google-cloud-filestore-autoscale
Inspects Google Cloud Filestore capacity and utilization, evaluates storage scaling rules, and performs capacity autoscaling (scale UP for low free space or scale DOWN for cost optimization)
Install / Use
npx skills add google/skills --skill google-cloud-filestore-autoscaleInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
AutomationSupported Platforms
Tags
Our assessment of google-cloud-filestore-autoscale
google-cloud-filestore-autoscale scores 97/100 on our quality scale, 99th of 1,267 Automation skills we index (top 8%).
Its SKILL.md is 12 KB long, well organised into 14 sections with 3 code examples: a thorough specification that gives an agent plenty to work with.
With 20,340 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 2 days ago, so google-cloud-filestore-autoscale is actively maintained.
- It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.
Automated pattern scan on 2026-09-26. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
google-cloud-filestore-autoscale compared with similar skills
All 4 of these similar skills score higher than google-cloud-filestore-autoscale; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| google-cloud-filestore-autoscale (this skill)by google | 97 | 20.3k | 2d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 85.4k | 10d ago | CLAUDE.md |
| rufloby ruvnet | 100 | 73.3k | 1d ago | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 83.7k | today | MCP Server |
| algorithmic-artby anthropics | 100 | 177.9k | 3d ago | SKILL.md |
Frequently asked questions
- How do I install google-cloud-filestore-autoscale?
- Run
npx skills add google/skills --skill google-cloud-filestore-autoscale. The install tabs above show the steps for each supported agent. - Which AI agents does google-cloud-filestore-autoscale work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is google-cloud-filestore-autoscale safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is google-cloud-filestore-autoscale still maintained?
- The repository was last updated 2 days ago, so google-cloud-filestore-autoscale is actively maintained.
Skill content
View source on GitHubname: google-cloud-filestore-autoscale metadata: version: "1.0.0" category: Storage description: >- Inspects Google Cloud Filestore capacity and utilization, 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.
Google Cloud Filestore Autoscale
This skill enables agents to inspect, evaluate, and modify Google Cloud Filestore instance capacities across GCP 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 metricsused_bytes)roles/mcp.toolUser(Required if utilizing backend Filestore MCP tools)
Quick Start
-
Ensure
gcloudis installed. See gcloud installation guide if needed. -
Enable essential APIs:
gcloud services enable file.googleapis.com monitoring.googleapis.com --quiet -
Inspect fleet capacity and free space (see "Discovery & Read Operations" below).
-
Evaluate against configured up/down capacity thresholds.
-
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:
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_commandtool to execute any shell orgcloudcommands (including read-only list/describe commands). - Discovery:
- First, check if Filestore MCP tools (
list_instances,get_instance) are available and use them (these are API calls, not command executions). - 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 asEVAL.yamlorEVAL.txtpbduring evaluation runs as access is restricted). - 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.
- First, check if Filestore MCP tools (
- 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_bytesmetric.
Core Operational Workflow
1. Discovery & Read Operations
-
Step 1 (Fleet Discovery): Call the MCP tool
list_instances(parent='projects/{project_id}/locations/-')or CLIgcloud filestore instances list --project={project_id}to discover all Filestore instances in the target project. Read thecapacityGbandtierdirectly 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_bytesmetric across the entire project in a single request (seereferences/monitoring-metrics.mdfor 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 returnedtimeSeriesdata to extract its latestint64Valuebytes. - If an instance is not listed in
timeSeriesor has no points, default itsused_bytesto 0. - Calculate
used_bytes_gb = used_bytes / (1024^3). - Calculate
Free Space % = ((capacityGb - used_bytes_gb) / capacityGb) * 100. - NEVER leave
Used BytesorFree Space %as "N/A". Populate actual numbers into the output summary table.
- Match each instance's short name (or
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 attributedgcloudupdate 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 attributedgcloudupdate 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.
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:
InstanceService TierProvisioned CapacityUsed BytesFree Space %Autoscale Needed(MUST contain one of:Yes (Scale Up),Yes (Scale Down),No (Healthy),No (At min capacity limit), orNo (Tier cannot scale down))
Example standard output table:
| 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
- 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 updatecommand, 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.
- Execution upon Confirmation:
- Once the user confirms (e.g., "Yes, proceed with scaling", "Scale instance X"), execute the attributed
gcloud filestore instances updatecommand on the confirmed instance(s).
- Once the user confirms (e.g., "Yes, proceed with scaling", "Scale instance X"), execute the attributed
- Fallback:
- If execution fails due to Prod mutation restrictions, output the failure reason and provide the user with the exact attributed
gcloudcommand to run manually, reminding them to confirm before manual execution.
- If execution fails due to Prod mutation restrictions, output the failure reason and provide the user with the exact attributed
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):
- 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 t
Truncated for display — read the full file on GitHub.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
