eCan.ai CLAUDE.md

eCan.ai CLAUDE.md is an instructions file for coding agents from scszcoder/eCan.ai. It costs 3,566 tokens per session, scanned A, original, MIT.

Project instructions for scszcoder/eCan.ai that guide an agent toward careful planning, simple solutions, and narrowly scoped code changes.

In plain words
What is it for?
Use them when changing eCan.ai, especially to decide where new code belongs and how to handle unclear or potentially overcomplicated tasks.
Why use it?
They reduce assumptions, unnecessary features, and edits to the project's retired PyQt5 interface.

Instructions file

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 instructions/scszcoder/ecan.ai/claude-md
Clone the repo
git clone --depth 1 https://github.com/scszcoder/eCan.ai

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README.md
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Per session 3,566 This file is loaded in full into every session.
When invoked 3,566 The same file — it is already loaded in full.
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Fable 5 $0.03566 $0.03566
Opus 5 $0.01783 $0.01783
Sonnet 5 $0.00713 $0.00713
Haiku 4.5 $0.00357 $0.00357

Measured 4d ago against content hash fff6d477cf99, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

eCan.ai CLAUDE.md 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 4d 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.

CLAUDE.md · 208 lines

How it starts

The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

Behavioral guidelines to reduce common LLM coding mistakes. Merge with project-specific instructions as needed.

Tradeoff: These guidelines bias toward caution over speed. For trivial tasks, use judgment.

0. 废弃目录说明

gui/ 目录是废弃目录 — 这是旧的 PyQt5 GUI 的 Python 代码,现在已被 gui_v2/ (React/TypeScript) 替换。

  • 不要在 gui/ 目录添加新代码
  • 不要修改 gui/ 除非是维护废弃功能
  • 所有新开发应该在 gui_v2/ 进行

1. Think Before Coding

Don't assume. Don't hide confusion. Surface tradeoffs.

Before implementing:

  • State your assumptions explicitly. If uncertain, ask.
  • If multiple interpretations exist, present them - don't pick silently.
  • If a simpler approach exists, say so. Push back when warranted.
  • If something is unclear, stop. Name what's confusing. Ask.

2. Simplicity First

Minimum code that solves the problem. Nothing speculative.

  • No features beyond what was asked.
  • No abstractions for single-use code.
  • No "flexibility" or "configurability" that wasn't requested.
  • No error handling for impossible scenarios.
  • If you write 200 lines and it could be 50, rewrite it.

Ask yourself: "Would a senior engineer say this is overcomplicated?" If yes, simplify.

3. Surgical Changes

Touch only what you must. Clean up only your own mess.

When editing existing code:

  • Don't "improve" adjacent code, comments, or formatting.
  • Don't refactor things that aren't broken.
  • Match existing style, even if you'd do it differently.
  • If you notice unrelated dead code, mention it - don't delete it.

When your changes create orphans:

  • Remove imports/variables/functions that YOUR changes made unused.
  • Don't remove pre-existing dead code unless asked.

The test: Every changed line should trace directly to the user's request.

4. Goal-Driven Execution

Define success criteria. Loop until verified.

Transform tasks into verifiable goals:

  • "Add validation" → "Write tests for invalid inputs, then make them pass"
  • "Fix the bug" → "Write a test that reproduces it, then make it pass"
  • "Refactor X" → "Ensure tests pass before and after"

Read the full file on GitHub · 208 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. 4d ago First seen · 208 lines · 3,566 tokens per session scan A fff6d477cf99

Subscribe to this mod's changes

eCan.ai CLAUDE.md is an instructions file published in the GitHub repository scszcoder/eCan.ai (17 stars, last pushed 4d ago), licensed MIT. It adds 3,566 tokens to every session, about $0.0178 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 2026-08-30.