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 ai-analyst-lab/ai-analyst --skill chart-to-drivegit clone --depth 1 https://github.com/ai-analyst-lab/ai-analystWrote 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/ai-analyst-lab/ai-analyst/chart-to-drive)<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst/chart-to-drive"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/chart-to-drive/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/ai-analyst-lab/ai-analyst/chart-to-drive"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/chart-to-drive.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 | $0.00196 | $0.01256 |
| Opus 5 | $0.00098 | $0.00628 |
| Sonnet 5 | $0.00039 | $0.00251 |
| Haiku 4.5 | $0.00020 | $0.00126 |
Grade A, and why
chart-to-drive 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Chart-to-Drive Uploader
Purpose
Standardized workflow for uploading local chart PNGs to Google Drive and making them available for insertion into Google Docs and Slides. One standard flow for upload, permissions, and URL construction, with no public file hosts involved.
When to Apply
Automatically whenever:
- Chart PNGs need to be inserted into Google Docs or Google Slides
- The
google-doc-creatororgoogle-slides-creatoragent needs chart URLs - User asks to "upload charts" or "add images to the doc/slides"
- User encounters "permission denied" or "image URL not accessible" errors when building Google Workspace documents — this usually means charts weren't uploaded to Drive first
When NOT to use this skill:
- For single-image uploads where you just need one Drive URL (use
mcp__google-docs__upload_image_to_drivedirectly) - When building Google Docs via the python-docx → upload workflow (that embeds images in the .docx file, no Drive URLs needed)
Workflow
Step 1: Collect chart files
Identify all chart PNGs that need uploading. Standard location: outputs/charts/.
import os
chart_dir = "outputs/charts"
charts = [(f, os.path.join(chart_dir, f)) for f in sorted(os.listdir(chart_dir)) if f.endswith('.png')]
Step 2: Upload each chart to Drive directly
Use the Google Docs MCP upload_image_to_drive tool with the LOCAL file path. It
uploads straight to the user's Drive and sets just enough link access for the
Docs/Slides APIs to fetch the image. No public file host is involved at any point;
never route charts through one (the analysis may contain confidential numbers).
for each (filename, filepath) in charts:
mcp__google-docs__upload_image_to_drive(image_path=filepath)
# Returns the Drive file ID; record it in the chart map
If that tool is unavailable, upload with the Drive API from Python using local
credentials (files().create with MediaFileUpload), then set reader link access.
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.
- 2d ago First seen · 125 lines · 196 tokens per session scan A a730bfbff1eb
chart-to-drive is a skill published in the GitHub repository ai-analyst-lab/ai-analyst (298 stars, last pushed 3d ago), licensed MIT. It adds 196 tokens to every session and 1,256 once invoked, about $0.0010 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 2026-09-12.
Other skills, from other repositories
baoyu-youtube-transcript
A tool for downloading the written captions, subtitles, chapter information, speaker labels, and cover image from a YouTube video using its URL or ID.
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…
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…
overleaf-sync
A two-way connection between a local paper folder and Overleaf, a web-based LaTeX editor for writing research papers. It lets you move changes between the local files and the shared Overleaf project.