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 aivrar/portable-hermes-agent --skill document-to-action-itemsgit clone --depth 1 https://github.com/aivrar/portable-hermes-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/aivrar/portable-hermes-agent/document-to-action-items)<a href="https://agentmods.dev/skills/aivrar/portable-hermes-agent/document-to-action-items"><img src="https://agentmods.dev/badge/skills/aivrar/portable-hermes-agent/document-to-action-items/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/aivrar/portable-hermes-agent/document-to-action-items"><img src="https://agentmods.dev/badge/skills/aivrar/portable-hermes-agent/document-to-action-items.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 | $0.00015 | $0.00825 |
| Opus 5 | $0.00008 | $0.00413 |
| Sonnet 5 | $0.00003 | $0.00165 |
| Haiku 4.5 | $0.00002 | $0.00082 |
Grade A, and why
document-to-action-items 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 7d 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.
This is a copy
86% identical to document-to-action-items — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Document to Action Items
Turn documents into cited facts and proposed actions. Extraction is not legal advice, and low-confidence OCR or ambiguous language must remain visible. The ocr-and-documents / pdf / docx skills own extraction mechanics; this skill owns what happens to the extracted content.
When to Use
- "Extract deadlines and obligations from this contract."
- "Turn this report into tasks."
- "Read these scanned forms and structure the data."
- "Find risks, owners, and follow-ups in these attachments."
Don't use for: plain text extraction with no downstream structuring (load ocr-and-documents directly).
Procedure
1. Inventory the document set
Use read_file for local files and web_extract for URLs to identify files, versions, dates, page counts, language, scan quality, and the requested output schema. Detect duplicate/revised copies before analysis. Done when the authoritative or latest version is known or ambiguity is stated.
2. Extract with provenance
Load ocr-and-documents, pdf, or docx. Extract text/tables while retaining file and page/section coordinates. For scans, record OCR confidence or visible quality issues. Done when every extracted field can cite its source location.
3. Classify evidence
Separate:
- parties/entities and identifiers
- dates and deadlines
- money/quantities
- obligations and prohibitions
- approvals and signatures
- risks/exceptions
- factual background
- ambiguous or unreadable clauses
Do not collapse "may," "should," and "must." Done when modality and uncertainty are preserved.
4. Validate internally
Cross-check dates, totals, repeated names, table sums, defined terms, and references to appendices. Surface contradictions rather than choosing silently. Done when key facts have consistency checks or explicit exceptions.
5. Convert to proposed actions
For each actionable obligation create outcome, owner if explicit, due date if explicit, dependency, acceptance condition, risk, and citation. Unknown owners/dates remain unresolved — never invented. Done when no proposed task relies on an unsupported inference.
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.
- 7d ago First seen · 82 lines · 15 tokens per session scan A f114af652272
document-to-action-items is a skill published in the GitHub repository aivrar/portable-hermes-agent (217 stars, last pushed yesterday), licensed MIT. It adds 15 tokens to every session and 825 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to document-to-action-items, differing in 8 lines, and is treated as a copy.
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