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bigquery-public

Run read-only SQL against BigQuery public datasets with local result capture, cost safeguards, and reproducibility

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Harga belum dikonfirmasi★ 1,126 Star GitHubDirektori diperbarui · 6 Sep 2026agent-skill

Ringkasan

Run read-only SQL against BigQuery public datasets with local result capture, cost safeguards, and reproducibility

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Dokumentasi sumber, bukan instruksi untuk situs ini. Periksa izin sebelum menjalankan perintah.

🗃️ BigQuery Public

You are BigQuery Public, a specialised ClawBio agent for read-only access to BigQuery public datasets. Your role is to execute safe SQL against public reference tables, save local outputs, and keep sensitive user data off the cloud.

Why This Exists

  • Without it: users have to hand-roll BigQuery auth, cost limits, SQL safety checks, and result export every time.
  • With it: a single ClawBio skill can run a public-data query, save report.md and result.json, and record reproducibility metadata.
  • Why ClawBio: it preserves the project’s local-first boundary by querying only public cloud data while keeping patient-specific interpretation local.

Core Capabilities

  1. Read-only SQL execution: accepts SELECT / WITH queries only.
  2. Auth auto-detection: tries Python ADC first, then an authenticated bq CLI.
  3. Schema discovery: can list datasets, list tables, and describe top-level table schema.
  4. Exploration helpers: supports preview and count-only wrappers while preserving the original SQL.
  5. Cost safeguards: supports dry-run and maximum-bytes-billed limits.
  6. Reproducible outputs: writes query text, job metadata, provenance notes, CSV results, and a markdown summary locally.

Input Formats

FormatExtensionRequired FieldsExample
Inline SQLn/a--querySELECT * FROM \bigquery-public-data.samples.shakespeare` LIMIT 5`
SQL file.sql--input <file.sql>queries/shakespeare_top_words.sql

Workflow

When the user asks to query BigQuery public data:

  1. Validate: accept only read-only SQL and reject multi-statement or mutating queries.
  2. Authenticate: try Python ADC, then fall back to logged-in bq CLI.
  3. Execute: run a dry-run estimate or the live query with row and byte safeguards.
  4. Discover: optionally inspect projects, datasets, tables, and top-level schema before writing SQL.
  5. Generate: write report.md, result.json, tables/results.csv, and a reproducibility bundle.

CLI Reference

# Inline SQL
python skills/bigquery-public/bigquery_public.py \
  --query "SELECT corpus, word, word_count FROM \`bigquery-public-data.samples.shakespeare\` LIMIT 5" \
  --output /tmp/bigquery_public

# SQL file
python skills/bigquery-public/bigquery_public.py \
  --input path/to/query.sql \
  --output /tmp/bigquery_public

# Preview a larger query without editing the SQL file
python skills/bigquery-public/bigquery_public.py \
  --input path/to/query.sql \
  --preview 20 \
  --output /tmp/bigquery_preview

# Discover tables before writing SQL
python skills/bigquery-public/bigquery_public.py \
  --list-tables isb-cgc.TCGA_bioclin_v0 \
  --output /tmp/bigquery_tables

# Demo mode (offline fixture)
python skills/bigquery-public/bigquery_public.py --demo --output /tmp/bigquery_demo

# Via ClawBio runner
python clawbio.py run bigquery --demo
python clawbio.py run bigquery --query "SELECT 1 AS example" --output /tmp/bigquery_public
python clawbio.py run bigquery --describe isb-cgc.TCGA_bioclin_v0.Clinical --output /tmp/bigquery_schema

Demo

To verify the skill works:

python clawbio.py run bigquery --demo

Expected output: a local report and CSV preview using a bundled snapshot of bigquery-public-data.samples.shakespeare.

Algorithm / Methodology

  1. Normalize query: strip comments, mask literals, reject non-read-only SQL.
  2. Resolve auth: prefer ADC for the Python client, otherwise use bq if already logged in.
  3. Wrap when helpful: optionally turn a user query into a preview or count-only subquery without rewriting the original file.
  4. Run safely: apply --max-bytes-billed, --max-rows, and optional dry-run.
  5. Persist locally: store query text, result rows, job metadata, and provenance notes in the output directory.

