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 emaballarin/ccplugins --skill pdf-exploregit clone --depth 1 https://github.com/emaballarin/ccpluginsWrote 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/emaballarin/ccplugins/pdf-explore)<a href="https://agentmods.dev/skills/emaballarin/ccplugins/pdf-explore"><img src="https://agentmods.dev/badge/skills/emaballarin/ccplugins/pdf-explore/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/emaballarin/ccplugins/pdf-explore"><img src="https://agentmods.dev/badge/skills/emaballarin/ccplugins/pdf-explore.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00263 | $0.05510 |
| Opus 5.5 | $0.00105 | $0.02204 |
| Sonnet 5.5 | $0.00053 | $0.01102 |
| Haiku 4.5 | $0.00026 | $0.00551 |
Grade A, and why
pdf-explore 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 15d 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 — 421 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PDF Explore — navigate a PDF too big to embed
The built-in Read(file_path=..., pages=[...]) attaches PDF pages as vision
blocks — capped at ~20 pages/turn and dropped from context after one
turn, so multi-section synthesis turns into re-reading the same pages over
and over. And when the answer is "every page" (list all datasets / citations
/ figures mentioned anywhere), reading the whole document page-by-page is the
expensive way to get it.
This skill parses the PDF once into persistent per-page text, and — for whole-document work — runs one cheap model call per page (or per batch) in parallel via subagents, so the page text lives in files and subagent contexts, never in yours. You load only what matters, or sweep every page without putting the pages in your own context at all.
Read(pages=...) and this skill are complementary: use Read(pages=...)
for a one-off look at 1–4 pages you will quote in your very next reply; use
this skill for persistent text, multi-section synthesis, whole-doc sweeps,
and structured extraction.
Loading the kernel
The helpers live in kernel.py next to this file. It is not auto-injected
— import it by path in a Bash python heredoc (zero import-time side effects,
all heavy imports are lazy):
python3 - <<'PY'
import importlib.util
K = "${CLAUDE_SKILL_DIR}/kernel.py"
spec = importlib.util.spec_from_file_location("pdf_kernel", K)
k = importlib.util.module_from_spec(spec)
spec.loader.exec_module(k)
for e in k.pdf_outline("paper.pdf"):
print(f"p{e['page']:>3} {' ' * (e['level'] - 1)}{e['heading']}")
PY
Every recipe below assumes k is loaded this way. Each python invocation is
a fresh process — the in-memory page cache does not survive between them,
but page renders are cached on disk and re-extracting the text layer is cheap,
so re-parsing the same file in a later call is fast.
Invocation. The recipes below all open with python3 - <<'PY', which is
right when the deps are importable from your python3. If they aren't — or you
would rather not install anything — prefix with uv, which fetches them into a
throwaway env:
What ships with it
1 file 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.
- 15d ago Changed · +1 lines · -1 tokens per session f0ffbea243ac
- 1mo ago First seen · 420 lines · 264 tokens per session scan A 88fad2b51582
pdf-explore is a skill published in the GitHub repository emaballarin/ccplugins (4 stars, last pushed 10d ago), licensed MIT. It adds 263 tokens to every session and 5,510 once invoked, about $0.0011 per session on Opus 5.5. 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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