Agent skill

Google Image Search

Search and download images via Google Custom Search API with LLM-powered selection.

MITAuto-check: notesKnowledge Management

Install Google Image Search

skills CLI

$ npx skills add glebis/claude-skills --skill google-image-search -a claude-code

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

GitHub CLI

$ gh skill install glebis/claude-skills google-image-search --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/glebis/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/google-image-search .claude/skills/google-image-search && 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/

Paste into Claude Code

Install the "google-image-search" agent skill from https://github.com/glebis/claude-skills/tree/main/google-image-search into .claude/skills/google-image-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-image-search", 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

$skill-installer install https://github.com/glebis/claude-skills/tree/main/google-image-search

Type 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.

skills CLI

$ npx skills add glebis/claude-skills --skill google-image-search -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install glebis/claude-skills google-image-search --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/glebis/claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/google-image-search .agents/skills/google-image-search && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "google-image-search" agent skill from https://github.com/glebis/claude-skills/tree/main/google-image-search into .agents/skills/google-image-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-image-search", 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.

skills CLI

$ npx skills add glebis/claude-skills --skill google-image-search -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install glebis/claude-skills google-image-search --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/glebis/claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/google-image-search .cursor/skills/google-image-search && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "google-image-search" agent skill from https://github.com/glebis/claude-skills/tree/main/google-image-search into .cursor/skills/google-image-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-image-search", 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

$ gemini skills install https://github.com/glebis/claude-skills.git --path google-image-search

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add glebis/claude-skills --skill google-image-search -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install glebis/claude-skills google-image-search --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/glebis/claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/google-image-search .gemini/skills/google-image-search && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "google-image-search" agent skill from https://github.com/glebis/claude-skills/tree/main/google-image-search into .gemini/skills/google-image-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-image-search", 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.

GitHub CLI

$ gh skill install glebis/claude-skills google-image-search

Installs 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).

skills CLI

$ npx skills add glebis/claude-skills --skill google-image-search -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/glebis/claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/google-image-search .github/skills/google-image-search && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "google-image-search" agent skill from https://github.com/glebis/claude-skills/tree/main/google-image-search into .github/skills/google-image-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-image-search", 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.

skills CLI

$ npx skills add glebis/claude-skills --skill google-image-search -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install glebis/claude-skills google-image-search --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/glebis/claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/google-image-search .opencode/skills/google-image-search && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "google-image-search" agent skill from https://github.com/glebis/claude-skills/tree/main/google-image-search into .opencode/skills/google-image-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-image-search", 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: google-image-search
GitHub stars: 390
Token cost: ~1.4k tokens
SKILL.md length: 488 words
Files: 11 (incl. scripts, references)
Skills in repo: 92
Repo updated: Oct 8, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Search and download images via Google Custom Search API with LLM-powered selection.

Works in 4 steps: Simple Query → Batch Processing → Generate Config from Terms → …
Tasks that involve Note-taking
SKILL.md covers When to Use, Requirements, Modes of Operation and Key Options, plus 5 more sections
Runs Python scripts from its folder; calls python3; needs OPENROUTER_API_KEY and OPENROUTER_KEY

What it does

Google Image Search is an agent skill from glebis/claude-skills. Search and download images via Google Custom Search API with LLM-powered selection. This skill should be used when finding images for articles, presentations, research documents, or enriching Obsidian notes with relevant visuals. Supports simple queries, batch processing from JSON config, automatic config generation from terms, and full note enrichment with automatic image insertion below headings.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including scripts and reference files (for example `.claude-plugin/plugin.json`, `references/api_config_reference.md` and `scripts/api.py`).

It sits in Knowledge Management, covering Note-taking, Data pipelines and ETL and Model routing and gateways. It works with OpenRouter. The repository describes itself as: Collection of Claude Code skills for enhanced AI workflows. The licence is MIT.

