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/traxonlp/hivemcp/hivemcp-usagenpx skills add traxonLp/HiveMCP --skill hivemcp-usagegit clone --depth 1 https://github.com/traxonLp/HiveMCPWrote 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/traxonlp/hivemcp/hivemcp-usage)<a href="https://agentmods.dev/skills/traxonlp/hivemcp/hivemcp-usage"><img src="https://agentmods.dev/badge/skills/traxonlp/hivemcp/hivemcp-usage.svg" alt="Measured on agentmods" 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 | $0.02539 |
| Opus 5 | $0.00019 | $0.01269 |
| Sonnet 5 | $0.00008 | $0.00508 |
| Haiku 4.5 | $0.00004 | $0.00254 |
Grade A, and why
hivemcp-usage 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.
How it starts
The opening of the file, as written. The whole thing — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Using HiveMCP
HiveMCP turns a spec you write into a real .pptx, .docx, .xlsx or .md file. You
supply the content; the server does the layout. It never invents content for a spec you
passed, and it never silently drops a field it does not understand — an unknown field is
a validation error you should fix and resend.
Pick the tool
| The user wants | Call |
|---|---|
slides, a deck, a presentation, .pptx |
hive_create_presentation |
a report, letter, memo, manual, .docx |
hive_create_document |
a table, workbook, budget, .xlsx |
hive_create_spreadsheet |
a README, release notes, .md |
hive_create_markdown |
| to change a file they attached | hive_read_document, then hive_edit_document |
| to see the corporate templates | hive_list_templates |
| to choose fonts, template, length | hive_open_config |
Write the file. Do not write the content into the chat instead. If someone asks for
a presentation, a message containing slide text is not what they asked for. Call the
tool, then tell them briefly what you made and hand them the download link from
download_markdown.
The two cards
Two tools return HTML that OpenWebUI renders as an interactive card. Return what they give you unchanged — do not summarise it, quote it, or describe it. Both are for the user to look at, not for you to read.
hive_open_config shows a settings form: font, size, template, audience, length,
page size. Call it when someone wants to choose how a document should look rather than
describe it — "settings", "options", "configure", "Einstellungen", or when they ask about
templates or fonts. Their choices come back as a new chat message, and only then do you
call a create tool.
Also worth offering when a request is vague about presentation and the answer would change the result: "Willst du Schrift und Vorlage vorher festlegen?" is often better than guessing. Do not open it for every request — someone who says "mach mir eine Präsentation über Kaffee" wants a presentation, not a form.
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 Changed · +32 lines · +3 tokens per session dbbad292fd91
- 5d ago First seen · 200 lines · 35 tokens per session scan A d562abea8856
hivemcp-usage is a skill published in the GitHub repository traxonLp/HiveMCP (1 stars, last pushed 3d ago), licensed MIT. It adds 38 tokens to every session and 2,539 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 2026-08-31.
Other skills, from other repositories
orbit-notion
Open Orbit briefing skill — selected by the Orbit pipeline when Notion is the user's only connected connector, or when the user explicitly scopes their daily digest to Notion. Pulls the past 24 hours of document edits, comments, mentions, and database row changes from the user's authenticated Notion connection and…
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
baoyu-youtube-transcript
Downloads YouTube video transcripts/subtitles and cover images by URL or video ID. Supports multiple languages, translation, chapters, and speaker identification. Caches raw data for fast re-formatting. Use when user asks to "get YouTube transcript", "download subtitles", "get captions", "YouTube字幕", "YouTube封面"…
feishu
Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.
read
Reads URLs and PDFs by fetching source content, defaulting to concise summaries for plain read requests and clean Markdown when asked to convert, save, quote, cite, or feed downstream work. Use when users ask in any language to read, fetch, check, summarize, quote, cite, convert, or save a URL or PDF. Not for local…
gog-slides
Google Slides operations through gog.