s3-explore
Skill598 starsChanged 8 months agoMITView on GitHub
Explore and query data on S3, Cloudflare R2, GCS, MinIO, or any S3-compatible storage. Use when the user mentions an s3://, r2://, gs://, or gcs:// URL, asks "what's in this bucket", wants to list remote files, preview remote Parquet/CSV/JSON, or query data on object storage without downloading it. Also triggers when the user wants to know the size, schema, or row count of remote datasets.
In this repository8 other files it gives its agents.
- attach-dbSkill
- convert-fileSkill
- duckdb-docsSkill
- install-duckdbSkill
- querySkill
- read-fileSkill
- read-memoriesSkill
- spatialSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 40
If the URL looks like a directory or bucket (no file extension, or ends with /), list its contents with sizes:
- Very specific: line 55
If the URL points to a specific file or glob pattern (has a file extension or contains *), preview it:
- Distinctive: line 87
If the user asks an analytical question (e.g., "how many rows match X"), write and run the appropriate SQL query.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
You are helping the user explore data on remote object storage using DuckDB.
URL: $0
Question: ${1:-list and describe what's there}
Step 1 — Detect provider and set up credentials
Based on the URL or user context, prepend the appropriate secret configuration:
| Provider | URL patterns | Secret setup |
| AWS S3 | s3:// | CREATE SECRET (TYPE S3, PROVIDER credential_chain); |
| Cloudflare R2 | r2://, s3:// with R2 endpoint | CREATE SECRET (TYPE R2, PROVIDER credential_chain); |
| GCS | gs://, gcs:// | CREATE SECRET (TYPE GCS, PROVIDER credential_chain); |
| MinIO / custom | s3:// with custom endpoint | CREATE SECRET (TYPE S3, KEY_ID '...', SECRET '...', ENDPOINT '...', USE_SSL true); |
For R2, if the user provides an account ID, the endpoint is <account_id>.r2.cloudflarestorage.com. R2 URLs like r2://bucket/path should be rewritten to s3://bucket/path with the R2 secret.
For public buckets (e.g., Overture Maps, AWS open data), no secret is needed — skip this step.
Always prepend:
LOAD httpfs;Step 2 — Determine what the URL points to
If the URL looks like a directory or bucket (no file extension, or ends with /), list its contents with sizes:
duckdb -c "
LOAD httpfs;
<SECRET_SETUP>
SELECT filename, (size / 1024 / 1024)::DECIMAL(10,1) AS size_mb, last_modified
FROM read_blob('<URL>/*')
ORDER BY filename
LIMIT 50;
"Note: only select filename, size, last_modified — never select content, which would download the actual files.
If the URL points to a specific file or glob pattern (has a file extension or contains *), preview it:
duckdb -c "
LOAD httpfs;
<SECRET_SETUP>
DESCRIBE FROM '<URL>';
SELECT count(*) AS row_count FROM '<URL>';
FROM '<URL>' LIMIT 20;
"For Parquet files, get row counts and sizes from metadata (no data download):
duckdb -c "
LOAD httpfs;
<SECRET_SETUP>
SELECT file_name,
sum(row_group_num_rows) AS total_rows,
(sum(row_group_compressed_bytes) / 1024 / 1024)::DECIMAL(10,1) AS compressed_mb
FROM parquet_metadata('<URL>')
GROUP BY file_name;
"Step 3 — Answer the question
Using the listing, schema, or sample data, answer:
${1:-list and describe what's there}
If the user asks an analytical question (e.g., "how many rows match X"), write and run the appropriate SQL query. DuckDB pushes predicates down into Parquet on S3, so filtering is efficient even on large remote datasets.
Error handling
duckdb: command not found→ delegate to/duckdb-skills:install-duckdb- Access denied / 403 → suggest the user check credentials:
aws configure, environment variables, or provide explicit key/secret - Bucket not found / 404 → check the URL and region
- Timeout on large listing → suggest narrowing the glob pattern or adding a prefix
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