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-loop)<a href="https://agentmods.dev/commands/mverab/egeoagents/geo-loop"><img src="https://agentmods.dev/badge/commands/mverab/egeoagents/geo-loop/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-loop"><img src="https://agentmods.dev/badge/commands/mverab/egeoagents/geo-loop.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 | $0.00035 | $0.00809 |
| Opus 5.5 | $0.00014 | $0.00324 |
| Sonnet 5.5 | $0.00007 | $0.00162 |
| Haiku 4.5 | $0.00003 | $0.00081 |
Grade A, and why
geo:loop 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/geo:loop Command
Execute one eGEOagents loop iteration. Loop state lives in the workspace
resolved from $EGEO_HOME (default ~/.egeo/); the repo tree is never written
to. One-shot /geo <url> is unaffected.
Follow .claude/skills/geo-loop/SKILL.md — it is the authoritative procedure.
Workflow
- Resolve the domain - Use
$ARGUMENTS.domain. If omitted and exactly one directory exists under$EGEO_HOME/domains/(excludingegeo-core), use it; otherwise list the domains and stop. - Plan -
egeo loop run <domain> --dry-run. Writes nothing. Non-zero exit means stop and report (egeo loop doctorexplains why). - Read state - domain charter,
data/*.jsonldeltas, existingsignals/,docs/,config.yaml. - One unit of work - from
## Current focus, else the first Backlog item. Reusecontent-scoring,competitive-analysis,schema-generator. No fresh data and nothing actionable =Outcome: no-op. - Write artifacts -
signals/<slug>.md/docs/<slug>.mdperSUBSTRATE.md. Re-observed evidence incrementsfrequencyon the existing signal instead of creating a file. - Close the run - append exactly one
### YYYY-MM-DD runTimeline entry ending inOutcome: success|partial|failure|no-op, and exactly oneLOG.mdline. Update## Current focusif it was completed. - Verify -
python -m egeo.substrate_lintandegeo loop doctor, then re-read both appends. Violations are fixed before exiting.
Execution
Loop run: $ARGUMENTS.domain
Step 1/6: Plan
→ egeo loop run $ARGUMENTS.domain --dry-run
Step 2/6: Reading workspace state
→ $EGEO_HOME/domains/$ARGUMENTS.domain/README.md, data/, signals/, docs/
Step 3/6: Unit of work
→ <focus item>
Step 4/6: Writing artifacts
→ signals/... / docs/...
Step 5/6: Closing the run
→ Timeline entry + LOG.md line
Step 6/6: Verification
→ substrate_lint + doctor + re-read
Output
Written to $EGEO_HOME/ (never geo-output/):
signals/[slug].md- evidence, deduped and frequency-counteddocs/[slug].md- durable knowledge, citing signals and sourcesdomains/[domain]/README.md- one appended Timeline entryLOG.md- one appended line
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 · 87 lines · 35 tokens per session scan A 6cc1ed5afaac
geo:loop is a command published in the GitHub repository mverab/eGEOagents (207 stars, last pushed 2d ago), licensed MIT. It adds 35 tokens to every session and 809 once invoked, about $0.0001 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.