Setting Pricing
GTM-Strategist/gtm-strategist-skills
A skill your agent uses when the user asks about pricing strategy, how to price their product, willingness-to-pay research, or business model design.
Design bundle pricing strategies using pure bundling, mixed bundling, and consumer surplus analysis.
Install Algo Price Bundle
$ npx skills add asgard-ai-platform/skills --skill algo-price-bundle -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install asgard-ai-platform/skills algo-price-bundle --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/algo-price-bundle .claude/skills/algo-price-bundle && rm -rf skills-srcUse ~/.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/
Install the "algo-price-bundle" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-price-bundle into .claude/skills/algo-price-bundle/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-price-bundle", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/asgard-ai-platform/skills/tree/main/algo-price-bundleType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add asgard-ai-platform/skills --skill algo-price-bundle -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install asgard-ai-platform/skills algo-price-bundle --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/algo-price-bundle .agents/skills/algo-price-bundle && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "algo-price-bundle" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-price-bundle into .agents/skills/algo-price-bundle/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-price-bundle", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add asgard-ai-platform/skills --skill algo-price-bundle -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install asgard-ai-platform/skills algo-price-bundle --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/algo-price-bundle .cursor/skills/algo-price-bundle && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "algo-price-bundle" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-price-bundle into .cursor/skills/algo-price-bundle/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-price-bundle", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/asgard-ai-platform/skills.git --path algo-price-bundle--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add asgard-ai-platform/skills --skill algo-price-bundle -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install asgard-ai-platform/skills algo-price-bundle --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/algo-price-bundle .gemini/skills/algo-price-bundle && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "algo-price-bundle" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-price-bundle into .gemini/skills/algo-price-bundle/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-price-bundle", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install asgard-ai-platform/skills algo-price-bundleInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add asgard-ai-platform/skills --skill algo-price-bundle -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/algo-price-bundle .github/skills/algo-price-bundle && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "algo-price-bundle" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-price-bundle into .github/skills/algo-price-bundle/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-price-bundle", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add asgard-ai-platform/skills --skill algo-price-bundle -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install asgard-ai-platform/skills algo-price-bundle --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/algo-price-bundle .opencode/skills/algo-price-bundle && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "algo-price-bundle" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-price-bundle into .opencode/skills/algo-price-bundle/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-price-bundle", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
algo-price-bundle- GitHub stars
- 242
- Token cost
- ~1.1k tokens
- SKILL.md length
- 412 words
- Files
- 4 (incl. references)
- Skills in repo
- 207
- Repo updated
- First seen
- Licence
- MIT
At a glance
Design bundle pricing strategies using pure bundling, mixed bundling, and consumer surplus analysis.
- Works in 4 steps: Input Validation → Core Algorithm → Verification → …
- The user needs to set prices for product bundles
- 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 Bundle is an agent skill from asgard-ai-platform/skills. Design bundle pricing strategies using pure bundling, mixed bundling, and consumer surplus analysis. Use this skill when the user needs to set prices for product bundles, determine whether bundling increases profit, or analyze unbundling opportunities — even if they say 'should we bundle these products', 'bundle pricing', or 'package deal pricing'.
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/bundling-theory.md` and `references/multi-product-pricing.md`).
It sits in Sales & Support, covering Pricing strategy. 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 set prices for product bundles
- Determine whether bundling increases profit
- Analyze unbundling opportunities — even if they say should we bundle these products
- Package deal pricing
Example prompts
- “should we bundle these products”
- “bundle pricing”
- “package deal pricing”
- “/algo-price-bundle”
Workflow steps
4 steps, taken from the step headings in SKILL.md.
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 Bundle loads about 1.1k tokens when it runs, and up to ~7k if it reads all its reference files. Until then it costs about 92 tokens; SKILL.md has 412 words of instructions outside code blocks.
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). 412 words, ~1,107 tokens.
Download SKILL.mdSave it as
.claude/skills/algo-price-bundle/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- algo-price-bundle
- description
- Design bundle pricing strategies using pure bundling, mixed bundling, and consumer surplus analysis. Use this skill when the user needs to set prices for product bundles, determine whether bundling increases profit, or analyze unbundling opportunities — even if they say 'should we bundle these products', 'bundle pricing', or 'package deal pricing'.
- metadata.category
- WP-39 定價演算法
- metadata.tags
- pricing, bundling, consumer-surplus, product-strategy
Bundle Pricing Strategy
Overview
Bundle pricing sells multiple products together at a combined price, extracting consumer surplus by averaging valuations across products. Works when customers have heterogeneous, negatively correlated valuations. Three types: pure bundling (bundle only), mixed bundling (bundle + individual), unbundling.
When to Use
Trigger conditions:
- Deciding whether to bundle products/services together
- Setting bundle price relative to individual prices
- Analyzing whether a current bundle should be unbundled
When NOT to use:
- When products have independent demand with no valuation correlation (bundling adds no value)
- When regulations prohibit tying arrangements
Algorithm
IRON LAW: Bundling Increases Profit ONLY With NEGATIVELY CORRELATED Valuations
If ALL customers value the same items highly, bundling adds no surplus.
Bundling works when: Customer A values Product 1 high + Product 2 low,
while Customer B values Product 1 low + Product 2 high. The bundle
price captures both at a middle price neither would pay for their
low-value item alone.Phase 1: Input Validation
Collect: individual product valuations (or willingness to pay) per customer segment. Compute correlation of valuations across products. Gate: Valuation data available, correlation is negative or mixed.
