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 thiswillbeyourgithub/wdoc --skill wdoc-skillgit clone --depth 1 https://github.com/thiswillbeyourgithub/wdocWrote 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/thiswillbeyourgithub/wdoc/wdoc-skill)<a href="https://agentmods.dev/skills/thiswillbeyourgithub/wdoc/wdoc-skill"><img src="https://agentmods.dev/badge/skills/thiswillbeyourgithub/wdoc/wdoc-skill/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/thiswillbeyourgithub/wdoc/wdoc-skill"><img src="https://agentmods.dev/badge/skills/thiswillbeyourgithub/wdoc/wdoc-skill.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 | $0.00121 | $0.01151 |
| Opus 5.5 | $0.00048 | $0.00460 |
| Sonnet 5.5 | $0.00024 | $0.00230 |
| Haiku 4.5 | $0.00012 | $0.00115 |
Grade A, and why
wdoc-skill 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
2 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.
- 1mo ago First seen · 74 lines · 121 tokens per session scan A 662c278f2518
wdoc-skill is a skill published in the GitHub repository thiswillbeyourgithub/wdoc (544 stars, last pushed 4d ago), licensed AGPL-3.0. It adds 121 tokens to every session and 1,151 once invoked, about $0.0005 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
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docutranslate
Use when translating documents locally via LLM — PDF, Word, Excel, Markdown, SRT subtitles with format preservation. DocuTranslate: LLM-powered multi-format local file translation tool with MCP server support.
delivery-engine
Zentrale Zustellungs-Engine fuer Dossiers, Analysen und Berichte. Kanaluebergreifende Zustellung mit User-Folder, Browser-Preview, E-Mail, Telegram, Cloud-Local und System-Inbox. Stand 2026-09-17: vollstaendig implementiert, aber noch von keinem Handler importiert (nur Standalone-Nutzung/Demo vorhanden).
pdf-extractor
Extract and convert PDF documents using Python scripts.
Read, fill and build PDFs: inspect structure and fonts, extract text and tables with pdfplumber and poppler, fill and flatten AcroForms with pypdf, create with reportlab, merge, split and encrypt with qpdf, and verify by rendering the page and looking at it.
Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.