nimble-search-reference
Reference for nimble search command. Load when searching the live web. Contains: all flags, 8 focus modes (general/coding/news/academic/shopping/social/geo/location), search_depth modes (lite/fast/deep), response structure, credit costs.
13 stars
Best use case
nimble-search-reference is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Reference for nimble search command. Load when searching the live web. Contains: all flags, 8 focus modes (general/coding/news/academic/shopping/social/geo/location), search_depth modes (lite/fast/deep), response structure, credit costs.
Teams using nimble-search-reference should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
$curl -o ~/.claude/skills/nimble-search/SKILL.md --create-dirs "https://raw.githubusercontent.com/Nimbleway/agent-skills/main/skills/web-search-tools/nimble-web-expert/references/nimble-search/SKILL.md"
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/nimble-search/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How nimble-search-reference Compares
| Feature / Agent | nimble-search-reference | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Reference for nimble search command. Load when searching the live web. Contains: all flags, 8 focus modes (general/coding/news/academic/shopping/social/geo/location), search_depth modes (lite/fast/deep), response structure, credit costs.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# nimble search — reference
Real-time web search with 8 focus modes. Returns results with titles, URLs, and optionally full content and AI answers.
## Table of Contents
- [Parameters](#parameters)
- [Search depth modes](#search-depth-modes)
- [Focus modes](#focus-modes)
- [CLI](#cli)
- [Python SDK](#python-sdk)
- [Response structure](#response-structure)
---
## Parameters
| Parameter | Type | Default | Description |
| ------------------------- | --------------- | -------- | ----------------------------------------------------------------------------------------------------------------- |
| `query` | string | required | Search query |
| `search_depth` | string | `deep` | Content depth: `lite` \| `fast` \| `deep` — see depth table below |
| `focus` | string or array | `general`| Focus mode (see table below) or array of specific agent names e.g. `["amazon_serp", "target_serp"]` |
| `include_answer` | bool | `false` | AI-synthesized answer (premium — retry without if 402/403) |
| `max_results` | int | `10` | Result count (1–100) |
| `output_format` | string | — | `plain_text` \| `markdown` \| `simplified_html` |
| `include_domains` | array | — | Restrict to these domains (max 50) |
| `exclude_domains` | array | — | Exclude these domains (max 50) |
| `time_range` | string | — | `hour` \| `day` \| `week` \| `month` \| `year` — cannot combine with dates |
| `start_date` / `end_date` | string | — | Date range `YYYY-MM-DD` — cannot combine with `time_range` |
| `content_type` | string | — | File type filter: `pdf`, `docx`, `xlsx`, `documents`, `spreadsheets`, `presentations` — only with `general` focus |
| `max_subagents` | int | — | Parallel agents for shopping/social/geo/location (1–5) |
| `country` | string | — | ISO Alpha-2 geo-targeted results (e.g. `US`) |
| `locale` | string | — | Language code (e.g. `en`, `fr`, `de`) |
| `deep_search` | bool | — | **Deprecated** — use `search_depth` instead. `true` = `deep`, `false` = `lite`. Still works for backward compat. |
CLI uses hyphens (`--search-depth`, `--include-answer`). SDK uses underscores (`search_depth`, `include_answer`).
---
## Search depth modes
| Mode | Content | Speed | Best for |
| ------ | -------------------------------- | -------- | --------------------------------------------------------------- |
| `lite` | Metadata only (title, URL, snippet) | Fastest | High-volume pipelines, URL discovery, quick filtering |
| `fast` | Rich cached content | Fast | AI agents, RAG, chatbots — quality content without scrape latency |
| `deep` | Full real-time page content | Slowest | Research, due diligence, tasks requiring complete source material |
**Default for AI agent use:** prefer `fast` — richest content-to-latency ratio.
---
## Focus modes
| Mode | Best for | Example query |
| ---------- | ----------------------------------- | ---------------------------------------- |
| `general` | Broad web (default) | "best practices for X" |
| `coding` | Docs, code, Stack Overflow, GitHub | "how to implement X in Python" |
| `news` | Current events, breaking news | "EU AI Act enforcement 2026" |
| `academic` | Research papers, scholarly articles | "transformer attention mechanisms paper" |
| `shopping` | Products, price comparisons | "best wireless headphones under $200" |
| `social` | People, LinkedIn, X, YouTube | "Jane Doe Head of Engineering" |
| `geo` | Geographic and regional data | "tech companies in Berlin" |
| `location` | Local businesses, restaurants | "italian restaurants San Francisco" |
---
## CLI
```bash
# Fast depth — rich content, low latency (best for agents)
nimble search --query "React server components" --search-depth fast
# Lite — metadata only, fastest
nimble search --query "OpenAI announcements" --focus news --search-depth lite
# Deep — full real-time page scrape
nimble search --query "EU AI Act" --focus news --search-depth deep \
--start-date 2025-01-01 --end-date 2025-12-31
# With AI answer + domain filter
nimble search --query "Python asyncio best practices" \
--focus coding --search-depth fast --include-answer \
--include-domain '["docs.python.org", "realpython.com"]'
# Extract just URLs
nimble --transform "results.#.url" search --query "React tutorials" --search-depth lite
```
## Python SDK
```python
from nimble_python import Nimble
nimble = Nimble(api_key=os.environ["NIMBLE_API_KEY"])
# Fast depth — best default for AI agent use
resp = nimble.search(query="React server components", search_depth="fast")
# Lite — scan many results quickly
resp = nimble.search(
query="OpenAI announcements",
focus="news",
search_depth="lite",
time_range="week",
)
# Deep — full content for research
resp = nimble.search(
query="EU AI Act enforcement",
focus="news",
search_depth="deep",
include_answer=True,
)
# Custom focus — explicit agent array
resp = nimble.search(
query="best wireless headphones",
focus=["amazon_serp", "walmart_serp"],
search_depth="fast",
max_results=10,
)
results = resp.results # list of result objects
answer = resp.answer # AI summary (if include_answer=True)
```
---
## Response structure
| Field | Type | Description |
| -------------------------------- | ------ | ------------------------------------------------------------ |
| `total_results` | int | Total results returned |
| `results` | array | Search results |
| `results[].title` | string | Page title |
| `results[].description` | string | Snippet |
| `results[].url` | string | Page URL |
| `results[].content` | string | Page content — cached (`fast`) or real-time scraped (`deep`) |
| `results[].metadata.position` | int | Result rank |
| `results[].metadata.entity_type` | string | e.g. `OrganicResult` |
| `answer` | string | AI summary (if `include_answer=True`) |
| `request_id` | UUID | Request identifier |Related Skills
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