Pricing Strategy
freekmurze/dotfiles
When the user wants help with pricing decisions, packaging, or monetization strategy.
Implement dynamic pricing strategies that adjust prices in real-time based on demand, time, and competition.
Install Algo Price Dynamic
$ npx skills add asgard-ai-platform/skills --skill algo-price-dynamic -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install asgard-ai-platform/skills algo-price-dynamic --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-dynamic .claude/skills/algo-price-dynamic && 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-dynamic" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-price-dynamic into .claude/skills/algo-price-dynamic/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-price-dynamic", 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-dynamicType 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-dynamic -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install asgard-ai-platform/skills algo-price-dynamic --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-dynamic .agents/skills/algo-price-dynamic && 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-dynamic" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-price-dynamic into .agents/skills/algo-price-dynamic/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-price-dynamic", 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-dynamic -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install asgard-ai-platform/skills algo-price-dynamic --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-dynamic .cursor/skills/algo-price-dynamic && 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-dynamic" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-price-dynamic into .cursor/skills/algo-price-dynamic/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-price-dynamic", 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-dynamic--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-dynamic -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install asgard-ai-platform/skills algo-price-dynamic --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-dynamic .gemini/skills/algo-price-dynamic && 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-dynamic" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-price-dynamic into .gemini/skills/algo-price-dynamic/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-price-dynamic", 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-dynamicInstalls 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-dynamic -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-dynamic .github/skills/algo-price-dynamic && 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-dynamic" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-price-dynamic into .github/skills/algo-price-dynamic/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-price-dynamic", 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-dynamic -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-dynamic --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-dynamic .opencode/skills/algo-price-dynamic && 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-dynamic" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-price-dynamic into .opencode/skills/algo-price-dynamic/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-price-dynamic", 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-dynamic- GitHub stars
- 242
- Token cost
- ~1.1k tokens
- SKILL.md length
- 403 words
- Files
- 4 (incl. references)
- Skills in repo
- 207
- Repo updated
- First seen
- Licence
- MIT
At a glance
Implement dynamic pricing strategies that adjust prices in real-time based on demand, time, and competition.
- Works in 4 steps: Input Validation → Core Algorithm → Verification → …
- The user needs to build a dynamic pricing system
- 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 Dynamic is an agent skill from asgard-ai-platform/skills. Implement dynamic pricing strategies that adjust prices in real-time based on demand, time, and competition. Use this skill when the user needs to build a dynamic pricing system, implement surge pricing, or optimize prices for perishable inventory — even if they say 'real-time pricing', 'surge pricing', or 'demand-based price adjustment'.
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/fairness-constraints.md` and `references/revenue-management.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 build a dynamic pricing system
- Implement surge pricing
- Optimize prices for perishable inventory — even if they say real-time pricing
- Demand-based price adjustment
Example prompts
- “real-time pricing”
- “surge pricing”
- “demand-based price adjustment”
- “/algo-price-dynamic”
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 Dynamic loads about 1.1k tokens when it runs, and up to ~6.7k if it reads all its reference files. Until then it costs about 90 tokens; SKILL.md has 403 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). 403 words, ~1,107 tokens.
Download SKILL.mdSave it as
.claude/skills/algo-price-dynamic/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- algo-price-dynamic
- description
- Implement dynamic pricing strategies that adjust prices in real-time based on demand, time, and competition. Use this skill when the user needs to build a dynamic pricing system, implement surge pricing, or optimize prices for perishable inventory — even if they say 'real-time pricing', 'surge pricing', or 'demand-based price adjustment'.
- metadata.category
- WP-39 定價演算法
- metadata.tags
- pricing, dynamic-pricing, revenue-management, real-time
Dynamic Pricing
Overview
Dynamic pricing adjusts prices in real-time based on demand signals, time, inventory, and competitive conditions. Common in airlines, hotels, ride-sharing, and e-commerce. Objective: maximize revenue (or profit) subject to capacity/inventory constraints.
When to Use
Trigger conditions:
- Pricing perishable inventory (hotel rooms, airline seats, event tickets)
- Implementing demand-responsive pricing for e-commerce
- Building surge pricing or time-based pricing systems
When NOT to use:
- For one-time pricing decisions (use Van Westendorp or conjoint)
- When price changes are impractical (regulated markets, long-term contracts)
Algorithm
IRON LAW: Dynamic Pricing Requires REAL-TIME Data
Stale data produces prices optimal for PAST conditions, not current ones.
Three data streams must be current:
1. Demand signal (bookings, searches, cart additions)
2. Inventory/capacity status
3. Competitive prices (where applicable)
Update frequency: minutes for ride-sharing, hours for hotels, daily for retail.Phase 1: Input Validation
Collect: current demand indicators, remaining inventory/capacity, time until expiration/event, competitor prices, price floor/ceiling constraints. Gate: Real-time data feeds connected, business rules defined.
Phase 2: Core Algorithm
Rule-based: If demand > threshold, increase price by X%. Tiered rules by inventory level.
Demand-curve based: 1. Estimate demand curve at current conditions. 2. Find price that maximizes revenue = P × Q(P). 3. Apply inventory constraint: if capacity is scarce, price up; if excess, price down.
