Official agent skill

Google Cloud Filestore Autoscale

by google in google/skills

Inspects Filestore capacity and utilization on Google Cloud, evaluates storage scaling rules, and performs capacity autoscaling (scale UP for low free space or scale DOWN for cost optimization).

OfficialApache-2.0Auto-check passedDevOps & Cloud

Install Google Cloud Filestore Autoscale

skills CLI
$ npx skills add google/skills --skill google-cloud-filestore-autoscale -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install google/skills google-cloud-filestore-autoscale --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/cloud/google-cloud-filestore-autoscale .claude/skills/google-cloud-filestore-autoscale && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
google-cloud-filestore-autoscale
GitHub stars
21k
Token cost
~3.2k tokens
SKILL.md length
1,492 words
Files
4 (incl. references)
Skills in repo
147
Repo updated
First seen
Licence
Apache-2.0

At a glance

Inspects Filestore capacity and utilization on Google Cloud, evaluates storage scaling rules, and performs capacity autoscaling (scale UP for low free space or scale DOWN for cost optimization).

  • Works in 3 steps: Discovery & Read Operations → Autoscale Needed Matrix → Execution & Confirmation Workflow
  • Monitoring Filestore instance headroom
  • SKILL.md covers Prerequisites / IAM Requirements, Quick Start, Attribution and Conceptual & Informational…, plus 4 more sections
  • Calls gcloud

What it does

Google Cloud Filestore Autoscale is an agent skill from google/skills, published by the product's own GitHub organization. Inspects Filestore capacity and utilization on Google Cloud, evaluates storage scaling rules, and performs capacity autoscaling (scale UP for low free space or scale DOWN for cost optimization). Use when monitoring Filestore instance headroom, resizing instance shares, configuring automated growth/shrink thresholds (custom thresholds apply globally across projects in session memory), or preventing out-of-space outages. Don't use for Cloud Storage (GCS) buckets, Persistent Disk block storage, or NetApp Volumes.

Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/instance-tiers-specs.md`, `references/monitoring-metrics.md` and `references/troubleshooting-errors.md`).

It sits in DevOps & Cloud, covering Incident response and Agent memory. It works with Google Cloud. The repository describes itself as: Agent Skills for Google products and technologies. The licence is Apache-2.0.

When your agent uses it

  • Monitoring Filestore instance headroom
  • Resizing instance shares
  • Configuring automated growth/shrink thresholds (custom thresholds apply globally across projects in session memory)
  • Preventing out-of-space outages

Example prompts

  • “Use the google-cloud-filestore-autoscale skill to inspect Filestore capacity and utilization on Google Cloud, evaluates storage scaling rules, and…”
  • “/google-cloud-filestore-autoscale”

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Discovery & Read Operations
  2. Autoscale Needed Matrix
  3. Execution & Confirmation Workflow

What it can do on your machine

Read from SKILL.md and the folder at commit 5120a76. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • gcloud

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • cloud.google.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Google Cloud Filestore Autoscale loads about 3.2k tokens when it runs, and up to ~5.1k if it reads all its reference files. Until then it costs about 137 tokens; SKILL.md has 1,492 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~137
When it runs · the whole SKILL.md, loaded when a task matches
~3.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from google/skills at commit 5120a76, republished under its Apache-2.0 licence (© google). 1,492 words, ~3,158 tokens.

Download SKILL.mdSave it as .claude/skills/google-cloud-filestore-autoscale/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
google-cloud-filestore-autoscale
description
Inspects Filestore capacity and utilization on Google Cloud, evaluates storage scaling rules, and performs capacity autoscaling (scale UP for low free space or scale DOWN for cost optimization). Use when monitoring Filestore instance headroom, resizing instance shares, configuring automated growth/shrink thresholds (custom thresholds apply globally across projects in session memory), or preventing out-of-space outages. Don't use for Cloud Storage (GCS) buckets, Persistent Disk block storage, or NetApp Volumes.
metadata.version
1.0.1
metadata.category
Storage

Filestore Autoscale

This skill enables agents to inspect, evaluate, and modify Filestore instance capacities across Google Cloud projects based on configured thresholds.

