fcis-analyzer

fcis-analyzer is an agent for Claude Code from zby/llm-do. It costs 53 tokens per session (1,983 once invoked), scanned A, original, no licence file.

A code-review agent for Python that checks whether business rules are separated from input, output, and other side effects. Functional Core, Imperative Shell is a design approach that keeps calculations separate from operations such as file or network access.

In plain words
What is it for?
Use it to review Python architecture, find business logic mixed with I/O, and identify side effects inside functions that should be easier to test.
Why use it?
It reveals code that mixes unrelated responsibilities, which can make testing and maintenance harder.

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/zby/llm-do/fcis-analyzer
Clone the repo
git clone --depth 1 https://github.com/zby/llm-do

Made for: Claude Code.

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 fcis-analyzer

README.md
[![agentmods](https://agentmods.dev/badge/agents/zby/llm-do/fcis-analyzer.svg)](https://agentmods.dev/agents/zby/llm-do/fcis-analyzer)
Your own site
<a href="https://agentmods.dev/agents/zby/llm-do/fcis-analyzer"><img src="https://agentmods.dev/badge/agents/zby/llm-do/fcis-analyzer.svg" alt="Measured on agentmods" height="20"></a>
Per session 53 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,983 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. 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 $0.00053 $0.01983
Opus 5 $0.00026 $0.00992
Sonnet 5 $0.00011 $0.00397
Haiku 4.5 $0.00005 $0.00198

Measured 3d ago against content hash d726e979be8c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

fcis-analyzer scanned grade A 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- `requests.get()`, `requests.post()`, etc.
.claude/skills/decomplect-py/agents/fcis-analyzer.md · 274 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

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 · 274 lines · 53 tokens per session scan A d726e979be8c

Subscribe to this mod's changes

fcis-analyzer is an agent published in the GitHub repository zby/llm-do (20 stars, last pushed 6mo ago), with no licence file. It adds 53 tokens to every session and 1,983 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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