Reduce SerpAPI search consumption through measured demand, exact-query caching, admission budgets, and current account pricing evidence.

MITAuto-check passedData & Analytics

Install Serpapi Cost Tuning

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill serpapi-cost-tuning -a claude-code

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

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace serpapi-cost-tuning --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/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/serpapi-cost-tuning .claude/skills/serpapi-cost-tuning && 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
serpapi-cost-tuning
GitHub stars
2.8k
Token cost
~1k tokens
SKILL.md length
392 words
Files
1
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Reduce SerpAPI search consumption through measured demand, exact-query caching, admission budgets, and current account pricing evidence.

  • Works in 7 steps: Enumerate every producer and separate… → Capture a dated Account API snapshot and… → Forecast searches through the next… → …
  • Controlling search spend
  • SKILL.md covers Overview, Prerequisites, Tool Discipline and Current Contract, plus 7 more sections
  • Needs SERPAPI_KEY

What it does

Serpapi Cost Tuning is an agent skill from jeremylongshore/tons-of-skills-marketplace. Reduce SerpAPI search consumption through measured demand, exact-query caching, admission budgets, and current account pricing evidence. Use when forecasting or controlling search spend. Trigger with "optimize SerpAPI cost".

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Designed for Claude Code; plan changes and production admission/cache changes require finance, product, and account-owner approval

It sits in Data & Analytics, covering Forecasting and time series and Caching. It works with SerpApi. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Controlling search spend
  • With optimize SerpAPI cost

Example prompts

  • “optimize SerpAPI cost”
  • “/serpapi-cost-tuning”

Requirements

  • A credential in SERPAPI_KEY
  • Compatibility (from SKILL.md): Designed for Claude Code; plan changes and production admission/cache changes require finance, product, and account-owner approval
  • Pre-approved tools (allowed-tools): Read, Glob, Grep, WebFetch, Write, Edit

Workflow steps

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

  1. Enumerate every producer and separate user-valued searches from retries, duplicate requests, tests, previews, and abandoned work.
  2. Capture a dated Account API snapshot and current pricing evidence; do not embed public list prices as durable code constants.
  3. Forecast searches through the next renewal using observed volume, seasonality, cache hit rate, pagination, and failure amplification.
  4. Rank optimizations: remove duplicate calls, normalize exact-match parameters, enable application caching, stop unnecessary pagination…
  5. Preserve freshness and correctness requirements; never claim that reducing result count reduces the number of searches without current…
  6. Model base, expected, and peak scenarios with headroom and an explicit assumption register.
  7. Present product-impacting budgets or plan changes for approval, canary safe changes, and reconcile forecast to actual usage.

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Glob
    • Grep
    • WebFetch
    • Write
    • Edit

    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

    Links to these hosts (documentation or services it may open):

    • serpapi.com

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • SERPAPI_KEY

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

  • Compatibility

    Designed for Claude Code; plan changes and production admission/cache changes require finance, product, and account-owner approval

    From compatibility in the SKILL.md frontmatter.

Context cost

Serpapi Cost Tuning loads about 1k tokens when it runs. Until then it costs about 61 tokens; SKILL.md has 392 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~61
When it runs · the whole SKILL.md, loaded when a task matches
~1k

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 jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 392 words, ~1,001 tokens.

Download SKILL.mdSave it as .claude/skills/serpapi-cost-tuning/SKILL.md (or your agent's skills folder).
name
serpapi-cost-tuning
description
Reduce SerpAPI search consumption through measured demand, exact-query caching, admission budgets, and current account pricing evidence. Use when forecasting or controlling search spend. Trigger with "optimize SerpAPI cost".
allowed-tools
Read, Glob, Grep, WebFetch, Write, Edit
compatibility
Designed for Claude Code; plan changes and production admission/cache changes require finance, product, and account-owner approval
argument-hint
[environment] [forecast-window]
version
1.6.0
author
Jeremy Longshore <jeremy@intentsolutions.io>
license
MIT
tags
saas, serpapi, cost, finops, caching
model
inherit
effort
high

SerpAPI Usage and Cost Governance

Overview

Forecast from observed search demand and the account's current contract, then reduce waste without inventing static plan economics.

Prerequisites

  • Current pricing page and Account API snapshot
  • Search attempts, server/application cache hits, engine mix, retries, and business outcome volume
  • Product freshness requirements and owners for finance, product, and the SerpAPI account

Tool Discipline

Use Read, Glob, and Grep to inventory callers, cache behavior, and retry amplification, WebFetch to verify current public pricing and cache rules, and Write or Edit for forecasts, budgets, dashboards, and safe optimizations.