When your agent uses it

Tasks that involve Note-taking
Tasks that involve Data pipelines and ETL
Tasks that involve Model routing and gateways

Example prompts

“/google-image-search”

Requirements

Python 3
A credential in OPENROUTER_API_KEY
A credential in OPENROUTER_KEY

Workflow steps

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

Simple Query
Batch Processing
Generate Config from Terms
Enrich Obsidian Note

What it can do on your machine

Read from SKILL.md and the folder at commit 3b88261. 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
Ships 8 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- python3
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 these keys or tokens, usually read from environment variables:
- OPENROUTER_API_KEY
- OPENROUTER_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Google Image Search loads about 1.4k tokens when it runs, and up to ~2.4k if it reads all its reference files. Until then it costs about 105 tokens; SKILL.md has 488 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~105
When it runs · the whole SKILL.md, loaded when a task matches: ~1.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~2.4k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

NoteMentions a .env fileSKILL.md:24
```
Store credentials in `.env`:
```

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); the scripts in this folder are not scanned.

SKILL.md

The full file from glebis/claude-skills at commit 3b88261, republished under its MIT licence (© glebis). 488 words, ~1,383 tokens.

Download SKILL.mdSave it as .claude/skills/google-image-search/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.

name: google-image-search
description: Search and download images via Google Custom Search API with LLM-powered selection. This skill should be used when finding images for articles, presentations, research documents, or enriching Obsidian notes with relevant visuals. Supports simple queries, batch processing from JSON config, automatic config generation from terms, and full note enrichment with automatic image insertion below headings.

Google Image Search Skill

Search for images using Google Custom Search API with intelligent scoring and LLM-based selection.

When to Use

Finding images to illustrate technical articles or research
Adding visuals to presentations
Enriching Obsidian notes with relevant images
Batch image search for multiple topics
Generating image search configs from plain text lists

Requirements

Google Custom Search API key and Search Engine ID
OpenRouter API key (for LLM selection)
llm CLI installed at /opt/homebrew/bin/llm

Store credentials in .env:

Google-Custom-Search-JSON-API-KEY=your_key
Google-Custom-Search-CX=your_cx
OPENROUTER-API-KEY=your_openrouter_key

(The OPENROUTER_API_KEY=... spelling works too — see the plugin note below.)

OpenRouter / llm-openrouter caveat

The llm-openrouter plugin only registers its models when it can read a key named OPENROUTER_KEY (env var or llm keys set openrouter). With only OPENROUTER_API_KEY set, llm models list shows zero OpenRouter models and every openrouter/... name fails with Unknown model — the script then silently falls back to keyword scoring. llm_select.py sets both names for the subprocess, so this is handled; if selection ever regresses, check OPENROUTER_KEY first:

bash

llm models list | grep -c openrouter   # 458+ means the plugin registered its models

Modes of Operation

1. Simple Query

Search for a single term:

bash

python3 ~/.claude/skills/google-image-search/scripts/google_image_search.py \
  --query "neural interface wearable device" \
  --output-dir ./images \
  --num-results 5

2. Batch Processing

Process multiple queries from JSON config:

bash

python3 ~/.claude/skills/google-image-search/scripts/google_image_search.py \
  --config image_queries.json \
  --output-dir ./images \
  --llm-select

3. Generate Config from Terms

Create JSON config from a list of terms using LLM:

bash

python3 ~/.claude/skills/google-image-search/scripts/google_image_search.py \
  --generate-config \
  --terms "AlterEgo wearable" "sEMG electrodes" "BCI headset" \
  --output my_queries.json

4. Enrich Obsidian Note

Extract visual terms from note, find images, and insert below headings:

bash

python3 ~/.claude/skills/google-image-search/scripts/google_image_search.py \
  --enrich-note ~/Brains/brain/Research/neural-interfaces.md

This mode:

Detects Obsidian vault and attachments folder
Uses LLM to extract visual-worthy terms from note
Searches for images for each term
Downloads best images to attachments folder
Inserts image embeds below relevant headings
Creates backup before modifying note

