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Agent skill

Algo Price Van Westendorp

by asgard-ai-platform in asgard-ai-platform/skills

Conduct Van Westendorp Price Sensitivity Meter analysis to identify acceptable price ranges.

MITAuto-check passed

Install Algo Price Van Westendorp

skills CLI
$ npx skills add asgard-ai-platform/skills --skill algo-price-van-westendorp -a claude-code

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

GitHub CLI
$ gh skill install asgard-ai-platform/skills algo-price-van-westendorp --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/asgard-ai-platform/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/algo-price-van-westendorp .claude/skills/algo-price-van-westendorp && 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
algo-price-van-westendorp
GitHub stars
242
Token cost
~1.1k tokens
SKILL.md length
431 words
Files
4 (incl. references)
Skills in repo
207
Repo updated
First seen
Licence
MIT

At a glance

Conduct Van Westendorp Price Sensitivity Meter analysis to identify acceptable price ranges.

  • Works in 4 steps: Input Validation → Core Algorithm → Verification → …
  • The user needs to determine price boundaries for a new product
  • SKILL.md covers Overview, When to Use, Algorithm and Output Format, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Algo Price Van Westendorp is an agent skill from asgard-ai-platform/skills. Conduct Van Westendorp Price Sensitivity Meter analysis to identify acceptable price ranges. Use this skill when the user needs to determine price boundaries for a new product, find the optimal and indifference price points, or survey-based pricing research — even if they say 'what should we charge', 'price sensitivity survey', or 'acceptable price range'.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `examples/sample_scenario.md`, `references/nms-extension.md` and `references/survey-design.md`).

The repository describes itself as: 301 open-source coding agent skills across 22 domains — methodology, judgment & gotchas packaged as Claude Agent Skills for the Asgard AI Platform. The licence is MIT.

When your agent uses it

  • The user needs to determine price boundaries for a new product
  • Find the optimal and indifference price points
  • Survey-based pricing research — even if they say what should we charge
  • Price sensitivity survey

Example prompts

  • “what should we charge”
  • “price sensitivity survey”
  • “acceptable price range”
  • “/algo-price-van-westendorp”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Input Validation
  2. Core Algorithm
  3. Verification
  4. Output

What it can do on your machine

Read from SKILL.md and the folder at commit 4e7f4f8. 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 (its code samples are json).

    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

Algo Price Van Westendorp loads about 1.1k tokens when it runs, and up to ~5.7k if it reads all its reference files. Until then it costs about 96 tokens; SKILL.md has 431 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~96
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.7k

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 asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 431 words, ~1,108 tokens.

Download SKILL.mdSave it as .claude/skills/algo-price-van-westendorp/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
algo-price-van-westendorp
description
Conduct Van Westendorp Price Sensitivity Meter analysis to identify acceptable price ranges. Use this skill when the user needs to determine price boundaries for a new product, find the optimal and indifference price points, or survey-based pricing research — even if they say 'what should we charge', 'price sensitivity survey', or 'acceptable price range'.
metadata.category
WP-39 定價演算法
metadata.tags
pricing, van-westendorp, survey, price-sensitivity

Van Westendorp Price Sensitivity Meter

Overview

Van Westendorp PSM uses four price perception questions to identify an acceptable price range through intersection analysis. Produces: Point of Marginal Cheapness (PMC), Point of Marginal Expensiveness (PME), Indifference Price Point (IPP), and Optimal Price Point (OPP). Requires survey data from 100+ respondents.

When to Use

Trigger conditions:

  • Setting initial price for a new product or service
  • Identifying the acceptable price range from consumer perception
  • Quick pricing research without complex experimental design

When NOT to use:

  • When you need to measure attribute trade-offs (use conjoint analysis)
  • When you need demand curve estimation (use price elasticity)

Algorithm

IRON LAW: Van Westendorp Identifies an ACCEPTABLE Range, Not Optimal Price
It doesn't account for competition, costs, or willingness to pay at
scale. It tells you WHERE prices are perceived as reasonable, not
what maximizes revenue. Use as input to pricing strategy, not as the
final answer.
Phase 1: Input Validation

Survey 100+ target customers with four questions at various price points:

  1. Too cheap (quality suspect)? 2. A bargain (great deal)? 3. Getting expensive (but would consider)? 4. Too expensive (would not buy)? Gate: 100+ responses, all four curves plottable.
Phase 2: Core Algorithm
  1. For each price point, compute cumulative percentages for each question
  2. Plot four curves: "too cheap" (descending), "cheap/bargain" (descending), "expensive" (ascending), "too expensive" (ascending)
  3. Find intersections:
    • OPP = intersection of "too cheap" and "too expensive" (optimal price point)
    • IPP = intersection of "cheap" and "expensive" (indifference price point)
    • PMC = intersection of "too cheap" and "expensive" (marginal cheapness)
    • PME = intersection of "cheap" and "too expensive" (marginal expensiveness)
  4. Acceptable range = [PMC, PME]
Phase 3: Verification

Check: PMC < OPP < IPP < PME (expected ordering). All intersections exist within surveyed range. Gate: Four-point ordering is logical, range is commercially viable.

Phase 4: Output

Return price points and acceptable range.

