duckdb-docs
by duckdbduckdb-docs helps you search DuckDB and DuckLake documentation, blog posts, and indexed reference chunks from a local DuckDB cache. Use it for source-backed answers, exact terminology, and duckdb-docs for Technical Writing workflows when you need precise section references.
This skill scores 74/100, which means it is worth listing for directory users: it has a real, triggerable workflow for searching DuckDB and DuckLake docs, but it still leaves some adoption friction because the description is terse and there is no install command or supporting reference files. Users should expect a practical documentation-retrieval skill, not a fully polished package.
- Explicit trigger and input format: the description says it searches DuckDB/DuckLake docs and accepts a question or keyword.
- Operationally concrete workflow: it checks for DuckDB, installs required extensions, chooses between two documented indexes, and runs a search query.
- Good agent leverage: it returns relevant doc chunks from a locally cached full-text index, reducing guesswork versus a generic web search prompt.
- Metadata is sparse: the description length is 1 and there is no install command, which makes directory evaluation and onboarding less immediate.
- No support files or references are included, so users have to rely mainly on SKILL.md for understanding edge cases and behavior.
Overview of duckdb-docs skill
What duckdb-docs does
The duckdb-docs skill helps you search DuckDB and DuckLake documentation, blog posts, and indexed reference chunks from a local DuckDB cache. It is best for answering “where is this documented?” or “what does the docs say about this feature?” faster than manually browsing the site.
Who it is for
Use the duckdb-docs skill if you write technical content, support users, or need precise source-backed answers for DuckDB or DuckLake. It is especially useful for duckdb-docs for Technical Writing workflows where you need exact terminology, section references, and relevant doc excerpts instead of a generic summary.
Why it is different
This is not a broad chat prompt. The duckdb-docs skill expects a short question or keyword, checks that DuckDB and required extensions exist, then searches a cached full-text index. That makes it practical when you need fast retrieval, but it also means your input must be specific enough for the search index to work well.
How to Use duckdb-docs skill
Install the skill
Use the GitHub skill install flow for duckdb-docs, then confirm the skill is available in your agent environment. The duckdb-docs install step is not the hard part; the real requirement is having a working local DuckDB CLI because the skill uses it directly.
Give it a search-shaped prompt
The duckdb-docs usage pattern is a question, keyword, or short topic, not a full essay. Good inputs look like:
How does DuckDB handle list aggregation?DuckLake catalogsHTTPFS extension install errorcurrent docs for COPY INTO
If you already know the document family, include it. A tighter query usually returns better chunks than a broad request like “explain DuckDB.”
Follow the workflow and inspect the right files
Start with SKILL.md because it contains the execution order and the search-index selection logic. In this repo, there are no helper scripts or reference folders to read first, so the main value comes from understanding the DuckDB CLI checks, extension installation, and the two index options: DuckDB docs/blog versus DuckLake docs.
Practical tips for better retrieval
Choose the index based on intent: default to DuckDB docs + blog for general questions, and mention DuckLake explicitly when your topic is catalogs, preview/stable behavior, or DuckLake-only features. If the answer needs exact phrasing, ask for the section or chunk rather than a loose summary. For duckdb-docs guide style tasks, focus the request on one concept and one version target at a time.
duckdb-docs skill FAQ
Is duckdb-docs only for DuckDB docs?
No. The skill covers both DuckDB docs/blog content and DuckLake docs, with the index chosen from your query. If your request mentions DuckLake, it should route to the DuckLake search cache instead of the default DuckDB one.
What should I know before installing?
The main dependency risk is environment setup, not the docs index itself. The skill checks for the duckdb command and requires httpfs and fts extensions to install successfully. If either is missing, the search flow stops early.
Is it better than a normal prompt?
Yes when you need source-grounded retrieval. A normal prompt can explain a concept, but duckdb-docs is built to find the most relevant documentation chunks quickly. That makes it better for citation-finding, terminology checks, and narrowing a vague question into the exact page or section.
When should I not use it?
Do not use duckdb-docs if you need code execution, data analysis, or a broad conceptual answer that does not depend on the docs. It is a search and retrieval skill, so it works best when the user already knows the topic or can state a clear keyword.
How to Improve duckdb-docs skill
Make the first query narrower
The biggest quality gain comes from clearer input. Instead of How do I load files?, try DuckDB read CSV with read_csv_auto or DuckLake authentication docs. This helps the search step return relevant chunks instead of nearby but unhelpful pages.
Specify the output you want
If you need documentation for writing, support, or training material, say so. duckdb-docs for Technical Writing works better when you ask for exact section names, short source quotes, or the page that best explains a feature’s behavior. That reduces paraphrase and makes the result easier to verify.
Watch for environment failures
Common failure modes are missing DuckDB, failing extension installation, or asking for a topic that belongs to the wrong index. If the skill reports an extension or CLI error, fix the environment first; if the result set feels off, retry with a more precise term or explicitly name DuckDB versus DuckLake.
Iterate from keyword to question
A good duckdb-docs workflow is: start with a keyword, inspect the returned chunks, then refine into a second query that names the exact feature, error, or version. That iterative loop is usually faster and more accurate than trying to solve everything in one broad prompt.