Build and manage Concordance mods for LLM generation interventions.
npx skills add https://github.com/concordance-co/quote --skill concordance-mod
Please help me install this Agent Skill. Skill: concordance-mod Source: https://github.com/concordance-co/quote/tree/main/.claude/skills/concordance-mod Command: npx skills add https://github.com/concordance-co/quote --skill concordance-mod
Developing and maintaining real-time LLM intervention mods can be complex, error-prone, and hard to share across teams; this skill provides a structured framework to create, upload, and debug Concordance mods for inference-time interventions.
Install the CLI, generate a new mod template, and begin testing your Concordance mod with the provided tooling.
High-intent search queries and answers about installing and using this skill.
To intercept and steer LLM generation during inference, you build Concordance mods using an extensible plugin framework that hooks into events like ForwardPass and Sampled to execute actions such as adjust_logits or force_tokens.
Inference-time interventions for LLMs are plugins that modify generation dynamically without retraining. You need them to enforce specific output constraints, correct errors in real-time, or apply complex control patterns like SelfPrompt.
To debug an LLM mod failing to apply force_tokens, use the Concordance CLI tooling to test your mod template, inspect event triggers, and verify that your action configurations are correctly deployed.
Yes, the Concordance framework supports backtracking and adjusting logits. Developers can implement these actions within the Sampled or ForwardPass events to dynamically alter token generation.
The best way to build complex control flows for LLM interventions is using the FlowEngine pattern, which provides an extensible architecture for orchestrating multi-step generation logic within your mods.
Yes, you need the Concordance SDK and CLI to develop and deploy mods. These tools provide the necessary templates, API integration, and testing environment required to build production-quality interventions.
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