Output Format

json
{
  "price_points": {"opp": 299, "ipp": 349, "pmc": 199, "pme": 449},
  "acceptable_range": {"min": 199, "max": 449},
  "metadata": {"respondents": 250, "currency": "TWD", "product": "..."}
}

Examples

Show full SKILL.md (173 more words)Show less
Sample I/O

Input: 200 survey responses for a SaaS product, price range tested: $5-$50/month Expected: PMC=$12, OPP=$18, IPP=$22, PME=$35. Acceptable range: $12-$35.

Edge Cases
InputExpectedWhy
Curves don't intersectExtend surveyed rangePrice points tested were too narrow
IPP < OPPUnusual but possibleCheck data quality, may indicate confused respondents
Very wide rangeLow price sensitivityProduct category has high tolerance

Gotchas

  • Hypothetical bias: People say they'd pay more than they actually would. Van Westendorp systematically overestimates willingness to pay.
  • No competitive context: Respondents answer in isolation. Real purchase decisions consider alternatives. Supplement with competitive analysis.
  • Sample representativeness: Results are only valid for the surveyed population. B2B vs B2C, early adopters vs mainstream — all give different ranges.
  • Newton-Miller-Smith extension: Add purchase intent questions at OPP and IPP for more actionable revenue estimates. Standard Van Westendorp alone lacks this.
  • Product must be understood: Respondents need to understand what they're pricing. For novel products, include a clear concept description.

References

  • For Newton-Miller-Smith purchase intent extension, see references/nms-extension.md
  • For survey design best practices, see references/survey-design.md

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

Files

SKILL.md and 3 other files (references) in algo-price-van-westendorp of asgard-ai-platform/skills.

  • SKILL.md
  • examples/sample_scenario.md
  • references/nms-extension.md
  • references/survey-design.md

Open the folder on GitHubat commit 4e7f4f8

Compare with similar skills

Algo Price Van Westendorp 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.

Algo Price Van Westendorp compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Algo Price Van Westendorp this skillasgard-ai-platform/skills242—~1.1kAutomated safety check: PassMIT
Pricingsickn33/agentic-awesome-skills47k1 repos~1.9kAutomated safety check: PassMIT
Pricing Strategistalirezarezvani/claude-skills28k—~2.3kAutomated safety check: PassMIT
Pricing Sensitivity Modelmohitagw15856/pm-claude-skills1.4k—~1kAutomated safety check: PassMIT
Pricing Strategyphuryn/pm-skills27k—~913Automated safety check: PassMIT
Pricing Strategyalirezarezvani/claude-skills28k1 repos~3.5kAutomated safety check: PassMIT

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Questions about Algo Price Van Westendorp

What does Algo Price Van Westendorp do?

Conduct Van Westendorp Price Sensitivity Meter analysis to identify acceptable price ranges. Algo Price Van Westendorp is an agent skill from asgard-ai-platform/skills. Conduct Van Westendorp Price Sensitivity Meter analysis to identify acceptable price ranges.

When should I use Algo Price Van Westendorp?

Algo Price Van Westendorp fits situations like: the user needs to determine price boundaries for a new product; find the optimal and indifference price points; survey-based pricing research — even if they say what should we charge; price sensitivity survey.

How do I install Algo Price Van Westendorp in Claude Code?

Run `npx skills add asgard-ai-platform/skills --skill algo-price-van-westendorp -a claude-code`. Or copy the skill folder (algo-price-van-westendorp in asgard-ai-platform/skills) into .claude/skills/algo-price-van-westendorp in your project. Claude Code loads it when a task matches its description.

How do I install Algo Price Van Westendorp in Codex?

Run `npx skills add asgard-ai-platform/skills --skill algo-price-van-westendorp -a codex`. Or copy the skill folder (algo-price-van-westendorp in asgard-ai-platform/skills) into .agents/skills/algo-price-van-westendorp in your project. Codex loads it when a task matches its description.

Can I use Algo Price Van Westendorp 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 asgard-ai-platform/skills --skill algo-price-van-westendorp -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/algo-price-van-westendorp, .gemini/skills/algo-price-van-westendorp, .github/skills/algo-price-van-westendorp and .opencode/skills/algo-price-van-westendorp in your project.

What does Algo Price Van Westendorp need to run?

SKILL.md names no scripts, command-line tools or credentials: Algo Price Van Westendorp is instructions for the agent only.

Does Algo Price Van Westendorp 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 Algo Price Van Westendorp 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 Algo Price Van Westendorp use?

Algo Price Van Westendorp 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 Algo Price Van Westendorp use?

About 1.1k tokens (SKILL.md is roughly 4.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.5k tokens, read only when the agent opens those files.

What are the alternatives to Algo Price Van Westendorp?

Skills that share tags, products or a category with Algo Price Van Westendorp: Pricing (sickn33/agentic-awesome-skills, 47k stars), Pricing Strategist (alirezarezvani/claude-skills, 28k stars), Pricing Sensitivity Model (mohitagw15856/pm-claude-skills, 1.4k stars) and Pricing Strategy (phuryn/pm-skills, 27k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Algo Price Van Westendorp?

asgard-ai-platform (a GitHub organization) maintains it in asgard-ai-platform/skills, which has 242 GitHub stars. The repository holds 207 skills in this directory. The repository was last updated on June 6, 2026.

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