faircode-ai-copilot

A guide for adding Claude-based AI features to custom Frappe or ERPNext applications. Frappe is the web framework behind ERPNext, a business-management system.

In plain words
What is it for?
Use it to build features such as summarising, email drafting, or classification with the Claude API in Frappe or ERPNext.
Why use it?
It addresses the setup, cost, caching, and background-processing decisions involved in adding AI to these applications.

Skill for Claude CodeCodex

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/nipunfaircode/faircode-frappe/faircode-ai-copilot
Any agent
npx skills add nipunFaircode/faircode-frappe --skill faircode-ai-copilot
Clone the repo
git clone --depth 1 https://github.com/nipunFaircode/faircode-frappe

Made for: Claude Code, Codex.

Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,728 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 $0.00093 $0.01728
Opus 5 $0.00046 $0.00864
Sonnet 5 $0.00019 $0.00346
Haiku 4.5 $0.00009 $0.00173

Measured 2d ago against content hash 0d65325c2154, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

faircode-ai-copilot 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.

skills/faircode-ai-copilot/SKILL.md · 213 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. 2d ago First seen · 213 lines · 93 tokens per session scan A 0d65325c2154

Subscribe to this mod's changes

faircode-ai-copilot is a skill published in the GitHub repository nipunFaircode/faircode-frappe (2 stars, last pushed 2mo ago), with no licence file. It adds 93 tokens to every session and 1,728 once invoked, about $0.0005 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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