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/cloud-sql-sqlserver/cloud-sql-sqlserver-monitornpx skills add gemini-cli-extensions/cloud-sql-sqlserver --skill cloud-sql-sqlserver-monitorgit clone --depth 1 https://github.com/gemini-cli-extensions/cloud-sql-sqlserverWhat 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 | $0.00026 | $0.02264 |
| Opus 5 | $0.00013 | $0.01132 |
| Sonnet 5 | $0.00005 | $0.00453 |
| Haiku 4.5 | $0.00003 | $0.00226 |
Grade A, and why
cloud-sql-sqlserver-monitor 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 — 87 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
get_system_metrics
Fetches system level cloudmonitoring data (timeseries metrics) for a SqlServer instance using a PromQL query. Take projectId and instanceId from the user for which the metrics timeseries data needs to be fetched.
To use this tool, you must provide the Google Cloud projectId and a PromQL query.
Generate PromQL query for SqlServer system metrics. Use the provided metrics and rules to construct queries, Get the labels like instance_id from user intent.
Defaults:
- Interval: Use a default interval of
5mfor_over_timeaggregation functions unless a different window is specified by the user.
PromQL Query Examples:
- Basic Time Series:
avg_over_time({"__name__"="cloudsql.googleapis.com/database/cpu/utilization","monitored_resource"="cloudsql_database","project_id"="my-projectId","database_id"="my-projectId:my-instanceId"}[5m]) - Top K:
topk(30, avg_over_time({"__name__"="cloudsql.googleapis.com/database/cpu/utilization","monitored_resource"="cloudsql_database","project_id"="my-projectId","database_id"="my-projectId:my-instanceId"}[5m])) - Mean:
avg(avg_over_time({"__name__"="cloudsql.googleapis.com/database/cpu/utilization","monitored_resource"="cloudsql_database","project_id"="my-projectId","database_id"="my-projectId:my-instanceId"}[5m])) - Minimum:
min(min_over_time({"__name__"="cloudsql.googleapis.com/database/cpu/utilization","monitored_resource"="cloudsql_database","project_id"="my-projectId","database_id"="my-projectId:my-instanceId"}[5m])) - Maximum:
max(max_over_time({"__name__"="cloudsql.googleapis.com/database/cpu/utilization","monitored_resource"="cloudsql_database","project_id"="my-projectId","database_id"="my-projectId:my-instanceId"}[5m])) - Sum:
sum(avg_over_time({"__name__"="cloudsql.googleapis.com/database/cpu/utilization","monitored_resource"="cloudsql_database","project_id"="my-projectId","database_id"="my-projectId:my-instanceId"}[5m])) - Count streams:
count(avg_over_time({"__name__"="cloudsql.googleapis.com/database/cpu/utilization","monitored_resource"="cloudsql_database","project_id"="my-projectId","database_id"="my-projectId:my-instanceId"}[5m])) - Percentile with groupby on database_id:
quantile by ("database_id")(0.99,avg_over_time({"__name__"="cloudsql.googleapis.com/database/cpu/utilization","monitored_resource"="cloudsql_database","project_id"="my-projectId","database_id"="my-projectId:my-instanceId"}[5m]))
What ships with it
1 file 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 · 87 lines · 26 tokens per session scan A 37d4c8f0a242
cloud-sql-sqlserver-monitor is a skill published in the GitHub repository gemini-cli-extensions/cloud-sql-sqlserver (7 stars, last pushed 5d ago), licensed Apache-2.0. It adds 26 tokens to every session and 2,264 once invoked, about $0.0001 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.
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