Key Options

Option	Description
`--query TEXT`	Simple single query
`--config FILE`	JSON config for batch
`--generate-config`	Generate config from `--terms`
`--enrich-note FILE`	Enrich Obsidian note
`--output-dir DIR`	Where to save images
`--urls-only`	Return URLs only, no download
`--llm-select`	Use LLM to pick best image (default: on)
`--no-llm-select`	Disable LLM selection
`--num-results N`	Results per query (default: 5)
`--dry-run`	Show what would be done

Show full SKILL.md (171 more words)Show less

JSON Config Format

Each entry supports:

json

{
  "id": "unique-id",
  "heading": "Display Heading",
  "description": "Context for what image to find",
  "query": "Google search query",
  "numResults": 5,
  "selectionCriteria": "What makes a good image",
  "requiredTerms": ["must", "have"],
  "optionalTerms": ["bonus", "terms"],
  "excludeTerms": ["stock", "clipart"],
  "preferredHosts": ["official-site.com"],
  "selectionCount": 2
}

See references/api_config_reference.md for full documentation.

Scoring System

Images are scored based on:

Required terms: -80 if missing, +30 if all present
Optional terms: +5 per match
Exclude terms: -50 per match
Preferred hosts: +25 if trusted, -5 if unknown
MIME type: +5 for PNG/JPEG, -10 for GIF
Resolution: +10 for high res, -10 for low res
File size: -5 if very small

LLM Selection

After scoring, LLM picks the best image from top candidates based on:

Title and URL metadata
Scoring reasons
Selection criteria

The LLM evaluates authenticity, clarity, and relevance for technical audiences.

Obsidian Integration

When in an Obsidian vault:

Auto-detects vault root via .obsidian folder
Uses configured attachments folder (default: Attachments)
Generates Obsidian-style embeds: ![[image.png|alt text]]
Creates backup before modifying notes

Script Files

File	Purpose
`google_image_search.py`	Main entry point
`api.py`	Google Custom Search API
`config.py`	Credentials and config handling
`download.py`	Image download with magic bytes
`evaluate.py`	Keyword-based scoring
`llm_select.py`	LLM selection and term extraction
`obsidian.py`	Vault detection and enrichment
`output.py`	Markdown output generation

Files

SKILL.md and 10 other files (scripts, references) in google-image-search of glebis/claude-skills.

SKILL.md
.claude-plugin/plugin.json
references/api_config_reference.md
scripts/api.py
scripts/config.py
scripts/download.py
scripts/evaluate.py
scripts/google_image_search.py
scripts/llm_select.py
scripts/obsidian.py
scripts/output.py

Open the folder on GitHubat commit 3b88261

Compare with similar skills

Google Image Search 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.

Google Image Search compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Google Image Search this skillglebis/claude-skills	390	—	~1.4k	Automated safety check: Notes	MIT	yesterday
Pricing Data Pipelinejqknono/coding-plans-for-copilot	138	—	~263	Automated safety check: Notes	MIT	yesterday
Decision Model Setupitechmeat/open-second-brain	442	—	~2.1k	Automated safety check: Pass	MIT	yesterday
Qmdalsk1992/CloddsBot	2.9k	3 repos	~1.2k	Automated safety check: Pass	MIT	7 days ago
Freetoken Botslimin112/min-skill	412	—	~1.3k	Automated safety check: Pass	None	yesterday
Add Modelget-convex/convex-evals	130	—	~1.5k	Automated safety check: Notes	Apache-2.0	yesterday

