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-connectionsgit 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-connections)<a href="https://agentmods.dev/skills/crestapps/crestapps.agentskills/orchardcore-ai-connections"><img src="https://agentmods.dev/badge/skills/crestapps/crestapps.agentskills/orchardcore-ai-connections/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-connections"><img src="https://agentmods.dev/badge/skills/crestapps/crestapps.agentskills/orchardcore-ai-connections.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 156 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 288 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00201 | $0.02494 |
| Opus 5 | $0.00101 | $0.01247 |
| Sonnet 5 | $0.00040 | $0.00499 |
| Haiku 4.5 | $0.00020 | $0.00249 |
Grade A, and why
orchardcore-ai-connections 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 10d 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 — 306 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchard Core AI Connection Management - Prompt Templates
Configure AI Provider Connections
You are an Orchard Core expert specializing in CrestApps AI provider connection management. Guide users through setting up, configuring, and managing AI provider connections using the admin UI, recipes, and deployment plans.
Guidelines
- The AI Connection Management feature provides a centralized admin UI for managing connections to AI providers.
- Enable the
CrestApps.OrchardCore.AI.ConnectionManagementfeature to access the connection management UI. - Each provider (OpenAI, Azure OpenAI, Ollama, Azure AI Inference) requires its own NuGet package installed in the web project.
- API keys are encrypted at rest using the ASP.NET Core Data Protection system.
- Configuration-backed connections (defined in
appsettings.json) are read-only in the admin UI. - Creating, editing, or deleting a connection triggers a shell release (tenant reload).
- The
ManageProviderConnectionspermission controls access to the connection management UI and is granted to theAdministratorrole by default. - For configuration-backed Ollama connections, use a flat
Endpointproperty on the connection entry rather than a nested metadata object. - When exporting connections via deployment, API keys are automatically stripped for security.
Feature IDs
| Feature | Feature ID |
|---|---|
| AI Connection Management | CrestApps.OrchardCore.AI.ConnectionManagement |
| OpenAI Provider | CrestApps.OrchardCore.OpenAI |
| Azure OpenAI Provider | CrestApps.OrchardCore.OpenAI.Azure |
| Ollama Provider | CrestApps.OrchardCore.Ollama |
| Azure AI Inference Provider | CrestApps.OrchardCore.AzureAIInference |
NuGet Packages
Install the connection management and at least one provider package in your web/startup project:
| Package | Description |
|---|---|
CrestApps.OrchardCore.AI |
Core AI services and connection management UI |
CrestApps.OrchardCore.OpenAI |
OpenAI provider (GPT models via OpenAI API) |
CrestApps.OrchardCore.OpenAI.Azure |
Azure OpenAI provider (GPT models via Azure) |
CrestApps.OrchardCore.Ollama |
Ollama provider (local/self-hosted models) |
CrestApps.OrchardCore.AzureAIInference |
Azure AI Inference provider (GitHub Models and Azure AI) |
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.
- 10d ago First seen · 306 lines · 201 tokens per session scan A bd78c49cacf5
orchardcore-ai-connections is a skill published in the GitHub repository CrestApps/CrestApps.AgentSkills (13 stars, last pushed 12d ago), licensed MIT. It adds 201 tokens to every session and 2,494 once invoked, about $0.0010 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.
Other skills, from other repositories
mongodb-mcp-v3-migration
Migrates external consumer code from the mongodb-mcp-server v1/v2 single-package API to the v3 scoped-package structure. In v3, mongodb-mcp-server is a binary-only package (npx / MCPB); library embedding uses @mongodb-js/mcp-cli, @mongodb-js/mcp-core, @mongodb-js/mcp-http-runners, @mongodb-js/mcp-tools-, and the other…
gdal-api
Use when programming against GDAL/OGR in C, C++, Python, or .NET for raster/vector I/O, coordinate transformation, or custom geospatial algorithms. GDAL API: low-level programming interface for reading/writing 70+ geospatial formats.
data-engineering
Transforms, validates, loads data in ETL pipelines. Use when building scrapers, validating NDJSON feeds, or importing data into CMS/DB targets.
aws-generative-ai-developer
Build Amazon Bedrock and serverless generative AI applications using Lambda, API Gateway, Step Functions, EventBridge, S3, DynamoDB, SQS, Guardrails, and IAM. Prefer this for serverless GenAI app design and implementation; prefer aws-agentcore for AgentCore runtime, aws-bedrock-agent-security-governor for deep Bedrock…
flowllm-dev
FlowLLM repository development guidance. Use when working in the flowllm codebase to implement, debug, test, review, or document FlowLLM runtime behavior, including CLI/client calls, services, application wiring, jobs, steps, components, configuration, streaming, registry registration, and tests.
scalix-ai
Run AI inference on Scalix Cloud through the OpenAI-compatible API — chat completions, streaming, and the Scalix Lumio model family. Use when the user wants LLM inference on Scalix, asks about Scalix AI or Lumio models, or wants to point existing OpenAI-compatible code at Scalix.