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.
npx skills add endearqb/endearqb-skills --skill endearqb-wechat-file-organizergit clone --depth 1 https://github.com/endearqb/endearqb-skillsWrote 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.
[](https://agentmods.dev/skills/endearqb/endearqb-skills/endearqb-wechat-file-organizer)<a href="https://agentmods.dev/skills/endearqb/endearqb-skills/endearqb-wechat-file-organizer"><img src="https://agentmods.dev/badge/skills/endearqb/endearqb-skills/endearqb-wechat-file-organizer/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.
<a href="https://agentmods.dev/skills/endearqb/endearqb-skills/endearqb-wechat-file-organizer"><img src="https://agentmods.dev/badge/skills/endearqb/endearqb-skills/endearqb-wechat-file-organizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00147 | $0.03286 |
| Opus 5 | $0.00073 | $0.01643 |
| Sonnet 5 | $0.00029 | $0.00657 |
| Haiku 4.5 | $0.00015 | $0.00329 |
Grade A, and why
wechat-file-organizer 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 304 lines — stays where its author put it; the contents beside it link to each section on GitHub.
微信文件整理技能
功能概述
-
自动检测微信文件存储路径（含非默认迁移路径）
-
识别微信重复文件：普通重复 + 括号序号命名（
文件(1).pdf、文件(2).pdf） -
重复文件移入回收站（非永久删除，可恢复）
-
按月份+类型分类，复制到用户指定目录
-
支持
--since时间范围过滤（如只整理最近3个月） -
两阶段确认：dry-run 预览 → 用户确认 → 执行
执行流程
第一步：检测 / 读取配置
python scripts/detect_wechat_dir.py
脚本会输出当前状态，Agent 根据结果执行不同的后续操作：
情况 A：已有配置文件（status = found_config）
脚本展示已保存的源目录、目标目录、上次整理时间。
-
询问用户：「沿用上次配置吗？（直接回复"是"，或输入"reset"重新配置）」
-
用户确认沿用 → 直接进入第三步
-
用户说 reset → 进入第二步重新配置
情况 B：首次运行 / 检测到候选路径（status = found_single / found_multiple）
-
若只有一个候选，向用户展示并询问确认：「检测到微信文件目录：[路径]，使用这个目录吗？」
-
若有多个候选，列出编号让用户选择
-
用户确认后 → 进入第二步
情况 C：未检测到任何路径（status = not_found）
-
请用户手动输入源目录路径
-
确认路径存在后 → 进入第二步
配置文件位置：skill 根目录下的 config.json
（与 SKILL.md 同级，即 .agents/skills/wechat-file-organizer/config.json）
操作日志同样保存在 skill 根目录：organizer_log.txt
第二步：询问并保存配置
仅在以下情况执行本步骤：首次运行、reset、或配置文件中缺少某项字段。
需要收集并确认的字段：
-
source_dir（微信源目录）
-
来自第一步检测结果或用户手动输入
-
必须确认路径实际存在
-
-
dest_dir（目标保存目录）
-
配置中无此字段 → 必须询问用户，提示默认值
%USERPROFILE%\Documents\微信整理 -
用户可直接回车接受默认，或输入自定义路径
-
-
mode（分类方式，默认 month_type）
-
month_type：按月份+类型，如2024-03/图片/ -
type_only：仅按类型，如图片/ -
month_only：仅按月份，如2024-03/ -
可以询问，也可以直接使用默认值，无需强制询问
-
收集完成后，用以下格式写入配置文件：
import json
from pathlib import Path
config = {
"source_dir": "<用户确认的源目录>",
"dest_dir": "<用户确认的目标目录>",
"mode": "month_type",
"last_run": None
}
# 配置文件放在 skill 根目录（与 SKILL.md 同级）
config_path = Path(__file__).parent.parent / "config.json"
with open(config_path, "w", encoding="utf-8") as f:
json.dump(config, f, ensure_ascii=False, indent=2)
print(f"✅ 配置已保存到：{config_path}")
保存后告知用户配置文件的完整路径。
每次整理前：确认目标目录
无论是否已有配置，每次执行整理操作前，都必须向用户展示目标目录并明确确认：
What ships with it
4 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.
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.
- 12d ago First seen · 304 lines · 147 tokens per session scan A c99863ea5a7c
wechat-file-organizer is a skill published in the GitHub repository endearqb/endearqb-skills (19 stars, last pushed 9d ago), licensed MIT. It adds 147 tokens to every session and 3,286 once invoked, about $0.0007 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.
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