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.
npx skills add BuilderCed/agent-skills --skill fr-open-data-explorergit clone --depth 1 https://github.com/BuilderCed/agent-skillsWrote 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/builderced/agent-skills/fr-open-data-explorer)<a href="https://agentmods.dev/skills/builderced/agent-skills/fr-open-data-explorer"><img src="https://agentmods.dev/badge/skills/builderced/agent-skills/fr-open-data-explorer/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/builderced/agent-skills/fr-open-data-explorer"><img src="https://agentmods.dev/badge/skills/builderced/agent-skills/fr-open-data-explorer.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 | $0.00045 | $0.01023 |
| Opus 5.5 | $0.00018 | $0.00409 |
| Sonnet 5.5 | $0.00009 | $0.00205 |
| Haiku 4.5 | $0.00005 | $0.00102 |
Grade A, and why
fr-open-data-explorer 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
French Open Data Explorer
Quand Utiliser
- Enrichir des donnees entreprise avec SIRENE
- Analyser le marche immobilier avec DVF
- Obtenir des donnees demographiques INSEE
- Verifier des informations cadastrales
- Analyser la performance energetique (DPE)
Sources Principales
| Source | Contenu | API | Licence |
|---|---|---|---|
| SIRENE (INSEE) | 12M+ entreprises, SIRET, NAF, dirigeants | api.insee.fr | Licence Ouverte 2.0 |
| DVF (Etalab) | Transactions immobilieres depuis 2014 | data.gouv.fr | Licence Ouverte 2.0 |
| Cadastre | Parcelles, batiments, adresses | cadastre.data.gouv.fr | Licence Ouverte 2.0 |
| DPE (ADEME) | Diagnostics energetiques batiments | data.ademe.fr | Licence Ouverte 2.0 |
| INSEE | Population, revenus, emploi par commune | api.insee.fr | Licence Ouverte 2.0 |
| BAN | Adresses normalisees (geocodage) | api-adresse.data.gouv.fr | Licence Ouverte 2.0 |
| RNCS | Registre du commerce | data.inpi.fr | Licence Ouverte 2.0 |
Cas d'Usage
1. Enrichissement Entreprise
Objectif : a partir d'un SIRET, obtenir raison sociale, adresse, code NAF, effectif.
API: GET https://api.insee.fr/entreprises/sirene/V3.11/siret/{SIRET}
Auth: Bearer token (inscription gratuite api.insee.fr)
2. Analyse Immobiliere
Objectif : prix au m2 par commune, evolution, comparaison.
Dataset: "demandes-de-valeurs-foncieres" sur data.gouv.fr
Filtres: code_commune, type_local, date_mutation
Calcul: prix/surface = prix_m2
3. Diagnostic Energetique
Objectif : DPE d'un batiment, classe energetique, recommandations.
API: data.ademe.fr/datasets/dpe-v2
Filtres: code_postal, adresse, numero_dpe
4. Geocodage
Objectif : convertir adresse en coordonnees GPS.
API: GET https://api-adresse.data.gouv.fr/search/?q={adresse}
Retour: latitude, longitude, score de confiance
Qualite des Donnees
| Source | Fraicheur | Completude | Fiabilite |
|---|---|---|---|
| SIRENE | Quotidienne | Tres haute | Officielle |
| DVF | Semestrielle | Haute (hors Alsace-Moselle) | Officielle |
| Cadastre | Mensuelle | Haute | Officielle |
| DPE | Continue | Moyenne (pas tous les batiments) | Variable |
| BAN | Continue | Haute | Collaborative |
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 · 100 lines · 45 tokens per session scan A b21926fa9df7
fr-open-data-explorer is a skill published in the GitHub repository BuilderCed/agent-skills (2 stars, last pushed 6mo ago), licensed MIT. It adds 45 tokens to every session and 1,023 once invoked, about $0.0002 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 2026-08-31.
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