Prerequisites / IAM Requirements

Before an agent or user can execute this skill, their runtime Service Account must possess the following IAM roles on the target project(s):

  • roles/file.editor (Required for listing instances and triggering scale up/down updates)
  • roles/monitoring.viewer (Required for reading Cloud Monitoring capacity metrics used_bytes)
  • roles/mcp.toolUser (Required if utilizing backend Filestore MCP tools)

Quick Start

  1. Ensure gcloud is installed. See gcloud installation guide if needed.

  2. Enable essential APIs:

    bash
    gcloud services enable file.googleapis.com monitoring.googleapis.com --quiet
  3. Inspect fleet capacity and free space (see "Discovery & Read Operations" below).

  4. Evaluate against configured up/down capacity thresholds.

  5. Scale target instances and apply attribution tags.

Attribution

Tag every Cloud Filestore command or API request provided or executed. Prefix gcloud commands with the correct metrics environment targeting this skill:

bash
CLOUDSDK_METRICS_ENVIRONMENT="gcs-skills gcs-skills/1.0 (skill:google-cloud-filestore-autoscale)" \
gcloud filestore instances update ...

On direct HTTP calls to the REST API, append the User-Agent:

User-Agent: gcs-skills/1.0 (skill:google-cloud-filestore-autoscale)

Conceptual & Informational Queries (CRITICAL)

For purely conceptual, educational, or informational questions (e.g., "What are Filestore scaling limits?", "Can Basic instances scale down?", "Explain Filestore Tiers"):

  • Rule: Answer immediately using your pre-trained knowledge and the matrix below.
  • Constraint: Do not execute external tool calls or API requests for basic knowledge questions.

Handling "No-Command" Constraints (CRITICAL)

If the user prompt contains constraints like "Do not execute commands", "without executing", or "read-only":

  • Rule: Strictly avoid calling the run_command tool to execute any shell or gcloud commands (including read-only list/describe commands).
  • Discovery:
    1. First, check if Filestore MCP tools (list_instances, get_instance) are available and use them (these are API calls, not command executions).
    2. If MCP tools are not available, search local markdown documentation files (e.g., references/instance-tiers-specs.md) for any mock instance definitions or project details matching the request. (Do NOT attempt to read evaluation config files such as EVAL.yaml or EVAL.txtpb during evaluation runs as access is restricted).
    3. If no data can be found, explain the required steps and formulas, and output the exact commands the user should run, without executing them yourself.
  • Mandatory User Confirmation Requirement: Even when the user prompt asks not to execute commands or asks only for command syntax/recommendations, your response MUST STILL end with a clear question prompting the user for confirmation before executing any capacity resizing commands (e.g., "Would you like me to proceed with scaling [instance] from [A] TiB to [B] TiB? Please confirm to execute.").

Tier & Capacity Limits Matrix

Filestore tiers enforce specific boundaries and behaviors. The skill must accept both modern UI names (Basic, Zonal, Regional) and legacy API enums interchangeably.

See references/instance-tiers-specs.md for the full Tier & Capacity Limits Matrix (Min/Max capacities, step increments).

Critical Thresholds:

  • Basic HDD / Basic SSD: Can scale up, but cannot scale down.
  • Zonal / Regional: Can scale down, but cannot shrink below their minimum floor (1 TiB or 10 TiB depending on band) AND cannot shrink below the current used_bytes metric.

Core Operational Workflow

1. Discovery & Read Operations
  • Step 1 (Fleet Discovery): Call the MCP tool list_instances(parent='projects/{project_id}/locations/-') or CLI gcloud filestore instances list --project={project_id} to discover all Filestore instances in the target project. Read the capacityGb and tier directly from the instances returned.

  • Step 2 (Single Bulk Utilization Metric Query): Immediately after discovering instances, query the Cloud Monitoring API for the file.googleapis.com/nfs/server/used_bytes metric across the entire project in a single request (see references/monitoring-metrics.md for runtime-specific options including GCP REST API, gcloud, curl, and MCP tools).

    CRITICAL: Make exactly ONE bulk metric request for the entire project. NEVER emit multiple per-instance queries or loops. Do NOT filter by zone or region.

