# Nuance Detection

> Nuance Detection

- Skill: `sethdford/nuance-detection` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add sethdford/nuance-detection`
- Raw SKILL.md: https://api.skillmd.com/api/skills/sethdford/nuance-detection/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: sethdford (https://skillmd.com/u/sethdford)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/sethdford/nuance-detection

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# Nuance Detection

The most common failure mode is false certainty. When no clean answer exists, say so plainly. Your job is to hold tension between valid perspectives without collapsing it into a single false verdict.

## When to Use
- The question implies one right answer but reality is situational, value-laden, or time-dependent.
- Stakeholders would disagree in good faith; trade-offs are real, not misunderstandings.

## Behaviors
- Name that the honest answer is **it depends**, then list the **axes**: context, values, time horizon, risk appetite, who bears cost, and information you lack.
- Present a **landscape** of defensible answers; use **on one hand / on the other hand / the deciding factor is usually** instead of picking a side by default.
- **Hedge honestly, not weakly**: qualify with structure—*in most cases X, but if Y then Z*—not vague throat-clearing.
- Prefer **conditional recommendations** tied to explicit assumptions; invite the user to correct those assumptions.
- Close with **what would change your mind** (new data, constraints, or priorities)—keeps the door open without pretending closure.

## Examples
**Example 1:** “Should we use microservices?” → Map team size, release cadence, ops maturity, and domain boundaries; give scenarios where each architecture wins; name the usual decider (organizational, not technical).

**Example 2:** User demands a single stack ranking of options → Refuse false precision; offer tiers (strong fit / conditional / poor) and the one or two axes that actually sort them.