Current Contract

Plans, prices, included searches, and hourly throughput can change. Account API exposes the subscribed plan, searches left, usage, renewal date, and throughput. Exactly matching cached searches can be served from SerpAPI's one-hour cache for free; no_cache=true opts out and can increase consumption.

Authentication

Read account facts with the server-side SERPAPI_KEY, but do not expose the key, account identity, or commercial details in public dashboards or receipts.

Instructions

  1. Enumerate every producer and separate user-valued searches from retries, duplicate requests, tests, previews, and abandoned work.
  2. Capture a dated Account API snapshot and current pricing evidence; do not embed public list prices as durable code constants.
  3. Forecast searches through the next renewal using observed volume, seasonality, cache hit rate, pagination, and failure amplification.
  4. Rank optimizations: remove duplicate calls, normalize exact-match parameters, enable application caching, stop unnecessary pagination, gate low-value work, and eliminate uncontrolled retries.
  5. Preserve freshness and correctness requirements; never claim that reducing result count reduces the number of searches without current evidence.
  6. Model base, expected, and peak scenarios with headroom and an explicit assumption register.
  7. Present product-impacting budgets or plan changes for approval, canary safe changes, and reconcile forecast to actual usage.
Show full SKILL.md (102 more words)Show less

Output

Return dated account/pricing evidence, producer ledger, demand forecast, waste analysis, prioritized controls, scenario assumptions, approval decisions, and forecast-versus-actual owner.

Error Handling

ConditionResponse
Pricing differs from the modelRefresh evidence and invalidate the stale scenario.
Usage exceeds events recordedAudit retries, pagination, hidden producers, and no_cache.
Cache lowers search qualityRestore the freshness contract and evaluate narrower reuse.
Renewal date is absentConfirm whether the account uses a non-monthly or cancelled arrangement.

Example

text
window=to-renewal; demand=observed; waste=duplicate-plus-retry; pricing=evidence-dated; scenarios=base/expected/peak; headroom=approved; action=normalize-cache-keys

Resources

Next Steps

Reconcile the forecast weekly and reopen the plan decision before renewal or a material demand change.

© jeremylongshore, 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/.curated/serpapi-cost-tuning of jeremylongshore/tons-of-skills-marketplace.

Open the folder on GitHubat commit cfae287

Compare with similar skills

Serpapi Cost Tuning 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.

Serpapi Cost Tuning compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Serpapi Cost Tuning this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1kAutomated safety check: PassMIT
Data Collectionbrycewang-stanford/Auto-Empirical-Research-Skills4.6k—~975Automated safety check: PassCustom licence
AWS Databaseaws/agent-toolkit-for-aws2.8k—~2kAutomated safety check: PassApache-2.0
Time Series Analytics Useropen-edge-platform/edge-ai-libraries171—~3.1kAutomated safety check: PassApache-2.0
Meihua Divinationtradecatlabs/fatecat201—~1.1kAutomated safety check: PassMIT
Bio Reporting Quarto ReportsGPTomics/bioSkills1.2k1 repos~2.4kAutomated safety check: PassMIT

Similar skills

  • Data Collection

    brycewang-stanford/Auto-Empirical-Research-Skills

    A skill your agent uses when collecting data for a research project, downloading time series, building a dataset, accessing economic or social data APIs, or scraping data from a non-API source.

    4.6k GitHub stars~975 tokensUpdated 6 days ago
    Data & AnalyticsAuto-check passed
  • AWS Database

    aws/agent-toolkit-for-aws

    Official

    Routes any task involving AWS databases — choosing, comparing, recommending, getting started with, or operating a database — to the correct service-specific skill.

    2.8k GitHub stars~2k tokensUpdated yesterday
    DatabasesAuto-check passed
  • Time Series Analytics User

    open-edge-platform/edge-ai-libraries

    Build a new time-series analytics use case on top of the deployed Time Series Analytics microservice — bring it up with Docker Compose (from a repo clone, or by fetching the compose files from…

    171 GitHub stars~3.1k tokensUpdated yesterday
    Data & AnalyticsAuto-check passed
  • Meihua Divination

    tradecatlabs/fatecat

    Structured Chinese-style divination and fate-reading skill for questions about current fortune, relationships, career choices, project momentum, and personal tendencies.

    201 GitHub stars~1.1k tokensUpdated 1 mo ago
    Data & AnalyticsAuto-check passed
  • Builds reproducible Quarto reports, presentations, and websites across R, Python, and Julia, with correct engine selection, cache-vs-freeze semantics, native cross-references, parameters, and…

    1.2k GitHub starsUsed in 1 repo~2.4k tokens
    Data & AnalyticsAuto-check passed
  • TimesFM Forecasting

    google-research/timesfm

    Forecasts any univariate time series zero-shot with Google's TimesFM model, returning point forecasts and calibrated prediction intervals without training.

