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-model-capabilitiesgit 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-model-capabilities)<a href="https://agentmods.dev/skills/crestapps/crestapps.agentskills/orchardcore-ai-model-capabilities"><img src="https://agentmods.dev/badge/skills/crestapps/crestapps.agentskills/orchardcore-ai-model-capabilities/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-model-capabilities"><img src="https://agentmods.dev/badge/skills/crestapps/crestapps.agentskills/orchardcore-ai-model-capabilities.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 | $0.00218 | $0.03196 |
| Opus 5.5 | $0.00087 | $0.01278 |
| Sonnet 5.5 | $0.00044 | $0.00639 |
| Haiku 4.5 | $0.00022 | $0.00320 |
Grade A, and why
orchardcore-ai-model-capabilities 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 today.
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 — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchard Core AI Model Capabilities and Slots
A deployment says what its model can do (capabilities, also called trained features) and which
options it exposes (model parameters). Where a deployment gets used is a slot: each picker and each
resolver asks for a slot, and only deployments with the slot's required capability qualify. This replaces
the deployment purpose of 2.x. Everything here ships with the base CrestApps.OrchardCore.AI feature;
the types come from CrestApps.Core (CrestApps.Core.AI.Models, CrestApps.Core.AI.Deployments,
CrestApps.Core.AI.Capabilities).
Guidelines
- Declare only what the model was trained for. An undeclared capability is never offered or sent; a falsely declared one is sent and rejected by the provider.
- At least one capability is required on every deployment.
textGenerationis opt-out: a deployment with no capability metadata at all is treated as text capable. Every other capability is opt-in.- Pick deployments by slot (
AIDeploymentSlotNames), never by name pattern or provider. - Resolve the utility slot through
ResolveSlotAsyncwith the chat deployment as a fallback, not with two independent resolves joined by??.
Capabilities
Feature name (AIDeploymentFeatureNames) |
Meaning |
|---|---|
textGeneration |
Answers text chat completions |
toolCalling |
Calls tools supplied with the request |
structuredOutputs |
Returns JSON that follows a supplied schema |
streaming |
Streams response updates |
reasoning |
Reasons before answering; unlocks reasoningEffort |
textEmbedding |
Generates embedding vectors (dedicated embedding models only) |
imageInput |
Understands images (fills the vision slot) |
imageOutput |
Generates images |
audioInput, audioOutput, videoInput, videoOutput |
Accepts or produces audio or video |
speechToText |
Dedicated transcription model such as Whisper |
textToSpeech |
Dedicated speech synthesis model |
realtime |
Holds speech-to-speech sessions. Excluded from the chat and utility slots |
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.
- today First seen · 285 lines · 218 tokens per session scan A 9cf992358aa1
orchardcore-ai-model-capabilities is a skill published in the GitHub repository CrestApps/CrestApps.AgentSkills (13 stars, last pushed today), licensed MIT. It adds 218 tokens to every session and 3,196 once invoked, about $0.0009 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 2026-10-22.
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