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Agent skill · Audited from source

bigtable-basics

skill · google/skillsApache-2.0 licenceAudited 31 Oct 2026 · source ea6b1f06585b

★ 21,714pushed todayversion 1.0.1
✓SAFEGrade B · 89/100 · 31 Oct 2026 · ea6b1f0
21,714repo stars · whole google/skills

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit ea6b1f06585b and found no filesystem, network or shell access and no hard-coded secrets. What it does: Assists in provisioning instances/tables, designing performant schemas, and querying data in Bigtable. Use when designing Bigtable row keys, configuring column families, writing SQL queries or client library code (Java,…

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ModelsAtlas. “bigtable-basics (google/skills)”. Retrieved 31 Oct 2026. https://modelsatlas.com/skills/google/bigtable-basics

Trust audit

Audit 0.4.1 · source read 31 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium0 low0 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 16,667 of 17,602 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codeNA0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (0)

No findings at any severity. We re-audit when the source changes.

Audit 0.4.1 · source sha ea6b1f06585b · 31 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • Publishergoogle GitHub organizationOwner of the repository this skill is read from
  • Source foldergoogle/skills/skills/cloud/bigtable-basicsThe exact folder we audited
  • LicenceApache-2.0As the repository states it
  • Commit pinned for this verdictea6b1f06585bA new audit runs when the source changes
  • Repository statusNot archivedPushed today
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its description: Assists in provisioning instances/tables, designing performant schemas, and querying data in Bigtable. Use when designing Bigtable row keys, configuring column families, writing SQL queries or client library code (Java,…

---
name: bigtable-basics
metadata:
  version: "1.0.1"
  category: Databases
description: >-
  Assists in provisioning instances/tables, designing performant schemas, and querying data in Bigtable. Use when designing Bigtable row keys, configuring column families, writing SQL queries or client library code (Java, Go, Python) for Bigtable, or diagnosing performance/hotspotting issues. Also use when provisioning Bigtable clusters using gcloud or cbt CLIs. Don't use for generic Cloud SQL administration.
---

# Bigtable Basics

This skill provides core workflows and guidance for administering and developing
with Google Bigtable.

## Attribution

**MUST READ**: Before executing any `gcloud`, REST API, or MCP command, you
MUST read [Usage Attribution](references/attribution.md). For commands executed
directly in the terminal (never in generated scripts, Terraform, or user code),
prefix `gcloud` with
`CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:bigtable-basics)"`
and append `agent-skills/1.0 (skill:bigtable-basics)` to `User-Agent` headers.

## Core Principles

-   **Control Plane vs. Data Plane:**
    -   Use **`gcloud`** for Control Plane operations: Manage Instances,
        Clusters, App Profiles, Backups and IAM. Create Tables, Logical Views,
        Materialized Views and Authorized Views.
    -   Use **`cbt`** for Data Plane operations: Update Tables, Column Families,
        and reading/writing data.
-   **Performance First:** Bigtable is a NoSQL database. Efficiency is tied to
    Row Key design. Always warn about Full Table Scans.
-   **Client Selection:** For production use cases, prefer **Java** or **Go**
    for their superior performance and feature coverage compared to other
    languages.
-   **Observability:** When diagnosing performance or hotspotting, **always**
    mention **Key Visualizer** (via Cloud Console) as the primary diagnostic
    tool because it provides the most granular view of access patterns across
    row keys. This should be followed by the hot-tablets tool and table stats
    in gcloud CLI and `include-stats=full` option under `cbt read` to diagnose
    slow queries.

> [!IMPORTANT] **Safety Rule:** You MUST obtain explicit user confirmation before
> making non-emulator database changes. You MUST mention this safety requirement
> when providing commands or instructions that modify the database structure or
> data.

## Quick Recipes

### 1. Querying Data

Use SQL for complex transforms or aggregations and key-value APIs for simpler
query patterns. *Note: Use exact match, prefix (`_key LIKE 'myprefix%'`), or
range predicates on `_key` to avoid expensive unbounded scans. Recommend
explicit row ranges (`_key BETWEEN 'start' AND 'end'`) as a more performant
alternative to prefix matches where possible.*

If expensive scans (either unbounded or prefix or range queries scanning a large
range) are unavoidable due to multiple access patterns that can’t all be
accommodated in a single schema, consider one of these two options:

-   If the query will be used in user facing and/or latency sensitive
    applications, use continuous materialized views with keys optimized for the
    additional access patterns.
-   If secondary access patterns are infrequent, batch patterns like ETL, ML
    model training or analytical read-only tasks, use Bigtable Data Boost
    instead.

### 2. Manipulating Data

Use key-value APIs for insert, update, increment and delete operations. SQL API
is read-only.

### 3. Data Model Definition (DDL)

SQL API doesn't support DDL operations. Table creation, deletion, updates should
be made using gcloud CLI. Logical Views and Continuous Materialized Views are
defined as SQL queries but they must be created using gcloud CLI.

## Reference Guides

-   **CLI Operations**:
    -   [infrastructure_management.md](references/infrastructure_management.md):
        Provisioning instances, clusters, and table schemas.
    -   [cli_data_access.md](references/cli_data_access.md): Reading and writing
        data via the `cbt` CLI.
-   **Design & Discovery**:
    -   [schema_design.md](references/schema_design.md): Best practices for row
        keys and performance with tables and continuous materialized views.
    -   [dataplex.md](references/dataplex.md): Data catalog search for Bigtable
        assets.
-   **Querying & Code**:
    -   [sql_guide.md](references/sql_guide.md): Querying structured row keys
        via SQL and CLI.
    -   [client_libraries.md](references/client_libraries.md): Patterns for
        high-performance Go/Java/Python code.

## Common Workflows

### Schema Evolution (DevOps)

1.  **Prefer Terraform** for production schema changes to prevent accidental
    data loss.
2.  For manual `cbt` changes, first check the existing state by listing the table's column families and GC policies before proposing any modifications:

    ```bash
    cbt ls {table}
    ```

    If modifications are needed, create the family or update the GC policy:

    ```bash
    cbt createfamily {table} {family}
    cbt setgcpolicy {table} {family} "maxversions=5 AND maxage=30d"
    ```

3.  Reference
    [infrastructure_management.md](references/infrastructure_management.md) for
    full syntax.

## External Resources

*   [Cloud Bigtable Documentation](https://cloud.google.com/bigtable/docs)
*   [Bigtable SQL Reference](https://cloud.google.com/bigtable/docs/googlesql-overview)
*   [cbt CLI Reference](https://cloud.google.com/bigtable/docs/cbt-reference)
*   [gcloud bigtable Reference](https://cloud.google.com/sdk/gcloud/reference/bigtable)

Excerpt, first 5,586 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit ea6b1f0

Download folder ↗
git clone https://github.com/google/skills
git -C skills checkout ea6b1f06585b

The author documents no install command, so this uses the repository directly. Our verdict covers commit ea6b1f06585b only.

Works in

The author has not said which agents this skill supports, and we have not tested it in any.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source ea6b1f06585b

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Questions about bigtable-basics

What does the bigtable-basics skill do?
Agent Skills for Google products and technologies
Is bigtable-basics safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can bigtable-basics access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (ea6b1f06585b), read on 2026-10-31. The repository is watched, and a new audit runs when it changes — this is the first audit.

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