    34k GitHub stars~4.7k tokensUpdated 11 days ago
    Data & AnalyticsAuto-check passed

More from jeremylongshore/tons-of-skills-marketplace

All 3,342 skills in this repo
  • Performing Security Code Review

    jeremylongshore/tons-of-skills-marketplace

    Execute this skill enables AI assistant to conduct a security-focused code review using the security-agent plugin.

    2.8k GitHub starsUsed in 2 repos~1.3k tokens
    Auto-check: notes
  • Adapting Transfer Learning Models

    jeremylongshore/tons-of-skills-marketplace

    Build this skill automates the adaptation of pre-trained machine learning models using transfer learning techniques.

    2.8k GitHub stars~1.1k tokensUpdated today
    Auto-check passed
  • Agent Context Loader

    jeremylongshore/tons-of-skills-marketplace

    Execute proactive auto-loading: automatically detects and loads agents.md files.

    2.8k GitHub stars~1.1k tokensUpdated today
    Auto-check passed
  • Aggregating Performance Metrics

    jeremylongshore/tons-of-skills-marketplace

    Aggregate and centralize performance metrics from applications, systems, databases, caches, and services.

    2.8k GitHub stars~1.2k tokensUpdated today
    Auto-check passed
  • Analyzing Capacity Planning

    jeremylongshore/tons-of-skills-marketplace

    Execute this skill enables AI assistant to analyze capacity requirements and plan for future growth.

    2.8k GitHub stars~947 tokensUpdated today
    Auto-check passed
  • Analyzing Database Indexes

    jeremylongshore/tons-of-skills-marketplace

    Process use when you need to work with database indexing. An agent skill from jeremylongshore/tons-of-skills-marketplace.

    2.8k GitHub stars~2k tokensUpdated today
    Auto-check passed

Works with

Questions about Serpapi Cost Tuning

What does Serpapi Cost Tuning do?

Reduce SerpAPI search consumption through measured demand, exact-query caching, admission budgets, and current account pricing evidence. Serpapi Cost Tuning is an agent skill from jeremylongshore/tons-of-skills-marketplace. Reduce SerpAPI search consumption through measured demand, exact-query caching, admission budgets, and current account pricing evidence.

When should I use Serpapi Cost Tuning?

Serpapi Cost Tuning fits situations like: controlling search spend; with optimize SerpAPI cost.

How do I install Serpapi Cost Tuning in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill serpapi-cost-tuning -a claude-code`. Or copy the skill folder (skills/.curated/serpapi-cost-tuning in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/serpapi-cost-tuning in your project. Claude Code loads it when a task matches its description.

How do I install Serpapi Cost Tuning in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill serpapi-cost-tuning -a codex`. Or copy the skill folder (skills/.curated/serpapi-cost-tuning in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/serpapi-cost-tuning in your project. Codex loads it when a task matches its description.

Can I use Serpapi Cost Tuning 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 jeremylongshore/tons-of-skills-marketplace --skill serpapi-cost-tuning -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/serpapi-cost-tuning, .gemini/skills/serpapi-cost-tuning, .github/skills/serpapi-cost-tuning and .opencode/skills/serpapi-cost-tuning in your project.

What does Serpapi Cost Tuning need to run?

Going by SKILL.md and its folder, Serpapi Cost Tuning needs credentials named SERPAPI_KEY. Our summary lists: A credential in SERPAPI_KEY. Its frontmatter pre-approves these tools: Read, Glob, Grep, WebFetch, Write, Edit. Compatibility (from SKILL.md): Designed for Claude Code; plan changes and production admission/cache changes require finance, product, and account-owner approval.

Does Serpapi Cost Tuning access the network?

SKILL.md names 1 domain. As links in the text: serpapi.com. This is read from the text; nothing was executed.

Is Serpapi Cost Tuning 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 Serpapi Cost Tuning use?

Serpapi Cost Tuning is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Serpapi Cost Tuning use?

About 1k tokens (SKILL.md is roughly 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 Serpapi Cost Tuning?

Skills that share tags, products or a category with Serpapi Cost Tuning: Data Collection (brycewang-stanford/Auto-Empirical-Research-Skills, 4.6k stars), AWS Database (aws/agent-toolkit-for-aws, 2.8k stars), Time Series Analytics User (open-edge-platform/edge-ai-libraries, 171 stars) and Meihua Divination (tradecatlabs/fatecat, 201 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Serpapi Cost Tuning?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

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