Borrowing it
Nothing to install: this file belongs to Pupok462/open-geo. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Pupok462/open-geo/main/.agents/skills/open-geo/SKILL.mdgit clone --depth 1 https://github.com/Pupok462/open-geoWrote 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/pupok462/open-geo/open-geo)<a href="https://agentmods.dev/skills/pupok462/open-geo/open-geo"><img src="https://agentmods.dev/badge/skills/pupok462/open-geo/open-geo/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/pupok462/open-geo/open-geo"><img src="https://agentmods.dev/badge/skills/pupok462/open-geo/open-geo.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 | $0.00077 | $0.08080 |
| Opus 5 | $0.00039 | $0.04040 |
| Sonnet 5 | $0.00015 | $0.01616 |
| Haiku 4.5 | $0.00008 | $0.00808 |
Grade A, and why
open-geo scanned grade A with 1 finding 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 7d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
`curl` health probe before you hand over a URL), `report.generate` including the combined How it starts
The opening of the file, as written. The whole thing — 474 lines — stays where its author put it; the contents beside it link to each section on GitHub.
open-geo — GEO visibility run orchestrator
You are the orchestrator for one open-geo run: drive a list of queries through one AI engine, capture how the target domain shows up in the answers, ingest the captures through the validated pipeline, aggregate metrics, and emit a portable JSON artifact plus any requested presentation output — finishing with a short summary.
This skill is the single operator and agent-workflow entry point. It can be invoked
directly by a user or called as one step inside another agent's workflow; in both cases it
returns the same versioned JSON artifact for downstream consumption. It coordinates components that are
specified in pipeline/INTERFACES.md (the authoritative contract). Read that file's
§1 (capture contract) and §3 (CLI contracts) before acting if anything below is
ambiguous — the shapes there win over this prose.
Code/identifiers and intermediate JSON are English. The final summary printed to the user follows
--lang(default English). Run pipeline commands from the resolved open-geo runtime root with its project venv (.venv/bin/python) sopipeline.*imports resolve. An explicit absolute--artifact-outmay point into the caller's workspace; all other runtime state stays inside open-geo.
INVOCATION
/open-geo <questions.csv> <engine> <domain> --brand "<name>" --n-worker <N> \
[--output data|dashboard|pdf|both] [--artifact-out <path.json>] \
[--period today|all] [--lang en|ru|zh|ar] [--force] [--repeat R]
Positional arguments
| arg | meaning |
|---|---|
<questions.csv> |
Path to the input CSV. Columns: query,lens where lens ∈ general | branded | comparative. See examples/questions.csv for a ready sample. general = neutral query, no brand named; branded = brand explicitly named; comparative = brand vs alternatives. Either a hand-made CSV or one generated by STEP A.5 (question harvesting, Feature 1 — harvest/METHODOLOGY.md); both are first-class. |
<engine> |
Engine id, snake_case, e.g. google. This value is (a) the engine field written into every QueryCapture and the run, and (b) the basename of the capture playbook the workers load: engines/<engine>.md (so google ↔ engines/google.md). This is the multi-engine extension point — google (Google AI Overview), chatgpt_search (ChatGPT web search), claude_search (Claude web search), yandex_neuro (Yandex Alice / Нейро), gemini (Google Gemini), deepseek (DeepSeek web search) and perplexity (Perplexity) ship today, all live-validated; the others are on the roadmap (ROADMAP Feature 3), and adding one is mainly authoring engines/<engine>.md (see engines/README.md). |
<domain> |
The target — a registrable domain (example.com) or a URL prefix (github.com/user/repo). Accept any spelling; normalized via pipeline.schema.normalize_target. Workers match links against the target via matches_target/target_ranks (same semantics pipeline-wide). |
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago Changed · -202 lines 83e40c1ecffb
- 12d ago First seen · 676 lines · 77 tokens per session scan A 6ce6f752c4a1
open-geo is a skill published in the GitHub repository Pupok462/open-geo (25 stars, last pushed 7d ago), licensed MIT. It adds 77 tokens to every session and 8,080 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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Use when a client audit, GEO/AI-visibility snapshot, or remediation re-scan needs the Cloudflare agent-readiness score from isitagentready.com — e.g. Theo client audits, "is the site agent-ready", markdown negotiation / MCP / llms.txt / Content-Signal checks, or tracking score deltas after Tier 0/1 fixes.
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