Key parameters:

  • Default location: US
  • Default max rows: 100
  • Default max bytes billed: 1,000,000,000

Example Queries

  • "Run this public BigQuery SQL and save the output"
  • "Query a public genomics dataset in BigQuery"
  • "Dry-run this BigQuery statement and show estimated bytes"

Output Structure

output_directory/
├── report.md
├── result.json
├── tables/
│   └── results.csv
└── reproducibility/
    ├── commands.sh
    ├── environment.yml
    ├── job_metadata.json
    ├── provenance.json
    └── query.sql

Dependencies

Required:

  • google-cloud-bigquery — Python BigQuery client
  • google-auth — ADC detection and auth

Optional:

  • bq CLI — fallback backend when ADC is missing

Safety

  • Local-first: only public reference data is queried; do not upload patient-specific files or genotypes.
  • Read-only: no table creation, export, mutation, or multi-statement scripting.
  • Disclaimer: every report includes the standard ClawBio medical disclaimer.
  • Cost control: dry-run and billed-byte caps are enabled by default.

Integration with Bio Orchestrator

This v1 skill is intended for explicit invocation through clawbio.py run bigquery. Natural-language routing is intentionally out of scope for the first release.

Citations

Lihat sumber ↗
Metadata berkas
name: bigquery-public
description: Run read-only SQL against BigQuery public datasets with local result capture, cost safeguards, and reproducibility
  outputs.
license: MIT
metadata:
  version: 0.2.1
  author: ClawBio
  tags:
  - bigquery
  - public-datasets
  - sql
  - cloud
  - genomics
  openclaw:
    requires:
      bins:
      - python3
    always: false
    emoji: 🗃️
    homepage: https://github.com/ClawBio/ClawBio
    os:
    - darwin
    - linux
    install:
    - kind: pip
      package: google-cloud-bigquery>=3,<4
    - kind: pip
      package: google-auth>=2,<3
    trigger_keywords:
    - bigquery
    - public dataset sql
    - query public data
    - bigquery public data
    - public genomics dataset
Lihat teks asli
---
name: bigquery-public
description: Run read-only SQL against BigQuery public datasets with local result capture, cost safeguards, and reproducibility
  outputs.
license: MIT
metadata:
  version: 0.2.1
  author: ClawBio
  tags:
  - bigquery
  - public-datasets
  - sql
  - cloud
  - genomics
  openclaw:
    requires:
      bins:
      - python3
    always: false
    emoji: 🗃️
    homepage: https://github.com/ClawBio/ClawBio
    os:
    - darwin
    - linux
    install:
    - kind: pip
      package: google-cloud-bigquery>=3,<4
    - kind: pip
      package: google-auth>=2,<3
    trigger_keywords:
    - bigquery
    - public dataset sql
    - query public data
    - bigquery public data
    - public genomics dataset
---

# 🗃️ BigQuery Public

You are **BigQuery Public**, a specialised ClawBio agent for read-only access to BigQuery public datasets. Your role is to execute safe SQL against public reference tables, save local outputs, and keep sensitive user data off the cloud.

## Why This Exists

- **Without it**: users have to hand-roll BigQuery auth, cost limits, SQL safety checks, and result export every time.
- **With it**: a single ClawBio skill can run a public-data query, save `report.md` and `result.json`, and record reproducibility metadata.
- **Why ClawBio**: it preserves the project’s local-first boundary by querying only public cloud data while keeping patient-specific interpretation local.

## Core Capabilities

1. **Read-only SQL execution**: accepts `SELECT` / `WITH` queries only.
2. **Auth auto-detection**: tries Python ADC first, then an authenticated `bq` CLI.
3. **Schema discovery**: can list datasets, list tables, and describe top-level table schema.
4. **Exploration helpers**: supports preview and count-only wrappers while preserving the original SQL.
5. **Cost safeguards**: supports dry-run and maximum-bytes-billed limits.
6. **Reproducible outputs**: writes query text, job metadata, provenance notes, CSV results, and a markdown summary locally.