  • Step 3 (Metric Extraction & Calculation):

    • Match each instance's short name (or resource.labels.instance_name / metric.labels.instance_name) in the returned timeSeries data to extract its latest int64Value bytes.
    • If an instance is not listed in timeSeries or has no points, default its used_bytes to 0.
    • Calculate used_bytes_gb = used_bytes / (1024^3).
    • Calculate Free Space % = ((capacityGb - used_bytes_gb) / capacityGb) * 100.
    • NEVER leave Used Bytes or Free Space % as "N/A". Populate actual numbers into the output summary table.
2. Autoscale Needed Matrix

The skill must categorize each evaluated instance into one of 5 definitive verdicts. On the initial analysis/fleet inspection run, the skill suggests the required scaling action with target capacity and update commands, and prompts for user confirmation before executing any autoscale modifications. State the value of the "Autoscale Needed" column clearly as one of the following:

  • Yes (Scale Up): Triggered when free space percentage is below the scale-up safety threshold (< 15% free space remaining). The evaluation response MUST explicitly state that the current free space percentage is below the 15% scale-up safety threshold. Capacity must be increased by 10% (default) or step-size minimum, rounded to the tier's step increment (256 GiB for Small Band [1–9.75 TiB], 2.5 TiB for Large Band [10–100 TiB], as specified in references/instance-tiers-specs.md), not exceeding the maximum capacity. Suggest target capacity, provide the attributed gcloud update command, and MUST conclude the response with a clear question prompting the user for confirmation to execute (e.g., "Would you like me to proceed with scaling [instance] from [A] TiB to [B] TiB? Please confirm to execute.").
  • Yes (Scale Down): Triggered when free space exceeds the scale-down threshold (> 30% free space remaining) and the instance is eligible for downscaling (Zonal or Regional / Enterprise tiers). Apply the default step reduction of -10% of current capacity, aligned to the tier's step increment (256 GiB for Small Band [1–9.75 TiB], 2.5 TiB for Large Band [10–100 TiB], as specified in references/instance-tiers-specs.md). For example, for a 2 TiB (2048 GiB) Enterprise / Regional instance, rounding to the 256 GiB step yields a proposed target capacity of 1.75 TiB (1792 GiB, or 1.8 TiB). The response MUST explicitly verify that the proposed target capacity (e.g. 1.75 TiB / 1792 GiB or 1.8 TiB) remains strictly above both the tier's minimum capacity floor (e.g. 1 TiB for Enterprise / Small Band, 10 TiB for Large Band) and currently used space (e.g. 0.9 TiB). Do NOT reduce directly to the floor in a single step. Suggest target capacity, estimated cost savings, provide the attributed gcloud update command, and prompt the user for confirmation to execute.
  • No (Healthy): Triggered when the instance's free space is within the optimal operating range (15% – 30%). No action required.
  • No (At min capacity limit): Triggered when free space is > 30%, but the instance is already at the minimum allowed tier capacity floor (e.g. 1 TiB for Small Band or 10 TiB for Large Band) or currently used space limit. No action can be taken.
  • No (Tier cannot scale down): Triggered when free space is > 30%, but the instance is on a Basic tier (Basic HDD / Basic SSD) which does not support downscaling. The agent must explicitly inform the user that scale-down is not supported and suggest data migration instead. No action can be taken.
Show full SKILL.md (370 more words)Show less
Output Format

Every status report, evaluation, or recommendation response MUST include a markdown table summarizing the evaluated instances. Even if evaluating a single instance, format it as a table. The table MUST contain the following columns:

  • Instance
  • Service Tier
  • Provisioned Capacity
  • Used Bytes
  • Free Space %
  • Autoscale Needed (MUST contain one of: Yes (Scale Up), Yes (Scale Down), No (Healthy), No (At min capacity limit), or No (Tier cannot scale down))

Example standard output table:

markdown
| Instance | Service Tier | Provisioned Capacity | Used Bytes | Free Space % | Autoscale Needed | Proposed Action |
|---|---|---|---|---|---|---|
| `[instance-name]` | REGIONAL | 2048 GiB | 900 GiB | 56.05% | Yes (Scale Down) | Scale down to 1792 GiB. `CLOUDSDK_METRICS_ENVIRONMENT=... gcloud filestore instances update ...` |
3. Execution & Confirmation Workflow
  1. Analysis & Recommendation (First Run / Inspection):
    • Calculate step-aligned target capacity adhering to tier ceilings, floors, and basic scale-up only rules.
    • Present the summary table and proposed actions.
    • MANDATORY USER CONFIRMATION PROMPT: Whenever recommending target capacity or providing a gcloud filestore instances update command, your response MUST explicitly include a clear question asking the user to confirm execution before any modifications are made (e.g. "Would you like me to proceed with scaling [instance] from [A] TiB to [B] TiB? Please confirm to execute.") to prevent accidental billing spikes or capacity exhaustion.
    • Do not execute autoscale commands without user confirmation.
  2. Execution upon Confirmation:
    • Once the user confirms (e.g., "Yes, proceed with scaling", "Scale instance X"), execute the attributed gcloud filestore instances update command on the confirmed instance(s).
  3. Fallback:
    • If execution fails due to Prod mutation restrictions, output the failure reason and provide the user with the exact attributed gcloud command to run manually, reminding them to confirm before manual execution.
Custom Thresholds

