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Grad Elm

asgard-ai-platform/grad-elm

Apply the Elaboration Likelihood Model to design persuasion strategies by matching message type to audience elaboration level. Use this skill when the user needs to craft persuasive communications, choose between argument-based and cue-based messaging, predict attitude durability after a campaign, or when they ask 'why did the message fail to persuade', 'how to change resistant attitudes', or 'should we use data or endorsements'.

2k tokens
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the whole folder, loaded on every use
2
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instructions only
0
copies elsewhere
how many repositories repackaged it
223
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/asgard-ai-platform/skills --skill grad-elm

What comes with it

1 205 bytes besides the instruction
examples/sample_scenario.md

The instruction itself

13 sections, as written by the author

Elaboration Likelihood Model (ELM)

Overview

The Elaboration Likelihood Model (Petty & Cacioppo, 1986) proposes that persuasion occurs through two distinct routes depending on the audience's motivation and ability to process a message. The central route relies on careful evaluation of argument quality, producing durable attitude change. The peripheral route relies on heuristic cues (source attractiveness, number of arguments), producing temporary and fragile attitude shifts.

When to Use

  • Designing marketing, policy, or internal communication strategies for different audience segments
  • Diagnosing why a well-reasoned message failed (audience lacked motivation/ability to process)
  • Predicting whether attitude change will persist and resist counter-persuasion
  • Choosing between investing in argument quality vs. source credibility or presentation style

When NOT to Use

  • When the goal is behavioral compliance rather than genuine attitude change (use compliance techniques)
  • For purely emotional appeals where cognitive processing models are insufficient (use affect-as-information)
  • When the audience has no prior schema on the topic and needs education before persuasion

Assumptions

IRON LAW: Attitude change via the central route is MORE durable
and resistant to counter-persuasion — but requires motivation
AND ability to process. When either is absent, only the
peripheral route is available, and its effects decay.

Key assumptions:

  • Elaboration exists on a continuum from low to high, not a strict binary
  • The same variable (e.g., source expertise) can serve as argument, cue, or affect elaboration direction depending on context
  • Central-route attitudes predict behavior better than peripheral-route attitudes

Methodology

Step 1 — Assess Audience Elaboration Likelihood

| Factor | High Elaboration | Low Elaboration |

|--------|-----------------|-----------------|

| Personal relevance | High (topic matters to them) | Low (distant from self) |

| Need for cognition | High (enjoys thinking) | Low (avoids effortful thought) |

| Prior knowledge | Sufficient to evaluate arguments | Insufficient to engage deeply |

| Distraction level | Low (can focus) | High (divided attention) |

| Time pressure | Low (can deliberate) | High (must decide quickly) |

Step 2 — Select Persuasion Route

  • Central route (high elaboration): invest in strong, evidence-based arguments
  • Peripheral route (low elaboration): invest in heuristic cues and presentation
  • Mixed (moderate elaboration): use both strong arguments and peripheral cues

Step 3 — Design the Message

Central route elements:

  • Logical argument structure, data, evidence
  • Two-sided messaging (acknowledge counterarguments)
  • Strong argument quality (scrutiny-resistant claims)

Peripheral route elements:

  • Source credibility, attractiveness, likability
  • Social proof (endorsements, testimonials, popularity)
  • Message length and formatting cues
  • Emotional tone and narrative framing

Step 4 — Predict Attitude Outcomes

| Route | Durability | Behavior Prediction | Counter-Persuasion Resistance |

|-------|-----------|--------------------|-----------------------------|

| Central | High | Strong | High |

| Peripheral | Low | Weak | Low |

Output Format

## ELM Persuasion Strategy: [Context]

### Audience Elaboration Assessment
| Segment | Motivation | Ability | Elaboration Level |
|---------|-----------|---------|-------------------|
| [segment] | [High/Low] | [High/Low] | [High/Moderate/Low] |

### Route Selection: [Central / Peripheral / Mixed]

### Message Design
- Primary arguments: [if central route]
- Peripheral cues: [if peripheral route]
- Source selection: [credibility/attractiveness rationale]

### Predicted Outcomes
- Attitude durability: [High/Medium/Low]
- Behavioral impact: [Strong/Moderate/Weak]
- Counter-persuasion vulnerability: [High/Medium/Low]

### Risk Mitigation
- [What happens if audience elaboration is misjudged]

Gotchas

  • The same variable can play multiple roles: source expertise can be a peripheral cue (low elaboration) or bias argument processing direction (high elaboration)
  • Strong arguments under central processing can backfire if they are perceived as manipulative — reactance theory applies
  • Peripheral cues are not inherently inferior; in low-stakes decisions, they are efficient and adaptive
  • ELM assumes a relatively cognitive model of persuasion; purely visceral or embodied persuasion is not well-captured
  • Cultural differences affect what counts as a strong argument vs. a peripheral cue (e.g., authority weight varies by culture)
  • Repeated exposure can shift processing from peripheral to central as familiarity grows — one-shot message design is insufficient for campaigns

References

  • Petty, R. E. & Cacioppo, J. T. (1986). *Communication and persuasion: central and peripheral routes to attitude change*. Springer-Verlag.
  • Petty, R. E. & Wegener, D. T. (1999). The elaboration likelihood model: current status and controversies. In S. Chaiken & Y. Trope (Eds.), *Dual-process theories in social psychology* (pp. 37-72). Guilford Press.
  • Petty, R. E., Brinol, P. & Priester, J. R. (2009). Mass media attitude change. In J. Bryant & M. B. Oliver (Eds.), *Media effects: advances in theory and research* (3rd ed., pp. 125-164). Routledge.

How to use it

Copy the folder

Take asgard-ai-platform/grad-elm from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

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