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Ejentum

Retrieve a task-matched cognitive operation from the Ejentum Reasoning Harness and inject it into the next LLM step. Each operation is engineered in two layers: a natural-language procedure plus an executable reasoning topology (graph DAG with gates, parallel branches, and meta-cognitive exits). Eight modes: four dynamic (reasoning, code, anti-deception, memory) plus four adaptive (adaptive-reasoning, adaptive-code, adaptive-anti-deception, adaptive-memory) that pre-fit the operation to your task via an adapter LLM. Dynamic available on all tiers including the 30-day free trial; adaptive requires Go or Super.

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Reasoning Harness

AI-generated

Summary

Retrieves a task-matched reasoning scaffold from the Ejentum Reasoning Harness API for analytical, diagnostic, planning, or multi-step tasks, so it can be injected into a later LLM step.

Inputs

  • query (required) — Short description of the task you are about to perform (e.g. "diagnose intermittent 503s under load"). Used to retrieve the best-matched cognitive scaffold. Trimmed; empty or whitespace-only values throw an error for that item.

Output shape

One output item per input item, with json containing mode ("reasoning"), the trimmed query, and response (the raw JSON returned by the Ejentum API). Each item is paired with its input item.

Sends a POST to the credential's base URL (default https://api.ejentum.com/harness/) with body {query, mode} using the ejentumApi credential. The shape of response is defined by the API and not by the node. With Continue On Fail enabled, failed items return json {error: message}. The node can also be used as an AI tool. This dynamic mode is available on all tiers.

Examples

Example 1: Give an AI agent a reasoning scaffold before it diagnoses a production incident.

Operation: Reasoning Harness; Query: "diagnose intermittent 503s under load". Pass the response field into the next LLM node's prompt.

Example 2: Build the query dynamically from each incoming item.

Operation: Reasoning Harness; Query: expression such as {{ $json.taskDescription }}, so one scaffold is retrieved per item.

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