When the user configures or passes custom threshold values in prompts (e.g. "Scale up if free space drops below 10% with a 20% step", or custom max_threshold / up_increment):

  1. Global Session Memory Confirmation: The response MUST accept and acknowledge the custom thresholds and MUST explicitly confirm that custom thresholds apply globally across projects in session memory, explicitly mentioning the target project IDs evaluated or active in session memory to prevent accidental cross-project misconfiguration.
  2. Configuration Summary: The response MUST display the updated active configuration summary showing all active thresholds and step increments.
  3. Preserve Overrides: The response MUST NOT revert to default thresholds (15% / 10%) when custom overrides are provided.

Reference Directory

For progressive disclosure of deeper topics, consult the references/ directory:

© google, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in skills/cloud/google-cloud-filestore-autoscale of google/skills.

  • SKILL.md
  • references/instance-tiers-specs.md
  • references/monitoring-metrics.md
  • references/troubleshooting-errors.md

Open the folder on GitHubat commit 5120a76

Compare with similar skills

Google Cloud Filestore Autoscale next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Google Cloud Filestore Autoscale compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Google Cloud Filestore Autoscale this skillgoogle/skills21k—~3.2kAutomated safety check: PassApache-2.0
Vertex Engine Inspectorjeremylongshore/tons-of-skills-marketplace2.8k—~1.7kAutomated safety check: PassMIT
Conducting Cloud Incident Responsemukul975/Anthropic-Cybersecurity-Skills34k—~3kAutomated safety check: PassApache-2.0
Myclaw BackupLeoYeAI/openclaw-backup659—~1.8kAutomated safety check: PassMIT
Thememoriamatrixorigin/memoria609—~728Automated safety check: PassApache-2.0
Loop Triage Reportcobusgreyling/loop-engineering11k—~500Automated safety check: PassMIT

Similar skills

  • Vertex Engine Inspector

    jeremylongshore/tons-of-skills-marketplace

    Inspect and validate Vertex AI Agent Engine deployments including Code Execution Sandbox, Memory Bank, A2A protocol compliance, and security posture.

    2.8k GitHub stars~1.7k tokensUpdated yesterday
    DevOps & CloudAuto-check passed
  • Conducting Cloud Incident Response

    mukul975/Anthropic-Cybersecurity-Skills

    Respond to security incidents in AWS, Azure, and GCP via identity-based containment, cloud-native log analysis (CloudTrail, Azure Activity Logs, GCP Audit Logs), resource isolation, and forensic…

    34k GitHub stars~3k tokensUpdated 1 mo ago
    DevOps & CloudAuto-check passed
  • Myclaw Backup

    LeoYeAI/openclaw-backup

    Backup and restore all OpenClaw configuration, agent memory, skills, and workspace data.

    659 GitHub stars~1.8k tokensUpdated 7 mo ago
    DevOps & CloudAuto-check passed
  • Thememoria

    matrixorigin/memoria

    Use Memoria as OpenClaw's durable memory slot. An agent skill from matrixorigin/memoria.

    609 GitHub stars~728 tokensUpdated yesterday
    DevOps & CloudAuto-check passed
  • Loop Triage Report

    cobusgreyling/loop-engineering

    Turns CI failures, open issues, recent commits and chat threads into a prioritized markdown report that an automation loop can act on without inventing architecture work.

    11k GitHub stars~500 tokensUpdated yesterday
    DevOps & CloudAuto-check passed
  • Agentcore Ops Review

    aws/tools-for-devops-agent

    Official

    Comprehensive operational review procedures for Amazon Bedrock AgentCore resources aligned with the AWS Well-Architected Framework.

    102 GitHub stars~4k tokensUpdated 2 days ago
    DevOps & CloudAuto-check passed

More from google/skills

All 147 skills in this repo
  • Official

    Query Cloud Trace spans, filter by latency thresholds or error status, correlate distributed traces with Cloud Logging, and diagnose latency bottlenecks across Google Cloud services.

