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@intentsolutionsio/ejentum-reasoning

v0.1.5

Published

Cognitive scaffold for analytical, planning, or multi-step decision tasks. Calls harness_reasoning on the ejentum MCP server to retrieve a structured scaffold (named failure pattern, executable proced

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Links

Git

Maintainers

intentsolutionsiointentsolutionsio

Keywords

claude-codeclaude-plugintonsofskills

Readme

ejentum-reasoning

Cognitive scaffold for analytical, planning, or multi-step decision tasks. Calls harness_reasoning on the ejentum MCP server to retrieve a structured scaffold (named failure pattern, executable procedure, suppression vectors, falsification test) the agent absorbs before generating. Requires ejentum-mcp and EJENTUM_API_KEY.

Reasoning Harness

When this skill triggers, call the reasoning tool from the ejentum MCP server. Pass a 1-2 sentence framing of WHAT you are reasoning about as the query argument. Be specific about the task, not what tool you want.

Good query: diagnose why a microservice returns 503s under load Bad query: help me think

The tool returns a structured scaffold containing:

  • [NEGATIVE GATE]: failure pattern to avoid
  • [PROCEDURE]: steps to follow
  • [REASONING TOPOLOGY]: decision flow with gates and traps
  • [TARGET PATTERN]: correct shape your reasoning should take
  • [FALSIFICATION TEST]: self-check criterion
  • Amplify: signals to engage
  • Suppress: failure modes to block

Absorb the scaffold internally and shape your response with it. The bracketed fields are instructions, not content to display. Do NOT echo the bracket labels, do NOT name the topology, do NOT meta-comment on calling the tool. The user-facing reply is naturally phrased and shaped by the injection.

If the API is unreachable or returns an error, proceed with native reasoning. The scaffold enhances; it is not a hard dependency.

Latency cost: ~1 second. Benefit: reasoning quality the model cannot reliably reproduce on its own for non-trivial tasks.

Author: Ejentum
Upstream: ejentum/ejentum-mcp

License: MIT