Skill: athola/nm-imbue-latent-space-engineering (version 1.0.2)

--- name: latent-space-engineering description: | Shape agent behavior through instruction framing, emotional priming, and style transfer rather than information density alone version: 1.9.5 triggers: - prompt-engineering - agent-behavior - instruction-framing - style-transfer - review-optimization metadata: {"openclaw": {"homepage": "https://github.com/athola/claude-night-market/tree/master/plugins/imbue", "emoji": "\ud83e\udd9e", "requires": {"config": ["night-market.modules/emotional-framing.md", "night-market.modules/style-gene-transfer.md", "night-market.modules/competitive-review.md"]}}} source: claude-night-market source_plugin: imbue --- > **Night Market Skill** — ported from [claude-night-market/imbue](https://github.com/athola/claude-night-market/tree/master/plugins/imbue). For the full experience with agents, hooks, and commands, install the Claude Code plugin. # Latent Space Engineering Shape agent behavior by framing instructions for optimal performance. Distinct from context engineering (packing the right information), this skill addresses HOW instructions are framed to put agents in productive mental states. ## When To Use - Composing agent dispatch prompts - Writing skill instructions that guide behavior - Dispatching 3+ parallel review agents - Generating code or documentation that must match an existing style ## When NOT To Use - Packing factual context (use context-optimization) - Simple single-shot tasks with no behavioral nuance - Tasks where instruction tone is irrelevant ## Core Techniques ### 1. Emotional Framing Replace threat-based prompting with calm, confident instructions. Fear-based prompts cause rushing and corner-cutting. **Load module**: `modules/emotional-framing.md` ### 2. Style Gene Transfer Inject exemplar code or prose into context before requesting output. Agents reproduce stylistic attributes from pre-loaded samples. **Load module**: `modules/style-gene-transfer.md` ### 3. Competitive Review Frame multi-agent review dispatch with competitive incentives to increase rigor and thoroughness. **Load module**: `modules/competitive-review.md` ## Quick Reference | Technique | When | Module | |-----------|------|--------| | Emotional framing | Any agent prompt | emotional-framing | | Style gene transfer | Code/doc generation | style-gene-transfer | | Competitive review | 3+ parallel reviewers | competitive-review |

path: modules/competitive-review.md
content: ---
name: competitive-review
description: Frame multi-agent review dispatch with competitive
  incentives for increased rigor. Use when dispatching 3+ parallel
  review agents.
parent_skill: imbue:latent-space-engineering
category: methodology
estimated_tokens: 200
---

# Competitive Review Framing

## Principle

When multiple agents review the same artifact, framing the dispatch
with competitive incentives increases thoroughness and evidence
quality.

## For 3+ Agents (Competitive)

Add this to each agent's dispatch prompt:

~~~
You are one of N independent reviewers analyzing this code. Each
reviewer's findings will be compared. The most thorough and
well-evidenced findings will be prioritized for action. Focus on
depth over breadth.
~~~

## For 2 Agents (Collaborative)

Use collaborative framing instead:

~~~
You and one other reviewer will cover different angles. Your findings
will be integrated into a single report. Focus on your assigned scope.
~~~

Competitive framing adds overhead for fewer than 3 agents and can
cause redundant coverage.

## Avoiding Perverse Incentives

Thoroughness means evidence-backed and prioritized by severity, not
volume. To prevent inflated issue counts:

- Require evidence citations for each finding
- Weight findings by severity, not count
- Discard findings that lack specific code references

## Where To Apply

- `pensive` review agents (code-reviewer, etc.)
- `pr-review-toolkit` multi-agent reviews
- `attune:war-room` expert panels
- Any parallel dispatch of 3+ review subagents

## Anti-Pattern

Do NOT use competitive framing for:

- Implementation agents (cooperation > competition)
- Planning agents (synthesis > competition)
- Single-agent dispatch (no comparison possible)


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