Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/gemini-cli-extensions/bigquery-data-analytics/bigquery-datanpx skills add gemini-cli-extensions/bigquery-data-analytics --skill bigquery-datagit clone --depth 1 https://github.com/gemini-cli-extensions/bigquery-data-analyticsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00045 | $0.00755 |
| Opus 5 | $0.00023 | $0.00378 |
| Sonnet 5 | $0.00009 | $0.00151 |
| Haiku 4.5 | $0.00005 | $0.00076 |
Grade A, and why
bigquery-data scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Usage
All scripts can be executed using Node.js. Replace <param_name> and <param_value> with actual values.
Bash:
node <skill_dir>/scripts/<script_name>.js '{"<param_name>": "<param_value>"}'
PowerShell:
node <skill_dir>/scripts/<script_name>.js '{\"<param_name>\": \"<param_value>\"}'
Note: The scripts automatically load the environment variables from various .env files. Do not ask the user to set vars unless skill executions fails due to env var absence.
Scripts
execute_sql
Use this skill to execute sql statement.
Parameters
| Name | Type | Description | Required | Default |
|---|---|---|---|---|
| sql | string | The SQL to execute. | Yes | |
| dry_run | boolean | If set to true, the query will be validated and information about the execution will be returned without running the query. Defaults to false. | No | false |
get_dataset_info
Use this skill to get dataset metadata.
Parameters
| Name | Type | Description | Required | Default |
|---|---|---|---|---|
| project | string | The Google Cloud project ID containing the dataset. | No | |
| dataset | string | The dataset to get metadata information. Can be in project.dataset format. |
Yes |
get_table_info
Use this skill to get table metadata.
Parameters
| Name | Type | Description | Required | Default |
|---|---|---|---|---|
| project | string | The Google Cloud project ID containing the dataset and table. | No | |
| dataset | string | The table's parent dataset. | Yes | |
| table | string | The table to get metadata information. | Yes |
list_dataset_ids
Use this skill to list datasets.
Parameters
| Name | Type | Description | Required | Default |
|---|---|---|---|---|
| project | string | The Google Cloud project to list dataset ids. | No |
list_table_ids
Use this skill to list tables.
Parameters
| Name | Type | Description | Required | Default |
|---|---|---|---|---|
| project | string | The Google Cloud project ID containing the dataset. | No | |
| dataset | string | The dataset to list table ids. | Yes |
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 109 lines · 45 tokens per session scan A 157ad7b823e3
bigquery-data is a skill published in the GitHub repository gemini-cli-extensions/bigquery-data-analytics (49 stars, last pushed 4d ago), licensed Apache-2.0. It adds 45 tokens to every session and 755 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
conductor-setup
Scaffolds the project and sets up the Conductor environment. Use this whenever a project needs to be initialized or if the Conductor configuration is missing.
conductor-new-track
Plans a new track (feature or bug fix), generates spec/plan documents, and updates the registry.
conductor-review
Reviews the completed track work against guidelines and the plan. Acts as a Principal Software Engineer to ensure quality and compliance.
conductor-implement
Executes the tasks defined in the specified track's plan. Use this to start or continue working on a feature, bug fix, or chore.
conductor-revert
Reverts previous work (tracks, phases, or tasks) by identifying associated commits and performing Git reverts.
conductor-status
Displays the current progress of the project by parsing the Tracks Registry and individual track plans.