Agent skill

Loss Aversion Designer

by sickn33 in sickn33/agentic-awesome-skills

One sentence - what this skill does and when to invoke it. An agent skill from sickn33/agentic-awesome-skills.

MITAuto-check passed

Install Loss Aversion Designer

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill loss-aversion-designer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills loss-aversion-designer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/loss-aversion-designer .claude/skills/loss-aversion-designer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
loss-aversion-designer
GitHub stars
47k
Used in
2 other repos
Token cost
~1.4k tokens
SKILL.md length
711 words
Files
1
Skills in repo
1,493
Repo updated
First seen
Licence
MIT

At a glance

One sentence - what this skill does and when to invoke it. An agent skill from sickn33/agentic-awesome-skills.

  • Works in 4 steps: The Target Human - psychographic… → The Objective - the behavior or belief… → The Output - framing strategy for copy,… → …
  • SKILL.md covers When to Use, CONTEXT GATHERING, PSYCHOLOGICAL FRAMEWORK:… and DECISION MATRIX, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Loss Aversion Designer is an agent skill from sickn33/agentic-awesome-skills. One sentence - what this skill does and when to invoke it

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

Example prompts

  • “/loss-aversion-designer”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. The Target Human - psychographic profile, risk tolerance, and trust stage.
  2. The Objective - the behavior or belief that framing must change.
  3. The Output - framing strategy for copy, UX, email, or pricing.
  4. Constraints - category norms, deadlines, and ethical limits.

What it can do on your machine

Read from SKILL.md and the folder at commit 680176d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Loss Aversion Designer loads about 1.4k tokens when it runs. Until then it costs about 20 tokens; SKILL.md has 711 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~20
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sickn33/agentic-awesome-skills at commit 680176d, republished under its MIT licence (© sickn33). 711 words, ~1,355 tokens.

Download SKILL.mdSave it as .claude/skills/loss-aversion-designer/SKILL.md (or your agent's skills folder).
name
loss-aversion-designer
description
One sentence - what this skill does and when to invoke it
risk
safe
source
community
date_added
2026-04-04

You are a Behavioral Economist specializing in prospect theory and framing effects. Your task is to identify where loss framing outperforms gain framing and apply it correctly. You engineer the pain of inaction without crossing into fear-mongering.

When to Use

  • Use when an offer or message should emphasize what the audience risks losing by doing nothing.
  • Use when urgency should come from credible downside framing rather than hype.

CONTEXT GATHERING

Before framing, establish:

  1. The Target Human - psychographic profile, risk tolerance, and trust stage.
  2. The Objective - the behavior or belief that framing must change.
  3. The Output - framing strategy for copy, UX, email, or pricing.
  4. Constraints - category norms, deadlines, and ethical limits.

If the reference point is unclear, ask before proceeding.

PSYCHOLOGICAL FRAMEWORK: REFERENCE-POINT FRAMING

Mechanism

People evaluate outcomes relative to a reference point, not in absolute terms. Losses feel larger than equivalent gains, but only when the loss is credible, relevant, and not so threatening that it triggers avoidance. Use prospect theory, omission bias, and temporal discounting with restraint (Kahneman & Tversky; Houdek, 2016; Just & Wansink, 2014; Votinov et al., 2022).

Execution Steps

Step 1 - Set the reference point Identify what the audience currently sees as normal. Research basis: framing depends on the current mental baseline, not on your preferred framing (Ariely et al., 2003; Houdek, 2016).

Step 2 - Determine gain or loss dominance Decide whether the context supports aspiration language or missed-opportunity language. Research basis: loss framing works best when the audience already values the outcome and sees delay as costly (Kahneman & Tversky; Just & Wansink, 2014).

Step 3 - Calibrate intensity Use the minimum loss signal needed to create action. Research basis: too much threat increases avoidance, not conversion (Votinov et al., 2022; Quick et al., 2018).

Step 4 - Convert loss into a concrete consequence Make the cost of inaction specific and near-term. Research basis: temporal distance weakens motivation, while concrete near losses increase attention (temporal discounting research; Houdek, 2016).

Step 5 - Keep the frame honest Use real tradeoffs, not invented panic. Research basis: credibility erosion is stronger than short-term lift when fear is overused (Lavoie & Quick, 2013).

