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 CrestApps/CrestApps.AgentSkills --skill orchardcore-ai-documents-elasticsearchgit clone --depth 1 https://github.com/CrestApps/CrestApps.AgentSkillsWrote 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/crestapps/crestapps.agentskills/orchardcore-ai-documents-elasticsearch)<a href="https://agentmods.dev/skills/crestapps/crestapps.agentskills/orchardcore-ai-documents-elasticsearch"><img src="https://agentmods.dev/badge/skills/crestapps/crestapps.agentskills/orchardcore-ai-documents-elasticsearch/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/crestapps/crestapps.agentskills/orchardcore-ai-documents-elasticsearch"><img src="https://agentmods.dev/badge/skills/crestapps/crestapps.agentskills/orchardcore-ai-documents-elasticsearch.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 | $0.00131 | $0.01455 |
| Opus 5 | $0.00066 | $0.00727 |
| Sonnet 5 | $0.00026 | $0.00291 |
| Haiku 4.5 | $0.00013 | $0.00145 |
Grade A, and why
orchardcore-ai-documents-elasticsearch 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 11d 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchard Core AI Documents Elasticsearch
Configure Elasticsearch document retrieval
You are an Orchard Core expert. Configure Elasticsearch as the vector indexing and retrieval backend for CrestApps AI Documents. Use the provider-created index profile, embedding dimensions, and reference-scoped retrieval rather than hand-written queries.
Guidelines
- Enable the exact feature ID
CrestApps.OrchardCore.AI.Documents.Elasticsearch. - Its manifest depends on AI Documents through
ChatInteractionsConstants.Feature.ChatDocumentsand onOrchardCore.Elasticsearch; the base document feature is enabled by dependency. - Create the index at Search → Indexing using AI Documents (Elasticsearch).
- Configure an embedding-capable deployment before creating or reindexing the profile.
- The service is registered as a keyed
IVectorSearchServiceusingElasticsearchConstants.ProviderName. - Keep document storage separate from indexing. Azure Blob Storage is optional and does not replace this provider.
- Install the package in the web or startup project and keep Elasticsearch connection secrets outside recipes and source control.
Feature registration
| Registration | Purpose |
|---|---|
AIDocumentElasticsearchIndexProfileHandler |
Defines chunk fields, dense vectors, and default textual fields. |
AIDocumentElasticsearchDocumentIndexHandler |
Maps document chunk records into Elasticsearch documents. |
ElasticsearchVectorSearchService |
Runs filtered k-nearest-neighbor chunk retrieval. |
AddElasticsearchIndexingSource |
Adds AI Documents (Elasticsearch) to Search → Indexing. |
Enable document indexing
{
"steps": [
{
"name": "Feature",
"enable": [
"CrestApps.OrchardCore.AI.Documents.ChatInteractions",
"CrestApps.OrchardCore.AI.Documents.Elasticsearch",
"OrchardCore.Elasticsearch"
],
"disable": []
}
]
}
Enable CrestApps.OrchardCore.AI.Documents.Pdf or
CrestApps.OrchardCore.AI.Documents.OpenXml separately for optional extraction
support. These processor features are not required by Elasticsearch itself.
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.
- 11d ago First seen · 151 lines · 131 tokens per session scan A 601b5d20cf10
orchardcore-ai-documents-elasticsearch is a skill published in the GitHub repository CrestApps/CrestApps.AgentSkills (13 stars, last pushed 13d ago), licensed MIT. It adds 131 tokens to every session and 1,455 once invoked, about $0.0007 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 2026-08-30.
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