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 dambuchs/redact-pdf-mcp --skill redact-before-sharinggit clone --depth 1 https://github.com/dambuchs/redact-pdf-mcpWrote 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/dambuchs/redact-pdf-mcp/redact-before-sharing)<a href="https://agentmods.dev/skills/dambuchs/redact-pdf-mcp/redact-before-sharing"><img src="https://agentmods.dev/badge/skills/dambuchs/redact-pdf-mcp/redact-before-sharing/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/dambuchs/redact-pdf-mcp/redact-before-sharing"><img src="https://agentmods.dev/badge/skills/dambuchs/redact-pdf-mcp/redact-before-sharing.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 | $0.00094 | $0.00549 |
| Opus 5.5 | $0.00038 | $0.00220 |
| Sonnet 5.5 | $0.00019 | $0.00110 |
| Haiku 4.5 | $0.00009 | $0.00055 |
Grade A, and why
redact-before-sharing 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 today.
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
Redact a document before it leaves
1. Run the redaction
Call redact_pdf_and_wait with file_path set to the user's PDF, JPEG or PNG. Pass photos and screenshots as they are; don't convert them to PDF first. If the user only wants to share the result and not have you read it, don't open the original either: pass the path.
Narrow it only when the user asks to:
pii_categories: only these kinds of data (for example onlyPersonandEmail).pii_included_terms: extra words to always black out, such as a project code name.pii_excluded_terms: words to keep visible, such as the user's own company name.
For a folder, start one redact_pdf job per file, then collect each with get_job_status and download_redacted. Don't upload the same file twice. If a call times out, the job keeps running: poll get_job_status with the job_id.
If there is no API key, call try_demo with the same file_path to redact the first page for free, then tell the user a free account gets its first document (up to 5 pages) done in full. If the user then gives you a key in the conversation, call set_api_key with it once and carry on; don't repeat the key back.
2. Report back
Give the user output_path (by default <name>-redacted.pdf next to the original, which is left unchanged) and the page count.
Tell them the redacted text is deleted from the file, not hidden under a black box, so it can't be copied out or recovered. Automatic detection can still miss something, so for a filing or anything public they should look through the redacted PDF before sending it. They can add or remove boxes in the Studio at redact-pdf.ai.
If the user wants the document to stay readable, with "who did what" still clear, use the anonymize-before-ai skill instead. Black boxes lose who did what; [Person 1] tags keep it.
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.
- today First seen · 29 lines · 94 tokens per session scan A c5296062f594
redact-before-sharing is a skill published in the GitHub repository dambuchs/redact-pdf-mcp (1 stars, last pushed today), licensed MIT. It adds 94 tokens to every session and 549 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 2026-10-19.
Other skills, from other repositories
pdf-processing
Extract text from PDFs, fill forms, and merge documents.
kernelcad-drawings
Export 2D engineering-drawing sheets (SVG, or a printable PDF on a standard sheet) from any model or assembly — third-angle front/top/left + isometric views with hidden-line removal, overall dimensions, and a title block. Use when the deliverable is a human-readable fabrication or review drawing.
agoragentic-anydoc-document-evidence
Convert a local Word, PowerPoint, spreadsheet, OpenDocument, RTF, EPUB, CSV, or text-based PDF into bounded Markdown and an Agoragentic evidence handoff. Use when an agent needs document contents plus runtime-verified provenance, explicit evidence coverage, known-loss warnings, and a pending-or-incomplete parse…
contract-analyzer
Extract contract parties, clauses, dates, and model-assessed risks using processdocument. Use when the user supplies contract text, Markdown, or a PDF/image for analysis.
pdf-invoice-extractor
Extract typed invoice data from supplied text, Markdown, or a PDF/image through processdocument. Use for invoice totals, line items, due dates, and extraction anomalies.
book-mirror
Take any book (EPUB/PDF), produce a personalized chapter-by-chapter analysis with two-column tables. Left column preserves the chapter content; right column maps every idea to the reader's actual life using brain context. Output is a single brain page at media/books/ -personalized plus an optional PDF via brain-pdf.