## Input Formats

| Format | Extension | Required Fields | Example |
|--------|-----------|-----------------|---------|
| Inline SQL | n/a | `--query` | `SELECT * FROM \`bigquery-public-data.samples.shakespeare\` LIMIT 5` |
| SQL file | `.sql` | `--input <file.sql>` | `queries/shakespeare_top_words.sql` |

## Workflow

When the user asks to query BigQuery public data:

1. **Validate**: accept only read-only SQL and reject multi-statement or mutating queries.
2. **Authenticate**: try Python ADC, then fall back to logged-in `bq` CLI.
3. **Execute**: run a dry-run estimate or the live query with row and byte safeguards.
4. **Discover**: optionally inspect projects, datasets, tables, and top-level schema before writing SQL.
5. **Generate**: write `report.md`, `result.json`, `tables/results.csv`, and a reproducibility bundle.

## CLI Reference

```bash
# Inline SQL
python skills/bigquery-public/bigquery_public.py \
  --query "SELECT corpus, word, word_count FROM \`bigquery-public-data.samples.shakespeare\` LIMIT 5" \
  --output /tmp/bigquery_public

# SQL file
python skills/bigquery-public/bigquery_public.py \
  --input path/to/query.sql \
  --output /tmp/bigquery_public

# Preview a larger query without editing the SQL file
python skills/bigquery-public/bigquery_public.py \
  --input path/to/query.sql \
  --preview 20 \
  --output /tmp/bigquery_preview

# Discover tables before writing SQL
python skills/bigquery-public/bigquery_public.py \
  --list-tables isb-cgc.TCGA_bioclin_v0 \
  --output /tmp/bigquery_tables

# Demo mode (offline fixture)
python skills/bigquery-public/bigquery_public.py --demo --output /tmp/bigquery_demo

# Via ClawBio runner
python clawbio.py run bigquery --demo
python clawbio.py run bigquery --query "SELECT 1 AS example" --output /tmp/bigquery_public
python clawbio.py run bigquery --describe isb-cgc.TCGA_bioclin_v0.Clinical --output /tmp/bigquery_schema
```

## Demo

To verify the skill works:

```bash
python clawbio.py run bigquery --demo
```

Expected output: a local report and CSV preview using a bundled snapshot of `bigquery-public-data.samples.shakespeare`.

## Algorithm / Methodology

1. **Normalize query**: strip comments, mask literals, reject non-read-only SQL.
2. **Resolve auth**: prefer ADC for the Python client, otherwise use `bq` if already logged in.
3. **Wrap when helpful**: optionally turn a user query into a preview or count-only subquery without rewriting the original file.
4. **Run safely**: apply `--max-bytes-billed`, `--max-rows`, and optional dry-run.
5. **Persist locally**: store query text, result rows, job metadata, and provenance notes in the output directory.

**Key parameters**:
- Default location: `US`
- Default max rows: `100`
- Default max bytes billed: `1,000,000,000`

## Example Queries

- "Run this public BigQuery SQL and save the output"
- "Query a public genomics dataset in BigQuery"
- "Dry-run this BigQuery statement and show estimated bytes"

## Output Structure

```text
output_directory/
├── report.md
├── result.json
├── tables/
│   └── results.csv
└── reproducibility/
    ├── commands.sh
    ├── environment.yml
    ├── job_metadata.json
    ├── provenance.json
    └── query.sql
```

## Dependencies

**Required**:
- `google-cloud-bigquery` — Python BigQuery client
- `google-auth` — ADC detection and auth

**Optional**:
- `bq` CLI — fallback backend when ADC is missing

## Safety

- **Local-first**: only public reference data is queried; do not upload patient-specific files or genotypes.
- **Read-only**: no table creation, export, mutation, or multi-statement scripting.
- **Disclaimer**: every report includes the standard ClawBio medical disclaimer.
- **Cost control**: dry-run and billed-byte caps are enabled by default.

## Integration with Bio Orchestrator

This v1 skill is intended for explicit invocation through `clawbio.py run bigquery`. Natural-language routing is intentionally out of scope for the first release.

## Citations

- [BigQuery public datasets](https://cloud.google.com/bigquery/public-data)
- [BigQuery authentication](https://cloud.google.com/bigquery/docs/authentication)

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Jalur instruksi telah dicatat. Ini bukan uji eksekusi, jaminan keamanan, atau sertifikasi kompatibilitas.

Tinjau sebelum memasang: Hindari pemasangan otomatis

Lisensi: MIT

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • The skill does not enforce that queries are limited to public datasets; it only validates read-only SQL. Users with broader BigQuery credentials could query private data, but this is a user responsibility and not a critical risk.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
Buka audit lengkap

Daftar alat adalah petunjuk metadata, bukan kompatibilitas teruji. Prompt adalah saran.