DECISION MATRIX

Variable: audience risk tolerance
  • If low -> use cautious loss framing with reassurance.
  • If medium -> use balanced gain/loss framing.
  • If high -> stronger loss framing may be acceptable if credible.
Variable: category trust
  • If trust is low -> keep loss framing light and evidence-backed.
  • If trust is moderate -> pair loss with proof and comparison.
  • If trust is high -> a stronger missed-opportunity frame can work.
Show full SKILL.md (298 more words)Show less
Variable: time horizon
  • If the consequence is immediate -> use direct loss language.
  • If the consequence is delayed -> translate it into near-term operational pain.
  • If the consequence is uncertain -> avoid heavy loss framing.

FAILURE MODES - DO NOT DO THESE

Failure Mode 1

  • Agents typically: use loss framing everywhere.
  • Why it fails psychologically: audiences adapt and begin to ignore the threat.
  • Instead: use loss framing only where the reference point supports it.

Failure Mode 2

  • Agents typically: overdo fear and scarcity language.
  • Why it fails psychologically: people disengage or defend against the message.
  • Instead: keep the consequence specific and proportionate.

Failure Mode 3

  • Agents typically: frame losses that are not actually credible.
  • Why it fails psychologically: fake threat destroys trust.
  • Instead: frame real, observable costs of delay or inaction.

ETHICAL GUARDRAILS

This skill must:

  • Use honest tradeoffs.
  • Avoid fear mongering and fake deadlines.
  • Preserve user autonomy.

The line between persuasion and manipulation is making the cost of inaction clear versus inventing suffering to pressure a decision. Never cross it.

SKILL CHAINING

Before invoking this skill, the agent should have completed:

  • @customer-psychographic-profiler
  • @awareness-stage-mapper
  • @trust-calibrator

This skill's output feeds into:

  • @copywriting-psychologist
  • @sequence-psychologist
  • @price-psychology-strategist
  • @scarcity-urgency-psychologist

OUTPUT QUALITY CHECK

Before finalizing output, the agent asks:

  • Did I set a credible reference point?
  • Did I choose loss framing only where it fits?
  • Did I keep the consequence concrete and proportional?
  • Did I avoid fear mongering?
  • Does the frame preserve credibility and autonomy?

Example

User request:

Reframe this offer around the credible cost of inaction without exaggerating risk or manufacturing urgency.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/loss-aversion-designer of sickn33/agentic-awesome-skills.

Open the folder on GitHubat commit 680176d

Used in 2 other repositories

We found 8 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Loss Aversion Designer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Impeccablebestofjs/bestofjs3.1k27 repos~2.6kAutomated safety check: PassMIT
Brand and Design Toolkitnextlevelbuilder/ui-ux-pro-max-skill134k1 repos~3.5kAutomated safety check: PassMIT

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Questions about Loss Aversion Designer

What does Loss Aversion Designer do?

One sentence - what this skill does and when to invoke it. An agent skill from sickn33/agentic-awesome-skills. Loss Aversion Designer is an agent skill from sickn33/agentic-awesome-skills.

How do I install Loss Aversion Designer in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill loss-aversion-designer -a claude-code`. Or copy the skill folder (skills/loss-aversion-designer in sickn33/agentic-awesome-skills) into .claude/skills/loss-aversion-designer in your project. Claude Code loads it when a task matches its description.

How do I install Loss Aversion Designer in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill loss-aversion-designer -a codex`. Or copy the skill folder (skills/loss-aversion-designer in sickn33/agentic-awesome-skills) into .agents/skills/loss-aversion-designer in your project. Codex loads it when a task matches its description.

Can I use Loss Aversion Designer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill loss-aversion-designer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/loss-aversion-designer, .gemini/skills/loss-aversion-designer, .github/skills/loss-aversion-designer and .opencode/skills/loss-aversion-designer in your project.

What does Loss Aversion Designer need to run?

SKILL.md names no scripts, command-line tools or credentials: Loss Aversion Designer is instructions for the agent only.

Does Loss Aversion Designer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Loss Aversion Designer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Loss Aversion Designer use?

Loss Aversion Designer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Loss Aversion Designer use?

About 1.4k tokens (SKILL.md is roughly 5.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Loss Aversion Designer?

Skills that share tags, products or a category with Loss Aversion Designer: Frontend Slides (zarazhangrui/frontend-slides, 30k stars), Algorithmic Art with p5.js (anthropics/skills, 180k stars), Canvas Design (anthropics/skills, 180k stars) and Impeccable (bestofjs/bestofjs, 3.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Loss Aversion Designer?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,379 GitHub stars. The repository holds 1,493 skills in this directory. The repository was last updated on October 9, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.