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 agentmods add skills/midnightdarling/collate/setupnpx skills add MidnightDarling/collate --skill setupgit clone --depth 1 https://github.com/MidnightDarling/collateWhat 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 | $0.00156 | $0.02214 |
| Opus 5 | $0.00078 | $0.01107 |
| Sonnet 5 | $0.00031 | $0.00443 |
| Haiku 4.5 | $0.00016 | $0.00221 |
Grade A, and why
setup scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)" How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
首次配置 — 环境初始化指南
Task
用户通常使用 Mac 处理历史文献扫描件(繁体古籍、民国排印本、现代简体论文),并非都具备技术背景。本 skill 的目标是在一次会话内完成三件事:
- 建立本插件的 Python 运行环境(3.9+,opencv、pillow、poppler 等依赖)
- 预装并预热 MinerU 本地 CLI(默认路径);或按需启用百度 OCR / MinerU 云 API 兼容分支
- 通过一次探活确认引擎可用
任一步失败时必须显性终止,不要跳过或静默兜底。
Process
Step 1:确认用户环境
首先确认:
- 用户是否用过命令行 / 终端?不熟悉终端的用户需要逐条解释命令含义。
- 默认走本地 MinerU CLI(无需账号、不上传、首次装机约 10 分钟、之后每份 PDF 约 90 秒)。
- 仅在用户明确表示"已有百度 OCR key 想复用"或"需要 MinerU 云 API"时,改走 Step 4A / 兼容分支,并说明这两条路径已非默认。
Step 2:检查 Python(Mac)
python3 --version
为什么要这步:新 Mac 预装的 Python 可能是 3.8 或更旧,跑 PyPDF2 会报奇怪的错。
- 版本 ≥ 3.9 → 直接下一步
- 版本 < 3.9 或报
command not found→ 让用户跑brew install [email protected](如果没装 Homebrew 先跑下面这句)
Homebrew 未安装时先装:
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
Homebrew 是 macOS 的包管理器,后续所有系统级依赖都通过它安装。
Step 3:装所有依赖(一条命令)
brew install poppler
pip3 install -U -r "${CLAUDE_PLUGIN_ROOT}/requirements.txt"
requirements.txt 列了两组东西:
- 经典管道:
opencv-python/pillow/pdf2image/PyPDF2/python-docx等——prep-scan / preview / to-docx / mp-format 用 - MinerU 本地管道:
mineru[pipeline]+torch+torchvision+shapely+scikit-image——ocr-run 的默认路径用
整个 pip 过程约 5 分钟(包含 ~1 GB 的 torch)。如果 pip 报
externally-managed-environment(Homebrew Python 常见),加 --user:
pip3 install --user -U -r "${CLAUDE_PLUGIN_ROOT}/requirements.txt"
验证:
python3 -c "import cv2, PIL, requests, dotenv, markdown, PyPDF2, pdf2image, bs4, docx, yaml, opencc, mineru, torch, torchvision; print('依赖齐全')"
which mineru
第二行应该打印 mineru 的路径(说明 CLI 装上了)。输出「依赖齐全」才算过。
Step 3.5:预热 MinerU 模型(一次性)
第一次跑 mineru 会下载 ~2–3 GB 模型到 ~/.cache/huggingface/hub/。
在正式 OCR 一份 PDF 前让它先下好,省得第一次跑 PDF 时卡住。
让用户拿一份任意的小 PDF(一两页即可,扫描或文字层都行)当 probe; 仓库本身不附 sample PDF,避免把额外二进制塞进 git。
先把用户提供的 PDF 绝对路径赋给 USER_PROBE_PDF,再运行:
# 1) 把用户的 probe PDF 路径填进来(绝对路径,含空格请用引号)
USER_PROBE_PDF="/Users/<name>/Downloads/probe.pdf"
# 2) 用该 probe PDF 触发 MinerU 模型下载,跑完立刻退出
TMP=$(mktemp -d)
mineru -p "$USER_PROBE_PDF" -o "$TMP" -b pipeline -m auto -l ch
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.
- 2d ago First seen · 196 lines · 156 tokens per session scan A 2987cdc5cbca
setup is a skill published in the GitHub repository MidnightDarling/collate (6 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 156 tokens to every session and 2,214 once invoked, about $0.0008 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 2026-08-31.
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