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/vixues/leagent/document-processornpx skills add vixues/LeAgent --skill document-processorgit clone --depth 1 https://github.com/vixues/LeAgentWhat 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 | $0.00044 | $0.00459 |
| Opus 5 | $0.00022 | $0.00230 |
| Sonnet 5 | $0.00009 | $0.00092 |
| Haiku 4.5 | $0.00004 | $0.00046 |
Grade A, and why
document-processor 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
Document Processing
You are assisting with document processing tasks. Follow these guidelines.
Document Analysis Workflow
- Identify the document type: PDF, DOCX, XLSX, TXT, Markdown, HTML.
- Assess document structure: headers, sections, tables, images, metadata.
- Extract relevant content based on the user's request.
- Transform extracted content to the requested format.
- Validate accuracy, structure, and completeness.
Common Operations
Text Extraction
- Preserve document structure (headers, paragraphs, lists).
- Keep formatting where semantically meaningful (bold terms, emphasis).
- Extract metadata (author, creation date, document properties) when relevant.
Table Extraction
- Identify table boundaries and column headers.
- Preserve row/column relationships when exporting to CSV or JSON.
- Handle merged cells, nested tables, and multi-page tables carefully.
Information Extraction
- Extract specific fields (names, dates, amounts, addresses) with high precision.
- Use structured output (JSON, YAML) when returning multiple fields.
- Report confidence when extraction is ambiguous.
Format Conversion
- PDF ↔ Text/Markdown
- DOCX ↔ Markdown/HTML
- XLSX ↔ CSV/JSON
- HTML ↔ Markdown
Quality Guidelines
- Verify that extracted content matches the source.
- Preserve line breaks and paragraph structure unless asked to flatten.
- Flag OCR artifacts or illegible sections explicitly.
- For multi-page documents, maintain page references where useful.
Error Handling
- Document any parts that could not be processed (e.g., encrypted pages, images).
- Provide clear error messages for unsupported formats.
- Suggest alternative approaches when the primary method fails.
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 · 63 lines · 44 tokens per session scan A 2f64120cc234
document-processor is a skill published in the GitHub repository vixues/LeAgent (216 stars, last pushed 21d ago), licensed Apache-2.0. It adds 44 tokens to every session and 459 once invoked, about $0.0002 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 2026-08-30.
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