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 agentmods add skills/cognigy/cognigy-plugin/settingsnpx skills add Cognigy/cognigy-plugin --skill settingsgit clone --depth 1 https://github.com/Cognigy/cognigy-pluginWrote 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/cognigy/cognigy-plugin/settings)<a href="https://agentmods.dev/skills/cognigy/cognigy-plugin/settings"><img src="https://agentmods.dev/badge/skills/cognigy/cognigy-plugin/settings.svg" alt="Measured on agentmods" 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 | $0.00022 | $0.01200 |
| Opus 5 | $0.00011 | $0.00600 |
| Sonnet 5 | $0.00004 | $0.00240 |
| Haiku 4.5 | $0.00002 | $0.00120 |
Grade A, and why
settings 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 5d 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Settings Guide
Manage project-level settings in Cognigy via the manage_settings tool.
Voice Preview Settings
Configure a speech provider so voice endpoints (WebRTC) can synthesize and recognize speech.
Quick Start
{
"operation": "set_voice_preview",
"projectId": "<24-char hex>",
"provider": "microsoft"
}
This auto-detects an existing speech connection for the provider. If none is found, you'll get instructions to upload a package containing one.
With explicit connection
{
"operation": "set_voice_preview",
"projectId": "<24-char hex>",
"provider": "microsoft",
"connectionId": "<connection referenceId>"
}
Supported Providers
| Provider | Connection Type |
|---|---|
microsoft |
MicrosoftSpeechProvider |
google |
GoogleSpeechProvider |
aws |
AWSSpeechProvider |
deepgram |
DeepgramSpeechProvider |
elevenlabs |
ElevenLabsSpeechProvider |
No speech connection found?
Speech connections are typically installed via Cognigy packages. To add one:
manage_packages { operation: "upload_and_inspect", projectId, filePath: "<path to package.zip>" }manage_packages { operation: "import", projectId, packageId }- Retry
manage_settings { operation: "set_voice_preview", projectId, provider }
Typical Full Workflow
create_ai_agent→ get projectIdsetup_llm→ configure LLMmanage_settings { operation: "set_voice_preview", projectId, provider: "microsoft" }→ configure speechmanage_voice_gateway { projectId, flowId }→ create voice endpoint with WebRTC
Knowledge AI Settings
Configure the project-level settings used by Knowledge Search and document parsing.
This is separate from the embedding model used by manage_knowledge to build the knowledge-store index. Do not confuse these settings:
- Embedding model: required for the knowledge store itself
- Knowledge Search model: configured here via
knowledgeSearchModelId answerExtractionModelIdis also supported by the tool, but it is usually not needed for normal AI-agent knowledge-store setups.knowledgeSearchModelIdmust reference anllm_modelfrom the same project- The accepted model type for
knowledgeSearchModelIdis instance-dependent
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.
- 5d ago First seen · 125 lines · 22 tokens per session scan A b3c3db9c5bfa
settings is a skill published in the GitHub repository Cognigy/cognigy-plugin (12 stars, last pushed yesterday), licensed MIT. It adds 22 tokens to every session and 1,200 once invoked, about $0.0001 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 2026-08-31.
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