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Query Pollinations text API with web-search models (gemini-search, perplexity-fast, nomnom, etc.). Use when you need web search grounded answers via Pollinations.
---
name: web-research-a9c4e7471002
description: Query Pollinations text API with web-search models (gemini-search, perplexity-fast, nomnom, etc.). Use when you need web search grounded answers via Pollinations.
---
# Web Research
## Available Models
- **gemini-search** — Google Gemini with web search grounding (default)
- **perplexity-fast** — Perplexity AI, faster (default)
- **perplexity** — Perplexity AI
- **nomnom** — NomNom search model
By default, queries both **gemini-search** and **perplexity-fast** in parallel.
## Requirements
- `curl`
## Authentication
Set an API key in an environment variable (preferred):
```bash
export POLLINATIONS_API_KEY="YOUR_KEY"
```
Or create a local `.env` file at `.claude/skills/web-research/.env`:
```bash
POLLINATIONS_API_KEY="YOUR_KEY"
```
If `POLLINATIONS_API_KEY` is not set, the script will prompt for a key (input hidden).
## Quick usage
```bash
.claude/skills/web-research/scripts/web-research.sh "What is pollinations.ai?"
```
Choose a model:
```bash
.claude/skills/web-research/scripts/web-research.sh --model perplexity-fast "Fact-check this claim with sources"
```
Compare multiple models:
```bash
.claude/skills/web-research/scripts/web-research.sh --models gemini-search,perplexity-fast,nomnom "Compare answers"
```
Run multi-model in parallel:
```bash
.claude/skills/web-research/scripts/web-research.sh --models gemini-search,perplexity-fast --parallel "Compare answers"
```
## Before reviewing a build plan
Run two searches first — `"<vendor> <capability> <year>"` and `"<capability> MCP server"`
— and record the result. A first-party vendor launch in the last two quarters gets its own
section ("why not the managed product"). It's the cheapest part of the review and can
invalidate the whole plan, so do it before studying the design.
## Numbers from PDFs or long documents
A summarizer given a leading prompt ("did X beat Y?") tends to echo the prompt, including
invented quotes. Ask neutrally ("list every numeric result table") and, for any number
you'll repeat, read the source text or table yourself.
## Notes
- Uses `https://gen.pollinations.ai/v1/chat/completions`
- Sends `Authorization: Bearer <key>`
---
name: web-research-a9c4e7471002
description: Query Pollinations text API with web-search models (gemini-search, perplexity-fast, nomnom, etc.). Use when you need web search grounded answers via Pollinations.
---
# Web Research
## Available Models
- **gemini-search** — Google Gemini with web search grounding (default)
- **perplexity-fast** — Perplexity AI, faster (default)
- **perplexity** — Perplexity AI
- **nomnom** — NomNom search model
By default, queries both **gemini-search** and **perplexity-fast** in parallel.
## Requirements
- `curl`
## Authentication
Set an API key in an environment variable (preferred):
```bash
export POLLINATIONS_API_KEY="YOUR_KEY"
```
Or create a local `.env` file at `.claude/skills/web-research/.env`:
```bash
POLLINATIONS_API_KEY="YOUR_KEY"
```
If `POLLINATIONS_API_KEY` is not set, the script will prompt for a key (input hidden).
## Quick usage
```bash
.claude/skills/web-research/scripts/web-research.sh "What is pollinations.ai?"
```
Choose a model:
```bash
.claude/skills/web-research/scripts/web-research.sh --model perplexity-fast "Fact-check this claim with sources"
```
Compare multiple models:
```bash
.claude/skills/web-research/scripts/web-research.sh --models gemini-search,perplexity-fast,nomnom "Compare answers"
```
Run multi-model in parallel:
```bash
.claude/skills/web-research/scripts/web-research.sh --models gemini-search,perplexity-fast --parallel "Compare answers"
```
## Before reviewing a build plan
Run two searches first — `"<vendor> <capability> <year>"` and `"<capability> MCP server"`
— and record the result. A first-party vendor launch in the last two quarters gets its own
section ("why not the managed product"). It's the cheapest part of the review and can
invalidate the whole plan, so do it before studying the design.
## Numbers from PDFs or long documents
A summarizer given a leading prompt ("did X beat Y?") tends to echo the prompt, including
invented quotes. Ask neutrally ("list every numeric result table") and, for any number
you'll repeat, read the source text or table yourself.
## Notes
- Uses `https://gen.pollinations.ai/v1/chat/completions`
- Sends `Authorization: Bearer <key>`
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Includes source scripts; review them before use. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.