.

In plain words
What is it for?
Use it to design, scaffold, evaluate, or deliver language-model and agent systems, including search-based answers, tool calling, orchestration, observability, provider selection, and security.
Why use it?
It helps organise the many engineering decisions involved in building and evaluating AI-powered systems.

Skill for Claude CodeCodex

Part of the development-system plugin — 6 skills, 1 hook, 7 plugins shipped together

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 skills/jwilger/ai-plugins/agentic-systems
Any agent
npx skills add jwilger/ai-plugins --skill agentic-systems
Clone the repo
git clone --depth 1 https://github.com/jwilger/ai-plugins

Made for: Claude Code, Codex.

Or install development-system, the plugin that ships this one along with the rest of its 6 skills, 1 hook, 7 plugins.

Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 526 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00066 $0.00526
Opus 5 $0.00033 $0.00263
Sonnet 5 $0.00013 $0.00105
Haiku 4.5 $0.00007 $0.00053

Measured 3d ago against content hash 1ba635d950dd, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agentic-systems 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 3d 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.

plugins/development-system/skills/agentic-systems/SKILL.md · 45 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

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.

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. 3d ago First seen · 45 lines · 66 tokens per session scan A 1ba635d950dd

Subscribe to this mod's changes

agentic-systems is a skill published in the GitHub repository jwilger/ai-plugins (4 stars, last pushed 3d ago), with no licence file. It adds 66 tokens to every session and 526 once invoked, about $0.0003 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.

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