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 AtlasOmnia/hermes-custom-pack --skill office-document-reviewgit clone --depth 1 https://github.com/AtlasOmnia/hermes-custom-packWrote 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/atlasomnia/hermes-custom-pack/office-document-review)<a href="https://agentmods.dev/skills/atlasomnia/hermes-custom-pack/office-document-review"><img src="https://agentmods.dev/badge/skills/atlasomnia/hermes-custom-pack/office-document-review/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/atlasomnia/hermes-custom-pack/office-document-review"><img src="https://agentmods.dev/badge/skills/atlasomnia/hermes-custom-pack/office-document-review.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 | $0.00038 | $0.01221 |
| Opus 5.5 | $0.00015 | $0.00488 |
| Sonnet 5.5 | $0.00008 | $0.00244 |
| Haiku 4.5 | $0.00004 | $0.00122 |
Grade A, and why
office-document-review 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.
This is a copy
100% identical to office-document-review — 0 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Office Document Review
Use this skill when the user wants you to inspect a OneDrive/SharePoint-style folder tree, locate a subfolder by name/date, and proofread all documents in it for spelling and grammar.
This is a workflow skill, not a single-app skill: it covers local file-system browsing, document text extraction, and batch proofreading notes.
Triggers
- "go to the OneDrive folder"
- "look in folder X and then folder Y"
- "proofread all those documents"
- "check for spelling/grammar errors in the docs"
- "review the files in this folder"
Core workflow
- Resolve the real path first
- Prefer a filesystem path over guessing from the user’s wording.
- Folder names in casual speech may not match the actual on-disk name exactly.
- If the exact folder cannot be found, list the visible folder names and state what is missing before asking for clarification.
- Search the tree recursively
- Use the live file tree to locate the target folder and confirm the actual path.
- When the user gives a date-like folder name, search for variant spellings and punctuation (
6-2-26,6.2.26,6_2_26,6-2-2026) before assuming it does not exist.
- Inventory the documents
- Identify all files in the target folder.
- Group by extension and prioritize editable office docs (
.docx,.doc,.odt,.rtf,.txt) before PDFs or spreadsheets.
- Extract readable text
- For Word/Office files, extract the text in a way that preserves headings and paragraphs as much as possible.
- If the file-reading tool rejects
.docxas binary, do not classify the document as unreadable and do not repeat the same call across the batch. A DOCX is a ZIP package: validate it with Pythonzipfile, then usepython-docxwhen available or extractword/document.xmland convert paragraph/table XML to bounded text. Record package validity, paragraph/table counts, and extraction method. Use native Word or PDF rendering separately when layout—not just text—is under review. - When validating generated fixtures, compare extracted text against the fixture specification or authoritative
.txtsource before opening Word. A valid ZIP alone does not prove the fixture contains the intended content. - For scanned or image-based files, use OCR or an extraction tool first.
- If a file is not meaningfully text-reviewable after at least one appropriate format-specific fallback, say so explicitly instead of pretending to proofread 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.
- 1mo ago First seen · 108 lines · 38 tokens per session scan A b6cc86779655
office-document-review is a skill published in the GitHub repository AtlasOmnia/hermes-custom-pack (73 stars, last pushed yesterday), licensed MIT. It adds 38 tokens to every session and 1,221 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to office-document-review, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
obshare-cli
Use when setting up obshare-cli 0.2.0, reviewing available commands, or choosing the right command for config, upload, permission, history, delete, and the plugin-first direct-share workflow.
upload
Use when uploading a Markdown note to Feishu, optionally applying public or copy/download permissions, or requesting JSON upload results for automation or the Obsidian plugin direct-share flow.
permission
Use when changing Feishu document visibility, copy permissions, or download permissions for an uploaded document token.
delete
Use when removing a Feishu document by token and cleaning the matching entry from local obshare-cli upload history.
list
Use when checking obshare-cli upload history, finding document tokens, or reviewing previous upload URLs and permission snapshots.
knap
Render Markdown from templates and structured data using Knap CLI. Use when the user asks to apply a Knap template, turn JSON or CSV data into notes, batch-generate Markdown files, or format Defuddle output into a note.