aits-systemic

aits-systemic is an agent for Claude Code from fabiolalli/aits-agents. It costs 77 tokens per session (2,806 once invoked), scanned B, original, MIT.

An agent for decisions involving connected parts, feedback loops, or unintended side effects. It represents how resources or conditions build up and move through a system, then looks for influential intervention points and chains of effects.

In plain words
What is it for?
Use it to map complex relationships, locate places where a small action may have a large effect, and trace possible knock-on consequences.
Why use it?
It helps expose consequences that are easy to miss when each part is considered separately. This is useful when one change can trigger effects elsewhere in the system.

Agent for Claude Code

Written for Claude Code: $CLAUDE_PLUGIN_ROOT} variable. Also seen: model in frontmatter; reads .claude/ paths.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the aits plugin — 4 commands, 12 agents, 3 hooks, 1 MCP server shipped together

Good fit Use it to map complex relationships, locate places where a small action may have a large effect, and trace possible knock-on consequences.

Compare 6 agents from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add fabiolalli/aits-agents
Claude Code
/plugin install aits

Made for: Claude Code.

Or install aits, the plugin that ships this one along with the rest of its 4 commands, 12 agents, 3 hooks, 1 MCP server.

Wrote 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.

agentmods badge for aits-systemic

README.md
[![agentmods](https://agentmods.dev/badge/agents/fabiolalli/aits-agents/aits-systemic/github.svg)](https://agentmods.dev/agents/fabiolalli/aits-agents/aits-systemic)
Your own site
<a href="https://agentmods.dev/agents/fabiolalli/aits-agents/aits-systemic"><img src="https://agentmods.dev/badge/agents/fabiolalli/aits-agents/aits-systemic/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.

agentmods 80×15 button for aits-systemic

Your own site · 80×15
<a href="https://agentmods.dev/agents/fabiolalli/aits-agents/aits-systemic"><img src="https://agentmods.dev/badge/agents/fabiolalli/aits-agents/aits-systemic.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 77 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,806 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00077 $0.02806
Opus 5.5 $0.00031 $0.01122
Sonnet 5.5 $0.00015 $0.00561
Haiku 4.5 $0.00008 $0.00281

Measured 3d ago against content hash 4afce6083f2a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade B, and why

aits-systemic scanned grade B with 1 finding 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.

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

3. If both are empty, look for the folder once with `ls -d ~/.claude/plugins/cache/*/aits/*/ ~/.claude/plugins/marketplaces/*/plugins/aits/ 2>/dev/null | head -1`, and use `$HOME/.claude/` only if nothing is found (files
plugins/aits/agents/aits-systemic.md · 237 lines

How it starts

The opening of the file, as written. The whole thing — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Path Resolution (plugin install)

Files referenced as references/..., playbooks/..., graphs/... or schemas/... are relative to the plugin root, not to the current project.

  1. At the start of your work, run once echo "${AITS_PLUGIN_ROOT:-$CLAUDE_PLUGIN_ROOT}" and cache the value. The plugin sets AITS_PLUGIN_ROOT when the session starts.
  2. Prepend that root to any references/..., playbooks/..., graphs/... or schemas/... path before reading it.
  3. If both are empty, look for the folder once with ls -d ~/.claude/plugins/cache/*/aits/*/ ~/.claude/plugins/marketplaces/*/plugins/aits/ 2>/dev/null | head -1, and use $HOME/.claude/ only if nothing is found (files copied by hand). Do not search the whole disk.

Project-local paths such as .aits/ stay relative to the current project. The AITS engine is available as MCP tools with the aits_ prefix.

Systemic Agent (🌐) — AITS

You are the Systemic Agent of AITS — the systems thinker of the decision process. You map the decision's context as a system of stocks, flows, and feedback loops. You identify leverage points where small interventions produce disproportionate effects. You surface the second-order consequences that linear analysis misses.

Cognitive Mission

Reveal the system structure beneath the decision. Identify feedback loops (reinforcing and balancing) that will amplify or dampen the decision's effects. Locate leverage points where change propagates. Trace cascade paths of second-order consequences. Distinguish local optimization from systemic health.

Role in the System

  • Activated for complex interdependencies — M&A, policy changes, incentive structures, platform dynamics
  • Activated in specific playbooks — ma-due-diligence, risk-assessment always include Systemic
  • Feeds Critical — feedback loops often reveal hidden risks
  • Feeds Optimizer — leverage points are high-ROI opportunities
  • Feeds Predictive — loops determine how the system evolves over time
  • Conflict with Optimizer — local optimization vs systemic health; arbitrated by Predictive

Read the full file on GitHub · 237 lines

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 Changed · +42 lines · -125 tokens per session scan A → B 4afce6083f2a
  2. 2mo ago First seen · 195 lines · 202 tokens per session scan A 9234308f097e

Subscribe to this mod's changes

aits-systemic is an agent published in the GitHub repository fabiolalli/aits-agents (10 stars, last pushed 3d ago), licensed MIT. It adds 77 tokens to every session and 2,806 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

aits-systemic compared with agents from other repositories

aits-systemic next to 6 agents from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
aits-systemicfabiolalli/aits-agentsAgent103d agoMITB77Claude Code
context-architectfabioc-aloha/Alex_Skill_MallAgent5yesterdayMITA21Claude Code
systematic-debuggingfabioc-aloha/Alex_Skill_MallAgent5yesterdayMITA28Claude Code
domain_reviewer_agentfabioc-aloha/Alex_Skill_MallAgent5yesterdayMITA22Claude Code
methodology_reviewer_agentfabioc-aloha/Alex_Skill_MallAgent5yesterdayMITA23Claude Code
editorial_synthesizer_agentfabioc-aloha/Alex_Skill_MallAgent5yesterdayMITA23Claude Code
perspective_reviewer_agentfabioc-aloha/Alex_Skill_MallAgent5yesterdayMITA22Claude Code