ML-based: Train model to predict demand at each price point given context features. Optimize over predicted demand curve.
Phase 3: Verification
Monitor: revenue per unit, booking pace, customer complaints, competitive position. A/B test new pricing rules. Gate: Revenue improved without significant volume loss or customer backlash.
Phase 4: Output
Return recommended price with reasoning and expected impact.
Output Format
{
"recommended_price": 1200,
"current_price": 999,
"reasoning": {"demand_signal": "high", "inventory_remaining_pct": 15, "competitor_avg": 1100},
"expected_impact": {"revenue_change_pct": 18, "volume_change_pct": -5},
"metadata": {"strategy": "demand-curve", "update_frequency": "hourly"}
}Examples
Sample I/O
Input: Hotel room, 3 days until date, 85% occupancy, average competitor price $150 Expected: Price above competitor ($160-170) due to high occupancy, short time horizon.
Show full SKILL.md (159 more words)Show less
Edge Cases
| Input | Expected | Why |
|---|---|---|
| Zero demand | Drop to floor price | Stimulate demand, recover some revenue |
| Last unit available | Price near ceiling | Scarcity maximizes willingness to pay |
| Competitor flash sale | Don't auto-match if unnecessary | Avoid price war; assess if your product differentiates |
Gotchas
- Customer fairness perception: Visible price discrimination (same product, different prices for different users) generates backlash. Segment by time, channel, or bundle — not by individual.
- Price war spiraling: Automated competitive pricing can create a race to the bottom. Set absolute floors and rate-of-change limits.
- Demand cannibalization: If customers learn prices drop later, they wait. This is the "strategic customer" problem — don't train customers to delay.
- Regulatory risk: Dynamic pricing may violate anti-gouging laws during emergencies. Build in legal constraint rules.
- A/B testing bias: Testing different prices creates revenue measurement challenges. The control group at the "wrong" price loses money by design.
References
- For revenue management models (airline/hotel), see
references/revenue-management.md - For fairness constraints in dynamic pricing, see
references/fairness-constraints.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-dynamic of asgard-ai-platform/skills.
- SKILL.md
- examples/sample_scenario.md
- references/fairness-constraints.md
- references/revenue-management.md
Open the folder on GitHubat commit 4e7f4f8
Compare with similar skills
Algo Price Dynamic 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 Dynamic this skillasgard-ai-platform/skills | 242 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Pricing Strategyfreekmurze/dotfiles | 1k | 18 repos | ~1.6k | Automated safety check: Pass | None | |
| Profit Margin Calculator Amazonnexscope-ai/eCommerce-Skills | 1.1k | — | ~1.7k | Automated safety check: Pass | MIT | |
| Niche Opportunity Finderzanecole10/software-tailor-skills | 106 | — | ~4.2k | Automated safety check: Pass | None | |
| Pricing Strategyalirezarezvani/claude-skills | 28k | 1 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Software Pricing Calculatorzanecole10/software-tailor-skills | 106 | — | ~3.7k | Automated safety check: Pass | None |
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Related
Categories
Questions about Algo Price Dynamic
What does Algo Price Dynamic do?
Implement dynamic pricing strategies that adjust prices in real-time based on demand, time, and competition. Algo Price Dynamic is an agent skill from asgard-ai-platform/skills. Implement dynamic pricing strategies that adjust prices in real-time based on demand, time, and competition.
When should I use Algo Price Dynamic?
Algo Price Dynamic fits situations like: the user needs to build a dynamic pricing system; implement surge pricing; optimize prices for perishable inventory — even if they say real-time pricing; demand-based price adjustment.
How do I install Algo Price Dynamic in Claude Code?
Run `npx skills add asgard-ai-platform/skills --skill algo-price-dynamic -a claude-code`. Or copy the skill folder (algo-price-dynamic in asgard-ai-platform/skills) into .claude/skills/algo-price-dynamic in your project. Claude Code loads it when a task matches its description.
How do I install Algo Price Dynamic in Codex?
Run `npx skills add asgard-ai-platform/skills --skill algo-price-dynamic -a codex`. Or copy the skill folder (algo-price-dynamic in asgard-ai-platform/skills) into .agents/skills/algo-price-dynamic in your project. Codex loads it when a task matches its description.
Can I use Algo Price Dynamic 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-dynamic -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-dynamic, .gemini/skills/algo-price-dynamic, .github/skills/algo-price-dynamic and .opencode/skills/algo-price-dynamic in your project.
What does Algo Price Dynamic need to run?
SKILL.md names no scripts, command-line tools or credentials: Algo Price Dynamic is instructions for the agent only.
Does Algo Price Dynamic 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 Dynamic 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 Dynamic use?
Algo Price Dynamic 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 Dynamic 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 5.6k tokens, read only when the agent opens those files.
What are the alternatives to Algo Price Dynamic?
Skills that share tags, products or a category with Algo Price Dynamic: Pricing Strategy (freekmurze/dotfiles, 1k stars), Profit Margin Calculator Amazon (nexscope-ai/eCommerce-Skills, 1.1k stars), Niche Opportunity Finder (zanecole10/software-tailor-skills, 106 stars) and Pricing Strategy (alirezarezvani/claude-skills, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Algo Price Dynamic?
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.