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/cxcscmu/skilllearnbench/pdf-calendar-extractornpx skills add cxcscmu/SkillLearnBench --skill pdf-calendar-extractorgit clone --depth 1 https://github.com/cxcscmu/SkillLearnBenchWrote 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/cxcscmu/skilllearnbench/pdf-calendar-extractor)<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/pdf-calendar-extractor"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/pdf-calendar-extractor.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00025 | $0.00357 |
| Opus 5 | $0.00013 | $0.00179 |
| Sonnet 5 | $0.00005 | $0.00071 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
pdf-calendar-extractor 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 yesterday.
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.
What it actually says
PDF Calendar Extractor
This skill provides a way to extract text elements and graphical shapes (like rectangles) from a PDF, including their positions and color properties. This is useful for processing visual calendars where appointments are represented by colored blocks.
Requirements
pdfplumber
Example Usage: Extract Rectangles and Text
import pdfplumber
def extract_calendar_data(pdf_path):
with pdfplumber.open(pdf_path) as pdf:
page = pdf.pages[0]
# Extract text with positions
text_elements = page.extract_text_full() # or extract_words()
words = page.extract_words()
# Extract rectangles (appointments)
rects = page.rects
# For each rectangle, you can get:
# rect['top'], rect['bottom'], rect['left'], rect['right']
# rect['non_stroking_color'] (fill color)
return words, rects
# Identifying 'blue' blocks
# Blue in RGB is often (0, 0, 1) or a similar variation.
# pdfplumber color formats can vary (RGB, CMYK, etc.)
Tips for Measuring Time
If the calendar has horizontal lines representing 15-minute intervals:
- Identify all horizontal lines (
page.lineswherey0 == y1). - Sort them by vertical position (
top). - Calculate the height of a 15-minute block.
- Map rectangle
topandbottomto specific times based on their position relative to the lines.
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.
- yesterday First seen · 46 lines · 25 tokens per session scan A 8bf106b5bc0e
pdf-calendar-extractor is a skill published in the GitHub repository cxcscmu/SkillLearnBench (83 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 357 once invoked, about $0.0001 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 2026-09-03.
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