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/prashishh/seo-geo-report-engineWrote 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/prashishh/seo-geo-report-engine/new-client)<a href="https://agentmods.dev/commands/prashishh/seo-geo-report-engine/new-client"><img src="https://agentmods.dev/badge/commands/prashishh/seo-geo-report-engine/new-client/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/prashishh/seo-geo-report-engine/new-client"><img src="https://agentmods.dev/badge/commands/prashishh/seo-geo-report-engine/new-client.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 | $0.00027 | $0.00910 |
| Opus 5 | $0.00014 | $0.00455 |
| Sonnet 5 | $0.00005 | $0.00182 |
| Haiku 4.5 | $0.00003 | $0.00091 |
Grade A, and why
new-client 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 9d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/new-client
Stand up a new client project at projects/$1/. The slug ($1) is kebab-case and becomes the
output filename prefix everywhere. A project is pure data — it inherits every capability from
this parent framework (see the root CLAUDE.md). This command does the scaffold, then interviews
the user for the profile that the skills downstream depend on.
Steps
-
Guard. If
projects/$1/already exists, stop and tell the user (offer to openclient.ymlinstead). Slug must be kebab-case — lowercase, hyphens, no spaces. -
Scaffold the folders.
mkdir -p projects/$1/{inputs,research,deliverables,data}inputs/— briefs, exports, source material the client gave us.research/— keyword / competitor / GEO / audit outputs we generate.deliverables/— proposals, reports, comparison pages (the handover).data/— snapshots, rank history, csv (data/raw/is gitignored).
-
Copy the templates (don't author from scratch — copy then edit):
cp templates/client.yml.example projects/$1/client.yml cp templates/project/CLAUDE.md projects/$1/CLAUDE.md -
Interview the user for the essentials. Ask in one batched message; let them answer what they know and leave the rest blank. Capture:
- Name + domain (apex, e.g.
acme.com). - Industry (one line) and market (primary geo) + languages.
- Positioning — 2–3 lines: what they sell, to whom, the wedge.
- ICP — the ideal customer profiles / segments.
- Competitors — name + domain for each (used by competitor + comparison skills).
- Target keywords — seed terms for keyword / rank / programmatic work.
- Brand colors —
primaryandaccenthex (for proposal/report decks). - Ahrefs ids —
project_id(Rank Tracker / Site Audit) andbrand_radar_report_id(GEO). If the user doesn't have them, offer to list withmanagement-projectsandmanagement-brand-radar-reports(Ahrefs MCP) and match by domain, then paste the ids in. - Owned analytics (optional) — GA4 property id, GSC site (
sc-domain:…or URL).
- Name + domain (apex, e.g.
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.
- 9d ago First seen · 65 lines · 27 tokens per session scan A 8b5685acb0a9
new-client is a command published in the GitHub repository prashishh/seo-geo-report-engine (5 stars, last pushed 2mo ago), licensed MIT. It adds 27 tokens to every session and 910 once invoked, about $0.0001 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 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.
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.
influencer
Run an influencer-marketing (STAR) workflow: audience & creator scouting, campaign targeting, briefs, outreach, amplification, and ROI reporting. 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.