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 exportgit 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/export)<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst/export"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/export/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/export"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/export.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 | $0.00197 | $0.03643 |
| Opus 5.5 | $0.00079 | $0.01457 |
| Sonnet 5.5 | $0.00039 | $0.00729 |
| Haiku 4.5 | $0.00020 | $0.00364 |
Grade A, and why
export 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.
How it starts
The opening of the file, as written. The whole thing — 342 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Export
Purpose
Export analysis results in different formats for different audiences. Converts pipeline outputs into ready-to-share deliverables.
Invocation
/export slides — generate/refresh Marp slide deck from latest analysis
/export email — write an executive summary email (markdown)
/export slack — write a concise Slack update (markdown)
/export brief — write a 1-page decision brief (markdown)
/export data — export analysis data tables as CSV
/export gdoc — create a Google Doc with full Analysis Readout (charts, SQL, bookmarks)
/export docx — generate a local .docx Word document (no Google upload)
/export notion — publish a verified analysis as an approved Notion text page
/export receipt — generate full analysis receipt (Reproduce-level audit trail)
/export all — generate all text formats + data (does NOT include gdoc, notion, or receipt — use /export gdoc, /export notion, and /export receipt separately)
Instructions
Step 1: Find Source Material
Primary source detection (use exactly ONE of these, in order):
outputs/narrative_*.md— if exists, use the most recent by date (check filename date suffix)outputs/analysis_*.md— if narrative absent, use most recent analysisworking/pipeline_summary.md— if no outputs/ files existworking/storyboard_*.md— last resort if above are all missing
How to choose when multiple files exist: Sort by filename date (YYYYMMDD or YYYY-MM-DD suffix), use the latest. If no date in filename, use file modification time.
Supporting materials (collect when available, but NOT primary source):
outputs/charts/*.png— chart imagesoutputs/validation_*.md— confidence scoreoutputs/close_the_loop_*.md— success tracking + action itemsworking/sql_queries/*.sql— SQL queries
If no outputs exist:
- Check
working/for partial results - If nothing found: "No analysis results to export. Run an analysis first or use
/run-pipeline."
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 Changed · +5 lines 5c5e8a569931
- 1mo ago First seen · 337 lines · 197 tokens per session scan A 73783757add2
export is a skill published in the GitHub repository ai-analyst-lab/ai-analyst (322 stars, last pushed 1mo ago), licensed MIT. It adds 197 tokens to every session and 3,643 once invoked, about $0.0008 per session on Opus 5.5. 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.
export compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| exportai-analyst-lab/ai-analyst | Skill | 322 | 1mo ago | MIT | A | 197 | Claude Code |
| orbit-notionnexu-io/open-design | Skill | 106k | yesterday | Apache-2.0 | A | 117 | Claude Code, Codex |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | 2d ago | Apache-2.0 | A | 123 | Claude Code |
| apify-youtube-transcript-scrapersickn33/agentic-awesome-skills | Skill | 49k | yesterday | MIT | A | 48 | Claude Code |
| legal-holdanthropics/claude-for-legal | Skill | 9.9k | 3d ago | Apache-2.0 | A | 68 | Claude Code |
| ppt-reviewOrkas-AI/Orkas | Skill | 9.0k | yesterday | MIT | A | 2 | Claude Code, Codex |
| feishuHmbown/CodeWhale | Skill | 41k | 5d ago | MIT | A | 33 | Claude Code, Codex |