Apply the Theory of Planned Behavior to predict behavioral intentions from attitudes, subjective norms, and perceived behavioral control, and identify intervention leverage points. Use this skill when the user needs to predict adoption of a new behavior, diagnose why an intended behavior does not occur, design behavior change campaigns, or when they ask 'why do people not follow through', 'what predicts behavior change', or 'how to increase adoption rates'.
npx skills add https://github.com/asgard-ai-platform/skills --skill grad-tpb
The Theory of Planned Behavior (Ajzen, 1991) extends the Theory of Reasoned Action by adding perceived behavioral control as a predictor of both intention and behavior. Behavioral intention is determined by three factors: attitude toward the behavior, subjective norms, and perceived behavioral control. Intention is the proximal predictor of behavior, moderated by actual control.
IRON LAW: Intention predicts behavior ONLY when perceived
behavioral control is high — without actual control, intention
alone is insufficient. The intention-behavior gap widens as
volitional control decreases.
Key assumptions:
Define the behavior precisely using the TACT framework:
| Predictor | Definition | Underlying Beliefs |
|-----------|------------|--------------------|
| Attitude | Favorable/unfavorable evaluation of performing the behavior | Behavioral beliefs (outcomes x evaluations) |
| Subjective norms | Perceived social pressure to perform or not perform | Normative beliefs (referents x motivation to comply) |
| Perceived behavioral control (PBC) | Perceived ease or difficulty of performing the behavior | Control beliefs (facilitators/barriers x power) |
## TPB Analysis: [Target Behavior]
### Behavior Specification (TACT)
- Target: [object/person]
- Action: [specific behavior]
- Context: [situation]
- Time: [time frame]
### Predictor Assessment
| Predictor | Score | Key Beliefs | Intervention Potential |
|-----------|-------|-------------|----------------------|
| Attitude | [+/-] | [salient beliefs] | [High/Medium/Low] |
| Subjective norms | [+/-] | [key referents] | [High/Medium/Low] |
| PBC | [+/-] | [barriers/facilitators] | [High/Medium/Low] |
### Intention Strength: [Strong/Moderate/Weak]
### Intention-Behavior Gap Risk: [High/Medium/Low]
### Recommended Intervention
1. [Primary lever: weakest predictor]
2. [Implementation intention strategy]
3. [Barrier removal or facilitator enhancement]
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.
Identifies high-quality leads for your product or service by analyzing your business, searching for target companies, and providing actionable contact strategies. Perfect for sales, business development, and marketing professionals.
Analyzes your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalized growth report to your Slack DMs.
Official Google SEO guide covering search optimization, best practices, Search Console, crawling, indexing, and improving website search visibility based on official Google documentation
Fix PageSpeed Insights/Lighthouse accessibility "!" errors caused by contrast audit failures (CSS filters, OKLCH/OKLAB, low opacity, gradient text, image backgrounds). Use for accessibility-driven SEO/performance debugging and remediation.
Complete App Store Optimization (ASO) toolkit for researching, optimizing, and tracking mobile app performance on Apple App Store and Google Play Store
Elite frontend image-direction skill for generating premium, conversion-aware website design references. CRITICAL OUTPUT RULE — generate ONE separate horizontal image FOR EVERY section. A landing page with 8 sections produces 8 images. Never compress multiple sections into one image. Enforces composition variety (not always left-text / right-image), background-image freedom, varied CTAs, varied hero scales (giant / mid / mini minimalist), narrative concept spine, second-read moments, and a single consistent palette across all images. Optimized for landing pages, marketing sites, and product comps that developers or coding models can accurately recreate.
Take asgard-ai-platform/grad-tpb from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.