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.
git clone --depth 1 https://github.com/mverab/eGEOagentsWrote 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/commands/mverab/egeoagents/geo-batch)<a href="https://agentmods.dev/commands/mverab/egeoagents/geo-batch"><img src="https://agentmods.dev/badge/commands/mverab/egeoagents/geo-batch/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/commands/mverab/egeoagents/geo-batch"><img src="https://agentmods.dev/badge/commands/mverab/egeoagents/geo-batch.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 | $0.00011 | $0.00452 |
| Opus 5.5 | $0.00004 | $0.00181 |
| Sonnet 5.5 | $0.00002 | $0.00090 |
| Haiku 4.5 | $0.00001 | $0.00045 |
Grade A, and why
geo:batch 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 23d 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.
What it actually says
/geo:batch Command
Batch process all content files in a folder.
Workflow
- Validate MCPs - Run
validation-doctor; if missing, provide setup snippets - Scan - Find all matching files in folder; announce the count before starting
- Process - Run
/geo:optimizeon each file (analyzer-based), reporting progress after each one - Summarize - Generate batch report
Progress
Report progress as you go, never only at the end:
- Before processing, print
Processing batch (N files)...with the total found. - After each file finishes, print one line
[i/N] <file> ✓(or✗ <short reason>if it failed). Do not hold lines back to print them together. - A failed file does not stop the batch: record it, continue with the next file, and list failures in the summary.
- Finish with
Complete! Results in geo-output/(orComplete with K failure(s). Results in geo-output/).
Processing batch (3 files)...
[1/3] pricing.md ✓
[2/3] about.md ✓
[3/3] contact.md ✗ empty file, skipped
Complete with 1 failure. Results in geo-output/
If no files match, print No files matching <pattern> in <folder>. and stop.
Output
For each file:
- Optimized version in
geo-output/optimized/ - Schema in
geo-output/schema/
Summary report with:
- Files processed
- Average score improvement
- Top priority fixes across all content
Example Usage
/geo:batch ./content
/geo:batch ./pages --pattern "*.html"
/geo:batch ./blog
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.
- 23d ago Changed · +20 lines 6403e3ad3986
- 1mo ago First seen · 42 lines · 11 tokens per session scan A 6db49a08a80c
geo:batch is a command published in the GitHub repository mverab/eGEOagents (207 stars, last pushed 2d ago), licensed MIT. It adds 11 tokens to every session and 452 once invoked, about $0.0000 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 2026-08-30.
Other commands, from other repositories
seo-geo
SEO/GEO end-to-end along the SITE loop: survey demand and competitors, implement content, tune quality/tech/on-page, and evaluate authority/rankings/reports/memory (--phase survey|implement|tune|evaluate). Not sure? Use /aaron-marketing:auto.
launch
Run a product-launch (RAMP) workflow: positioning and launch tiering, window/early-access design, message house and asset kits, the launch-readiness gate with a T-1 go/no-go, launch-day execution, and the post-launch prove loop. Not sure? Use /aaron-marketing:auto.
narrative
Run a brand-narrative & messaging (TALE) workflow: trace the current message and positioning truth, architect the durable message house/voice/story canon, land it consistently across every surface, and evaluate resonance with tests and drift monitoring. Not sure? Use /aaron-marketing:auto.
social
Run an organic-social (ECHO) workflow: channel portfolio and voice dossiers, platform-native content and calendars, the social-quality gate with a pre-publish go/no-go, community/inbox/crisis operations, and the listening/SOV/dark-social measurement loop. Not sure? Use /aaron-marketing:auto.
ad
Run a paid-ads (ROAS) workflow: audience segments, account structure, ad creative, experiment design, pre-launch signal QA + the account-audit gate, measurement, and attribution. Not sure? Use /aaron-marketing:auto.
Run an email-marketing (SEND) workflow: deliverability/consent setup, segmentation, email creative, lifecycle flows, newsletter monetization, send-testing, and the email-quality audit gate. Not sure? Use /aaron-marketing:auto.