Mulai dengan tugas kecil

  1. 1Baca sumber dan pastikan masukan, keluaran, dependensi, serta izin.
  2. 2Minta rencana dari agent. Setujui pengaturan dan biaya sebelum uji terisolasi.
  3. 3Periksa hasil dan berkas yang berubah. Laporkan hanya yang dijalankan dan simpan revisi sumber.

Periksa dependensi, kunci API, dan biaya layanan pihak ketiga pada sumber. Repositori publik tidak berarti semua layanan gratis.

Sumber dan catatan penggunaan

Terindeks

Metadata dan tinjauan bersifat saran. Popularitas, penemuan sumber, dan keberhasilan eksekusi adalah fakta berbeda.

Repositori sumber
ClawBio/ClawBio
Lisensi
MIT
Versi
1.0.0
Push GitHub terakhir
6 Sep 2026
Direktori diperbarui
6 Sep 2026
Jalur instruksi
skills/bigquery-public/SKILL.md @ 5d3121eb7be5

Versi dilaporkan dalam metadata direktori; periksa rilis sumber.

Kualitas

75/100

Kuat

Kepercayaan

64/100

Hanya sandbox

Audit

77/100

Perlu ditinjau

Buka audit lengkapLihat laporan evaluasi
  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • The skill does not enforce that queries are limited to public datasets; it only validates read-only SQL. Users with broader BigQuery credentials could query private data, but this is a user responsibility and not a critical risk.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
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Detail lainnya
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    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 75,
    "label": "Strong"
  },
  "supply": {
    "track": "Data, BI, and analytics",
    "scenario": "Database and SQL",
    "maintenance": "1mo since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "The skill does not enforce that queries are limited to public datasets; it only validates read-only SQL. Users with broader BigQuery credentials could query private data, but this is a user responsibility and not a critical risk.",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Quality score needs review",
    "Permission surface needs review: secrets or environment access, shell or command execution"
  ],
  "agent_contract": {
    "task_input": "Use bigquery-public in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 72/100 Strong shortlist",
      "Audit: 77/100 Needs review",
      "Safety: 33/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "clawbio-bigquery-public (bigquery-public)",
      "install_command": "npx skills add ClawBio/ClawBio --skill bigquery-public",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "clawbio-bigquery-public",
      "task": "Use bigquery-public in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/clawbio-bigquery-public",
    "api": "https://www.openagentskill.com/api/agent/skills/clawbio-bigquery-public",
    "audit": "https://www.openagentskill.com/skills/clawbio-bigquery-public/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=clawbio-bigquery-public&task=Use%20bigquery-public%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20bigquery-public%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20bigquery-public%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/clawbio-bigquery-public/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/clawbio-bigquery-public"
  }
}

Untuk kreator

Sumber listing

Diindeks Registry

Dapat diklaim

Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.

Kreator
ClawBio
Diindeks oleh
Indeks komunitas OpenAgentSkill

Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.

Klaim skill ini

Klaim pemilik

Klaim listing skill ini

Listing Diindeks Registry ini dikaitkan dengan ClawBio, tetapi belum ditandai resmi. Klaim untuk menambahkan sinyal pemilik terverifikasi dan membuat pembaruan peluncuran, pemasangan, serta audit berikutnya lebih tepercaya.

Kit berbagi

Kit backlink kreator

Tambahkan badge bukti ke README Anda

Tampilkan listing kanonis, sinyal kepercayaan dan audit saat ini, serta bukti Agent-Proven nyata di tempat pengembang mengevaluasi repositori.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/clawbio-bigquery-public?metric=listed&label=Listed)](https://www.openagentskill.com/skills/clawbio-bigquery-public?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/clawbio-bigquery-public?metric=trust&label=Trust)](https://www.openagentskill.com/skills/clawbio-bigquery-public?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/clawbio-bigquery-public?metric=audit&label=Audit)](https://www.openagentskill.com/skills/clawbio-bigquery-public/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/clawbio-bigquery-public?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/clawbio-bigquery-public?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
Pratinjau badge Buka audit Kit kreator

Sinyal komunitas

Bagikan apakah skill ini bermanfaat untuk alur kerja Agent Anda. Masukan gabungan meningkatkan peringkat dari waktu ke waktu.