"algo-ad-gsp"

"algo-ad-gsp" is a skill for Claude Code from charlieviettq/awesome-agent-skill. It costs 72 tokens per session (961 once invoked), scanned A, a copy of algo-ad-gsp, MIT.

A method for assigning sponsored search ads to positions and setting their prices. In this auction, higher bids generally get better positions, and each winning advertiser pays the next position's bid, adjusted in some search engines by ad quality.

In plain words
What is it for?
Use it to calculate ad positions and cost per click from bids and quality scores, or to study bidding in sponsored search. It is not designed for display-ad auctions or auctions that require truthful bidding.
Why use it?
It gives developers a way to model common search-ad auctions and understand how position and cost are related. It also makes clear that truthful bidding is not always the best strategy.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to calculate ad positions and cost per click from bids and quality scores, or to study bidding in sponsored search. It is not designed for display-ad auctions or auctions that require truthful bidding.

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Install with agentmods
npx agentmods add skills/charlieviettq/awesome-agent-skill/algo-ad-gsp
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add charlieviettq/awesome-agent-skill --skill algo-ad-gsp
Clone the repo
git clone --depth 1 https://github.com/charlieviettq/awesome-agent-skill

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for "algo-ad-gsp"

README.md
[![agentmods](https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/algo-ad-gsp/github.svg)](https://agentmods.dev/skills/charlieviettq/awesome-agent-skill/algo-ad-gsp)
Your own site
<a href="https://agentmods.dev/skills/charlieviettq/awesome-agent-skill/algo-ad-gsp"><img src="https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/algo-ad-gsp/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for "algo-ad-gsp"

Your own site · 80×15
<a href="https://agentmods.dev/skills/charlieviettq/awesome-agent-skill/algo-ad-gsp"><img src="https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/algo-ad-gsp.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 72 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 961 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 91% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00072 $0.00961
Opus 5 $0.00036 $0.00481
Sonnet 5 $0.00014 $0.00192
Haiku 4.5 $0.00007 $0.00096

Measured 12d ago against content hash e9d84e6fa44c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

"algo-ad-gsp" scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

91% identical to algo-ad-gsp — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.claude/skills/algo-ad-gsp/SKILL.md · 86 lines

How it starts

The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Generalized Second Price Auction

Overview

GSP allocates K ad slots to N bidders, assigning the highest bidder the top slot, second-highest the second slot, etc. Each winner pays the bid of the advertiser ONE POSITION BELOW them (per-slot second price). Used by Google Ads and Bing Ads. Runs in O(N log N) for sorting bids.

When to Use

Trigger conditions:

  • Understanding search engine ad auction mechanics
  • Computing ad position and cost-per-click from bid and quality data
  • Analyzing bidding strategy in sponsored search

When NOT to use:

  • When you need incentive-compatible truthful bidding (use VCG mechanism)
  • When analyzing display/programmatic ad auctions (typically use first-price)

Algorithm

IRON LAW: GSP Is NOT Incentive-Compatible
Unlike Vickrey (single-item second-price) auctions, truthful bidding
is NOT a dominant strategy in GSP. Bidders may strategically shade
bids below their true value. The equilibrium depends on competitor bids.
Ad Rank = Bid × Quality Score (Google's variant adds format/extensions).

Phase 1: Input Validation

Collect: bids, quality scores (or ad rank scores) for all competing advertisers. Define available slot positions and their click-through rate multipliers. Gate: All bids positive, quality scores in valid range.

Phase 2: Core Algorithm

  1. Compute Ad Rank for each advertiser: AdRank_i = Bid_i × QualityScore_i
  2. Sort advertisers by Ad Rank descending
  3. Assign top-K to slots 1 through K
  4. Compute payment: CPC_i = AdRank_{i+1} / QualityScore_i (price to maintain position)
  5. Last slot winner pays the minimum bid threshold

Phase 3: Verification

Check: all payments ≤ bids, positions ordered by Ad Rank, no advertiser pays more than their bid. Gate: Payment ≤ bid for all winners, positions consistent.

Phase 4: Output

Return slot assignments with positions, CPCs, and estimated clicks.

Output Format

{
  "slots": [{"advertiser": "A", "position": 1, "ad_rank": 8.5, "cpc": 2.10, "est_clicks": 100}],
  "metadata": {"total_bidders": 15, "slots_available": 4, "auction_type": "gsp"}
}

Read the full file on GitHub · 86 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 86 lines · 72 tokens per session scan A e9d84e6fa44c

Subscribe to this mod's changes

"algo-ad-gsp" is a skill published in the GitHub repository charlieviettq/awesome-agent-skill (25 stars, last pushed 1mo ago), licensed MIT. It adds 72 tokens to every session and 961 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to algo-ad-gsp, differing in 8 lines, and is treated as a copy.

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