Agent skill · research science · jeremylongshore
reasoning
Use BEFORE answering analytical, diagnostic, planning, or multi-step reasoning questions. Trigger phrases include "should I X or Y", "why is X happening", "what's the best approach", "what are the tradeoffs", "help me think through", "diagnose", "root cause", "plan/design X", "what are the implications of", "compare these approaches". Also fires on cross-domain analysis, strategy questions, architecture decisions, or anything requiring multiple factors to be weighed before responding. The skill calls the reasoning MCP tool to retrieve a cognitive scaffold (named failure pattern, executable procedure, suppression vectors, falsification test) the model absorbs internally before generating its response. Catches causal shortcuts, premature conclusions, generic templates, and surface pattern matching that produce confidently-wrong answers. Do NOT trigger for simple factual lookups, syntax questions, file reads, code execution, or restating the user's input.
Why this skill is useful
Adds a cognitive scaffold that enhances the AI's ability to perform complex reasoning tasks and avoid common pitfalls in analysis.
What it needs
Requires ejentum-mcp installed locally. Requires ejentum account access. About 1k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
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.
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/ejentum-reasoning