Phase 2: Core Algorithm
- Compute optimal individual prices: maximize Σ(revenue per product)
- Compute optimal bundle price: find price that maximizes bundle revenue given joint valuation distribution
- Compare: pure bundling revenue, mixed bundling revenue, individual pricing revenue
- Mixed bundling: set bundle price < sum of individual prices; discount = bundle incentive
Phase 3: Verification
Check: mixed bundling should weakly dominate both pure bundling and individual pricing (Adams & Yellen, 1976). If not, review valuation assumptions. Gate: Mixed bundling profit ≥ max(pure bundling, individual pricing).
Phase 4: Output
Return optimal pricing strategy with profit projections.
Output Format
{
"recommendation": "mixed_bundling",
"prices": {"product_a": 299, "product_b": 199, "bundle_ab": 399},
"profit_comparison": {"individual": 45000, "pure_bundle": 48000, "mixed_bundle": 52000},
"metadata": {"segments": 3, "valuation_correlation": -0.35}
}Examples
Sample I/O
Input: Product A (WTP: Seg1=$80, Seg2=$30), Product B (WTP: Seg1=$30, Seg2=$70). Each segment has 100 customers. Expected: Individual optimal: A=$80, B=$70, revenue=$15K. Bundle at $100: both segments buy, revenue=$20K. Bundling wins.
Show full SKILL.md (163 more words)Show less
Edge Cases
| Input | Expected | Why |
|---|---|---|
| Perfectly positive correlation | Individual pricing wins | All customers value both high or both low |
| One product is free good | Bundle = premium + free | Common in software (free trial + paid add-on) |
| 10+ products in bundle | Mixed bundling complex | Too many combinations — use tiered bundles |
Gotchas
- Cannibalization: The bundle may cannibalize high-WTP customers who would have bought individually at higher total. Mixed bundling mitigates this.
- Perceived value: Bundle discount must be salient. A $499 bundle of $299+$299 products (16% off) is better perceived than $499 for two $260 products.
- Marginal cost matters: Zero marginal cost products (software, digital) benefit most from bundling. Physical goods with high COGS have tighter margins.
- Complexity cost: Too many bundle options create choice paralysis. Limit to 2-3 bundle tiers.
- Regulatory tying: In some markets, forcing purchase of one product to get another is illegal (antitrust). Ensure bundle is a discount, not a requirement.
References
- For Adams-Yellen bundling theory, see
references/bundling-theory.md - For multi-product pricing optimization, see
references/multi-product-pricing.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-bundle of asgard-ai-platform/skills.
- SKILL.md
- examples/sample_scenario.md
- references/bundling-theory.md
- references/multi-product-pricing.md
Open the folder on GitHubat commit 4e7f4f8
Compare with similar skills
Algo Price Bundle 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Algo Price Bundle this skillasgard-ai-platform/skills | 242 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Setting PricingGTM-Strategist/gtm-strategist-skills | 264 | — | ~5.4k | Automated safety check: Pass | MIT | |
| AI Product Pricingtech-leads-club/agent-skills | 7k | — | ~3.6k | Automated safety check: Pass | Custom licence | |
| Monetization Strategyphuryn/pm-skills | 27k | — | ~1.7k | Automated safety check: Pass | MIT | |
| Options Pricingagiprolabs/claude-trading-skills | 410 | — | ~1.4k | Automated safety check: Pass | MIT | |
| NegotiationTheCraigHewitt/skills | 159 | — | ~6.1k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Algo Price Bundle
What does Algo Price Bundle do?
Design bundle pricing strategies using pure bundling, mixed bundling, and consumer surplus analysis. Algo Price Bundle is an agent skill from asgard-ai-platform/skills. Design bundle pricing strategies using pure bundling, mixed bundling, and consumer surplus analysis.
When should I use Algo Price Bundle?
Algo Price Bundle fits situations like: the user needs to set prices for product bundles; determine whether bundling increases profit; analyze unbundling opportunities — even if they say should we bundle these products; package deal pricing.
How do I install Algo Price Bundle in Claude Code?
Run `npx skills add asgard-ai-platform/skills --skill algo-price-bundle -a claude-code`. Or copy the skill folder (algo-price-bundle in asgard-ai-platform/skills) into .claude/skills/algo-price-bundle in your project. Claude Code loads it when a task matches its description.
How do I install Algo Price Bundle in Codex?
Run `npx skills add asgard-ai-platform/skills --skill algo-price-bundle -a codex`. Or copy the skill folder (algo-price-bundle in asgard-ai-platform/skills) into .agents/skills/algo-price-bundle in your project. Codex loads it when a task matches its description.
Can I use Algo Price Bundle 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-bundle -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-bundle, .gemini/skills/algo-price-bundle, .github/skills/algo-price-bundle and .opencode/skills/algo-price-bundle in your project.
What does Algo Price Bundle need to run?
SKILL.md names no scripts, command-line tools or credentials: Algo Price Bundle is instructions for the agent only.
Does Algo Price Bundle 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 Bundle 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 Bundle use?
Algo Price Bundle 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 Bundle 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 5.9k tokens, read only when the agent opens those files.
What are the alternatives to Algo Price Bundle?
Skills that share tags, products or a category with Algo Price Bundle: Setting Pricing (GTM-Strategist/gtm-strategist-skills, 264 stars), AI Product Pricing (tech-leads-club/agent-skills, 7k stars), Monetization Strategy (phuryn/pm-skills, 27k stars) and Options Pricing (agiprolabs/claude-trading-skills, 410 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Algo Price Bundle?
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.