wikipedia-search

Included with Lifetime

$97 forever

Wikipedia article search and retrieval

Writing & Docs

What this skill does

# Wikipedia

## Available Tools

- **wikipedia_search(query)**: Search Wikipedia for articles matching a query.
- `query` (string, required): Search query

- **wikipedia_get_article(title, summary_only?)**: Get content of a Wikipedia article by exact title.
- `title` (string, required): Article title (case-sensitive, use exact title from search results)
- `summary_only` (boolean, optional, default: false): Return only the summary instead of full text

## Usage Guidelines

- Only English Wikipedia is supported. Translate non-English queries to English before searching.
- Use `wikipedia_search` first to find the correct article title, then `wikipedia_get_article` for full content.
- Article titles are case-sensitive — use the exact title from search results.
- Use `summary_only=true` for quick factual lookups when full article content isn't needed.
- Wikipedia content is best for background information, definitions, and historical context.

## Citation Format

When presenting information from Wikipedia, wrap every specific claim in `<cite>` tags:

```
<cite source="Wikipedia: ARTICLE_TITLE" url="https://en.wikipedia.org/wiki/ARTICLE_TITLE">claim text</cite>
```

**Rules:**
- Cite factual claims, statistics, dates, and specific information from articles.
- The `source` attribute should include the article title (e.g., `"Wikipedia: Quantum Computing"`).
- The `url` attribute should contain the Wikipedia article URL.
- Do NOT cite your own reasoning or general knowledge.
- Use the minimum number of citations necessary to support claims.

Files: 1

Size: 1.6 KB

Complexity: 3/100

Category: Writing & Docs

Source: https://github.com/aws-samples/sample-strands-agent-with-agentcore/tree/main/chatbot-app/agentcore/skills/wikipedia-search

Related in Writing & Docs

jax-development

Included

Use this skill when the user is writing, debugging, profiling, refactoring, reviewing, benchmarking, parallelising, exporting, or explaining JAX code, or when they mention JAX, jax.numpy, jit, grad, value_and_grad, vmap, scan, lax, random keys, pytrees, jax.Array, sharding, Mesh, PartitionSpec, NamedSharding, pmap, shard_map, Pallas, XLA, StableHLO, checkify, profiler, or the JAX repo. It helps turn NumPy or PyTorch-style code into pure functional JAX, fix tracer/control-flow/shape/PRNG bugs, remove recompiles and host-device syncs, choose transforms and sharding strategies, inspect jaxpr/lowering/IR, and benchmark compiled code correctly.

Writing & Docsscripts

nature-article-writer

Included

Drafts, rewrites, diagnostically critiques, and style-calibrates primary research manuscripts for Nature and Nature Portfolio journals. Use when the user wants a Nature-style title, summary paragraph or abstract, introduction, results, discussion, methods, figure legends, presubmission enquiry, cover letter, reviewer response, or when a scientific draft sounds generic, jargon-heavy, structurally weak, or AI-ish and needs precise, broad-reader-friendly prose without inventing data, analyses, or references. Best for primary research articles and letters rather than reviews or press releases unless explicitly adapting one.

Writing & Docsscripts

deckrd

Included

Document-driven framework that derives requirements, specifications, implementation plans, and executable tasks from goals through structured AI dialogue. Use when user says "write requirements", "create spec", "plan implementation", "derive tasks", "structure this feature", "break down into tasks", or "document this module". Also use for reverse engineering existing code into docs (/deckrd rev). Do NOT use for direct code writing — use /deckrd-coder after tasks are generated. Do NOT use when the user only wants to run or fix existing code without planning.

Writing & Docsscripts

clinical-decision-support

Included

Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.

Writing & Docsscripts

handling-sf-data

Included

Salesforce data operations with 130-point scoring. Use this skill to create, update, delete, bulk import/export, generate test data, and clean up org records using sf CLI and anonymous Apex. TRIGGER when: user creates test data, performs bulk import/export, uses sf data CLI commands, needs data factory patterns for Apex tests, or needs to seed/clean records in a Salesforce org. DO NOT TRIGGER when: SOQL query writing only (use querying-soql), Apex test execution (use running-apex-tests), or metadata deployment (use deploying-metadata).

Writing & Docsscripts

accelint-ac-to-playwright

Included

Convert and validate acceptance criteria for Playwright test automation. Use when user asks to (1) review/evaluate/check if AC are ready for automation, (2) assess if AC can be converted as-is, (3) validate AC quality for Playwright, (4) turn AC into tests, (5) generate tests from acceptance criteria, (6) convert .md bullets or .feature Gherkin files to Playwright specs, (7) create test automation from requirements. Handles both bullet-style markdown and Gherkin syntax with JSON test plan generation and validation.

Writing & Docsscripts