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 bitsky-tech/bridgic-agent --skill pdfgit clone --depth 1 https://github.com/bitsky-tech/bridgic-agentWrote 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/bitsky-tech/bridgic-agent/pdf)<a href="https://agentmods.dev/skills/bitsky-tech/bridgic-agent/pdf"><img src="https://agentmods.dev/badge/skills/bitsky-tech/bridgic-agent/pdf/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/bitsky-tech/bridgic-agent/pdf"><img src="https://agentmods.dev/badge/skills/bitsky-tech/bridgic-agent/pdf.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 | $0.00092 | $0.02082 |
| Opus 5.5 | $0.00037 | $0.00833 |
| Sonnet 5.5 | $0.00018 | $0.00416 |
| Haiku 4.5 | $0.00009 | $0.00208 |
Grade A, and why
pdf 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 1mo 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.
The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What ships with it
11 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.
- forms.md 12 KB
- LICENSE.txt 1.4 KB
- reference.md 16 KB
- scripts/check_bounding_boxes.py 2.7 KB runs code
- scripts/check_fillable_fields.py 268 B runs code
- scripts/convert_pdf_to_images.py 1008 B runs code
- scripts/create_validation_image.py 1.2 KB runs code
- scripts/extract_form_field_info.py 4.2 KB runs code
- scripts/extract_form_structure.py 3.9 KB runs code
- scripts/fill_fillable_fields.py 3.7 KB runs code
- scripts/fill_pdf_form_with_annotations.py 3.2 KB runs code
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.
- 1mo ago First seen · 315 lines · 92 tokens per session scan A 9f78b8359fbd
pdf is a skill published in the GitHub repository bitsky-tech/bridgic-agent (50 stars, last pushed 5d ago), licensed AGPL-3.0. It adds 92 tokens to every session and 2,082 once invoked, about $0.0004 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 2026-08-30.
Other skills, from other repositories
summarize
Summarize or transcribe URLs, YouTube/videos, podcasts, articles, transcripts, PDFs, and local files.
nano-pdf
Edit PDFs with natural-language instructions using the nano-pdf CLI.
document-processing
Use when the deliverable is a document's bytes or its literal content — text/tables out of PDFs, AcroForm fill and flatten, page merge/split, PDF/DOCX from templates, OCR of image-only scans. NOT schema-typed fields pulled from text (that is structured-extraction), NOT signature routing (e-signature) or spreadsheet…
nutrient-document-processing
A guide for processing documents through the Nutrient DWS API, an online service for converting, reading, editing, and signing files. It supports PDFs, office documents, web pages, and images.
document-query
Read, extract or compare PDFs, Office files, URLs and large text; OCR when vision fails.
kb-import
Import knowledge from existing documents into structured KB entries. Reads source documents (Markdown, PDF, DOCX, plain text), extracts key information, and creates properly formatted KB entries with YAML frontmatter.