    21k GitHub stars~1.7k tokensUpdated yesterday
    Auto-check passed
  • Official

    Manages Google Cloud Privileged Access Manager entitlements and grants: create and edit entitlements, request temporary access, and approve or deny pending grants.

    21k GitHub stars~3.2k tokensUpdated yesterday
    Auto-check passed
  • Official

    Writes Terraform alerting policies for AI agents that emit OpenTelemetry metrics, covering reliability, cost, safety, security and quality signals on Google Cloud.

    21k GitHub stars~4.2k tokensUpdated yesterday
    Auto-check passed
  • Official

    Deploys open models or custom weights from Model Garden to Agent Platform endpoints, checks deployment status and cleans up endpoints, confirming before any change.

    21k GitHub stars~5k tokensUpdated yesterday
    Auto-check passed
  • Official

    Searches, manages and scaffolds skills in the Gemini Enterprise Agent Platform Skill Registry using bundled Python scripts and Google Cloud credentials.

    21k GitHub stars~584 tokensUpdated yesterday
    Auto-check passed
  • Designs GCP infrastructure as local Terraform, validates and scans it against best practices, then imports it to Application Design Center for deployment and troubleshooting.

    21k GitHub stars~4.4k tokensUpdated yesterday
    Auto-check passed

Works with

Questions about Google Cloud Filestore Autoscale

What does Google Cloud Filestore Autoscale do?

Inspects Filestore capacity and utilization on Google Cloud, evaluates storage scaling rules, and performs capacity autoscaling (scale UP for low free space or scale DOWN for cost optimization). Google Cloud Filestore Autoscale is an agent skill from google/skills, published by the product's own GitHub organization. Inspects Filestore capacity and utilization on Google Cloud, evaluates storage scaling rules, and performs capacity autoscaling (scale UP for low free space or scale DOWN for cost optimization).

When should I use Google Cloud Filestore Autoscale?

Google Cloud Filestore Autoscale fits situations like: monitoring Filestore instance headroom; resizing instance shares; configuring automated growth/shrink thresholds (custom thresholds apply globally across projects in session memory); preventing out-of-space outages.

How do I install Google Cloud Filestore Autoscale in Claude Code?

Run `npx skills add google/skills --skill google-cloud-filestore-autoscale -a claude-code`. Or copy the skill folder (skills/cloud/google-cloud-filestore-autoscale in google/skills) into .claude/skills/google-cloud-filestore-autoscale in your project. Claude Code loads it when a task matches its description.

How do I install Google Cloud Filestore Autoscale in Codex?

Run `npx skills add google/skills --skill google-cloud-filestore-autoscale -a codex`. Or copy the skill folder (skills/cloud/google-cloud-filestore-autoscale in google/skills) into .agents/skills/google-cloud-filestore-autoscale in your project. Codex loads it when a task matches its description.

Can I use Google Cloud Filestore Autoscale in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add google/skills --skill google-cloud-filestore-autoscale -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/google-cloud-filestore-autoscale, .gemini/skills/google-cloud-filestore-autoscale, .github/skills/google-cloud-filestore-autoscale and .opencode/skills/google-cloud-filestore-autoscale in your project.

What does Google Cloud Filestore Autoscale need to run?

Going by SKILL.md and its folder, Google Cloud Filestore Autoscale needs the command-line tools its instructions call (gcloud).

Does Google Cloud Filestore Autoscale access the network?

SKILL.md names 1 domain. As links in the text: cloud.google.com. This is read from the text; nothing was executed.

Is Google Cloud Filestore Autoscale safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Google Cloud Filestore Autoscale use?

Google Cloud Filestore Autoscale is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Google Cloud Filestore Autoscale use?

About 3.2k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2k tokens, read only when the agent opens those files.

What are the alternatives to Google Cloud Filestore Autoscale?

Skills that share tags, products or a category with Google Cloud Filestore Autoscale: Vertex Engine Inspector (jeremylongshore/tons-of-skills-marketplace, 2.8k stars), Conducting Cloud Incident Response (mukul975/Anthropic-Cybersecurity-Skills, 34k stars), Myclaw Backup (LeoYeAI/openclaw-backup, 659 stars) and Thememoria (matrixorigin/memoria, 609 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Google Cloud Filestore Autoscale?

google (a GitHub organization, an official publisher) maintains it in google/skills, which has 21,069 GitHub stars. The repository holds 147 skills in this directory. The repository was last updated on October 9, 2026.

Source: google/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.