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/semantic-core/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/semantic-core)<a href="https://agentmods.dev/skills/pupok462/open-geo/semantic-core"><img src="https://agentmods.dev/badge/skills/pupok462/open-geo/semantic-core/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/semantic-core"><img src="https://agentmods.dev/badge/skills/pupok462/open-geo/semantic-core.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00091 | $0.02514 |
| Opus 5 | $0.00046 | $0.01257 |
| Sonnet 5 | $0.00018 | $0.00503 |
| Haiku 4.5 | $0.00009 | $0.00251 |
Grade A, and why
semantic-core 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 3d 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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
semantic-core — measured demand core, then the run
You are the orchestrator for one core build: find what people actually search around a product,
measure it through the platforms' own APIs, cluster it by intent, write the assistant-style
questions each cluster justifies, commit the whole thing as a core.json + questions.csv, and hand
that to an open-geo visibility run.
Two halves, deliberately separated:
- Deterministic — the numbers.
demand/asks Wordstat / Google Ads / Bing / autocomplete and returns each figure with its scope (region, period, pull date). No browser, no logged-in session, no hand-typed volume. Contract:pipeline/INTERFACES.md §8, guide:demand/README.md. - Agentic — the judgement. Which angles the product has, how a person phrases the need to an
assistant, which lines survive a skeptic. Authority:
harvest/METHODOLOGY.md(§3 demand gate, §4 lens invariants, §5 segments).
Run Python from the open-geo runtime root with its venv (
.venv/bin/python). Code and intermediate JSON are English; the summary you print follows--lang.
INVOCATION
/semantic-core <domain> --brand "<name>" [--market "<category>"] [--competitors "a, b"]
[--geo ru|us|ww|<cc>[,<cc>]] [--query-lang ru|en|<code>[,<code>]]
[--n 36] [--split 16/10/10] [--out core/<slug>/core.json]
[--run <engine>] [--n-worker N] [--output data|dashboard|pdf|both]
[--lang en|ru|zh|ar] [--no-run]
| arg / flag | required | default | meaning |
|---|---|---|---|
<domain> |
yes | — | The product's site. Also the target of the follow-on run. |
--brand "<name>" |
yes | — | Human brand name; enforces the lens/brand invariants at commit time. |
--market |
no | inferred | Category in the user's words. Inferred from the homepage when absent — always echo the inference for confirmation. |
--competitors |
no | — | Seed list; workers extend it. |
--geo |
no | ru |
ISO-3166 alpha-2 lowercase, or ww for worldwide. Comma-separated for several markets — each is measured on its own ruler. |
--query-lang |
no | follows geo | The language people search in — independent of --lang (the deliverable language). A distinct language is a distinct slice with its own CSV. |
--n |
no | 36 |
Target questions across all slices. |
--split |
no | derived | general/branded/comparative, general-tilted (for 36: 16/10/10). |
--out |
no | core/<brand-slug>/core.json |
Where the core artifact lands. The CSV goes beside it as <brand-slug>_questions.csv. |
--run <engine> |
no | ask | Engine for the follow-on open-geo run (google, chatgpt_search, yandex_neuro, …). |
--n-worker |
no | ask | Capture concurrency for that run. |
--no-run |
no | off | Build and commit the core, stop before the run. |
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.
- 3d ago First seen · 180 lines · 91 tokens per session scan A aee8fac1e4f6
semantic-core is a skill published in the GitHub repository Pupok462/open-geo (25 stars, last pushed 4d ago), licensed MIT. It adds 91 tokens to every session and 2,514 once invoked, about $0.0005 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 2026-09-05.
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