---
name: hashgraph-online/reciprocity-offer-design
source: https://app.decimal.ai/s/hashgraph-online-reciprocity-offer-design@1/SKILL.md
source_sha256: 3f6d62622bed
---

# Reciprocity Offer Design

Use reciprocity to create real value before asking, while avoiding obligation traps. The rule is powerful because people feel pressure to repay favors, including some they did not request.

## Quick Start

1. Read `guidelines.md` to choose the smallest useful reference set.
2. Load `references/reciprocity/knowledge.md` for concepts and `references/reciprocity/rules.md` for operating rules.
3. Use `workflows/design-value-first-offer.md` for repeatable tasks.
4. For audits, surface both the active influence cue and the ethical rewrite.

## Contents

| File | Purpose |
| --- | --- |
| references/reciprocity/knowledge.md | Core concepts and source-grounded definitions |
| references/reciprocity/rules.md | Rules, boundaries, and practical guidelines |
| references/reciprocity/examples.md | Bad/better examples for applied situations |
| references/reciprocity/smells.md | Red flags and anti-patterns to detect |
| references/reciprocity/checklist.md | Fast review checklist |
| workflows/design-value-first-offer.md | Create a free or front-loaded offer that builds trust without manufacturing debt. |

## Operating Principles

- Use only honest evidence. Do not invent popularity, scarcity, credentials, endorsements, or social connection.
- Separate helping a good decision from pushing a shortcut response. If the cue is counterfeit, treat it as a red flag.
- When rewriting, preserve user agency: add context, alternatives, and enough time to decide when stakes are meaningful.

## Output Pattern

1. **Diagnosis** - name the influence principle or cue.
2. **Evidence Check** - state what proof supports or is missing from the cue.
3. **Risk** - explain manipulation, trust, or decision-quality risk.
4. **Rewrite or Recommendation** - provide an ethical alternative.

## Validation

Use the prompts in `evals/evals.json` as smoke tests. A good result identifies the relevant Influence principle, preserves user agency, and avoids fabricated evidence or coercive pressure.