Similar skills

Pricing Data Pipeline
jqknono/coding-plans-for-copilot
更新编码套餐与 OpenRouter 指标/套餐 JSON、修复抓取失败或 pending。Use when: pricing:fetch, metrics:fetch, openrouter:plans:fetch, provider-pricing.json, dashboard 数据过期或 CI 定价 issue。
138 GitHub stars~263 tokensUpdated yesterday
Data & AnalyticsAuto-check: notes
Decision Model Setup
itechmeat/open-second-brain
Sets up, evaluates or turns off Open Second Brain's optional decision-model feature, starting from the o2b decision-model check command and a provider route you choose.
442 GitHub stars~2.1k tokensUpdated yesterday
Knowledge ManagementAuto-check passed
Qmd
alsk1992/CloddsBot
Local hybrid search for markdown notes and docs. An agent skill from alsk1992/CloddsBot.
2.9k GitHub starsUsed in 3 repos~1.2k tokens
Knowledge ManagementAuto-check passed
Freetoken Bots
limin112/min-skill
Discover, verify, and maintain zero-priced OpenRouter models for Pi child-agent workflows used by Muse, Grokbot, or Dot.
412 GitHub stars~1.3k tokensUpdated yesterday
AI & LLM EngineeringAuto-check passed
Add Model
get-convex/convex-evals
Add a new model to the convex-evals coding leaderboard, and optionally the decision benchmark, through a PR, then dispatch its baseline runs.
130 GitHub stars~1.5k tokensUpdated yesterday
AI & LLM EngineeringAuto-check: notes
Nature Figure
Tai609/NebulaMat
Create, revise, audit, and export submission-grade scientific figures for Nature-family and other high-impact venues in Python (matplotlib/seaborn) or R (ggplot2/patchwork/ComplexHeatmap), including…
100 GitHub stars~1.9k tokensUpdated 1 mo ago
Data & AnalyticsAuto-check passed

Questions about Google Image Search

What does Google Image Search do?

Search and download images via Google Custom Search API with LLM-powered selection. Google Image Search is an agent skill from glebis/claude-skills. Search and download images via Google Custom Search API with LLM-powered selection.

When should I use Google Image Search?

Google Image Search fits situations like: tasks that involve Note-taking; tasks that involve Data pipelines and ETL; tasks that involve Model routing and gateways.

How do I install Google Image Search in Claude Code?

Run `npx skills add glebis/claude-skills --skill google-image-search -a claude-code`. Or copy the skill folder (google-image-search in glebis/claude-skills) into .claude/skills/google-image-search in your project. Claude Code loads it when a task matches its description.

How do I install Google Image Search in Codex?

Run `npx skills add glebis/claude-skills --skill google-image-search -a codex`. Or copy the skill folder (google-image-search in glebis/claude-skills) into .agents/skills/google-image-search in your project. Codex loads it when a task matches its description.

Can I use Google Image Search 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 glebis/claude-skills --skill google-image-search -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/google-image-search, .gemini/skills/google-image-search, .github/skills/google-image-search and .opencode/skills/google-image-search in your project.

What does Google Image Search need to run?

Going by SKILL.md and its folder, Google Image Search needs Python for the scripts in its folder, the command-line tools its instructions call (python3) and credentials named OPENROUTER_API_KEY and OPENROUTER_KEY. Our summary lists: Python 3; A credential in OPENROUTER_API_KEY; A credential in OPENROUTER_KEY.

Does Google Image Search 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 Google Image Search safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Google Image Search use?

Google Image Search 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 Google Image Search use?

About 1.4k tokens (SKILL.md is roughly 5.5k 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 968 tokens, read only when the agent opens those files.

What are the alternatives to Google Image Search?

Skills that share tags, products or a category with Google Image Search: Pricing Data Pipeline (jqknono/coding-plans-for-copilot, 138 stars), Decision Model Setup (itechmeat/open-second-brain, 442 stars), Qmd (alsk1992/CloddsBot, 2.9k stars) and Freetoken Bots (limin112/min-skill, 412 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Google Image Search?

glebis (a GitHub user) maintains it in glebis/claude-skills, which has 390 GitHub stars. The repository holds 92 skills in this directory. The repository was last updated on October 8, 2026.

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

Install Google Image Search

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Google Image Search Skill

When to Use

Requirements

OpenRouter / llm-openrouter caveat

Modes of Operation

1. Simple Query

2. Batch Processing

3. Generate Config from Terms

4. Enrich Obsidian Note

Key Options

JSON Config Format

Scoring System

LLM Selection

Obsidian Integration

Script Files

Files

Compare with similar skills

Similar skills

More from glebis/claude-skills

Related

Questions about Google Image Search