vmware-storage

Server Quality Checklist

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Latest release: v1.8.10
Disambiguation5/5
Each tool targets a distinct operation: datastore listing, file browsing, image scanning, cached image listing, iSCSI lifecycle, and vSAN monitoring. The descriptions clearly differentiate live scans from cached data and browsing from image scanning, leaving no ambiguity.
Naming Consistency3/5
Naming mixes verb-first conventions (list_all_datastores, browse_datastore, scan_datastore_images) with domain-first conventions (storage_iscsi_enable, vsan_health, storage_rescan). While each subgroup is internally consistent, the lack of a single uniform pattern across the toolset is noticeable.
Tool Count5/5
With 11 tools, the server is well-scoped for VMware storage management. Each tool covers a distinct aspect—datastore discovery, image scanning, iSCSI configuration, rescanning, and vSAN monitoring—without redundancy or bloat.
Completeness4/5
The core workflows are covered: datastore listing, file browsing, image scanning (live and cached), full iSCSI enable/status/add/remove/rescan, and vSAN health/capacity. Minor gaps exist (e.g., no create/delete datastore operation), but these are not critical for the server's apparent purpose.
Average 4.8/5 across 11 of 11 tools scored. Lowest: 4.1/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 46 commits in the last 12 weeks
- Last stable release on August 6, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description contradicts the annotations: it claims 'Idempotent: a duplicate address:port returns "already configured" without changes,' but the annotation idempotentHint is false. This is a direct contradiction, so the score is 1 per the rubric. The description otherwise adds useful behavioral context (automatic rescan, audit logging) but the contradiction is disqualifying.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is cleanly structured: first paragraph states purpose and behavior, followed by prerequisite, idempotency, rescan note, audit logging, and return type, then an Args list. It is a bit lengthy but every sentence adds value. No waste, though it could be slightly more compact.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters and an output schema, the description is comprehensive. It covers prerequisites, idempotency, side effects (automatic rescan), logging behavior, and return type. The output schema likely covers the return structure, so not describing it in detail is acceptable. No major gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description provides detailed semantics for all 5 parameters in the Args section. It explains host_name as 'ESXi host name as shown in vCenter inventory,' address as 'IPv4/IPv6 literal; hostnames are rejected,' port range, dry_run behavior, and target as optional. This fully compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Add an iSCSI send (dynamic discovery) target to an ESXi host's software iSCSI adapter, then automatically rescan all HBAs and VMFS volumes to discover new LUNs.' This uses a specific verb and resource, and the phrase 'No separate storage_rescan call is needed afterwards' distinguishes it from sibling tools like storage_rescan and storage_iscsi_remove_target.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states the prerequisite: 'software iSCSI must be enabled first (storage_iscsi_enable); otherwise returns an error with guidance.' It also explicitly notes that no separate storage_rescan call is needed, naming the alternative tool. This gives clear when-to-use and when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description claims the tool is idempotent, but the annotations set idempotentHint to false, which is a direct contradiction. Although the description provides rich behavioral details, the contradiction violates the rule and forces a score of 1.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and every sentence adds value: purpose, context, idempotency, side effects, error handling, and parameter details. It is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers prerequisites, behavior, output, and error remediation. It is complete for an agent to select and invoke the tool, though the annotation contradiction in idempotency is a trust issue.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no property descriptions (0% coverage), but the description's 'Args' section thoroughly explains each parameter, including the exact format for host_name, the meaning of dry_run, and the optional target.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Enable the software iSCSI adapter (vmhba) on an ESXi host.' It uses a specific verb and resource, and distinguishes itself from sibling tools by positioning as a prerequisite for storage_iscsi_add_target.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is provided: 'Required prerequisite before storage_iscsi_add_target' and 'Check current state first with storage_iscsi_status.' This tells the agent when to use the tool and suggests an alternative for checking state.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds useful behavioral context beyond these, such as the [READ] tag, the one-pass enumeration guarantee ('Enumerated in one pass, so truncated is always false'), and the return envelope structure. This enriches the agent's understanding without contradicting annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the purpose and followed by usage guidance and return details. Each sentence provides value, though the 'Args' block slightly duplicates what the schema shows. Overall it is appropriately sized for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only list tool with one optional parameter and no output schema, the description covers the purpose, usage, return envelope, and truncation behavior. It also explains how this tool fits into workflows with sibling tools, making it fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description compensates by explaining that 'target' is an optional vCenter/ESXi target name from config. This adds meaning the schema lacks (which only provides a title and default). The definition is sufficient for the single parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists all datastores with capacity, usage percentage, and accessibility. It also distinguishes itself from siblings by noting it's the first step for obtaining ds_name used by browse_datastore and scan_datastore_images.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs 'Use this first for the ds_name that browse_datastore and scan_datastore_images require', giving a concrete when-to-use scenario and naming the sibling tools that depend on it. This provides clear usage guidance beyond what the schema or annotations offer.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds that it's a live scan, explains the return envelope (items/returned/total/truncated), and guarantees truncated is always false. It does not go into auth or performance, but adds meaningful context beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: a concise summary, usage guidance, return format, and parameter list. Every sentence adds value; no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description adequately describes the response envelope and the guarantee about truncation. It could be more explicit about what fields each image row contains, but given the tool's simplicity, it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, so the description's Args section is essential. It explains ds_name as the datastore name, path as subdirectory (empty for root), and target as optional vCenter/ESXi target, providing meaning that the schema lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with '[READ] Scan a datastore for deployable images (OVA, ISO, OVF, VMDK)', clearly stating the action and resource. It differentiates from list_cached_images by framing this as a live scan, and references sibling list_all_datastores for ds_name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this for a live scan of one datastore; prefer list_cached_images for a cached answer' and notes that ds_name comes from list_all_datastores, giving clear when-to-use and alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds valuable behavioral context: the exact return shape ({host, enabled, hba_device, iqn, send_targets}), the behavior when the adapter is disabled (enabled=false with null device/IQN and empty target list), and the error condition for host_name ('Errors if not found'). This goes beyond the annotations and gives the agent a clear model of the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense but not bloated. Every sentence earns its place: a one-line purpose, a terse return-format overview, a usage directive, and clear parameter explanations. The most critical information (purpose and usage context) is front-loaded, and the parameter section is organized for quick scanning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description provides the complete return structure inline. It also covers edge cases (disabled adapter), error behavior (host not found), prerequisites (list of hosts from another tool), and post-conditions (verification after mutations). For a read-only status tool with two params, nothing important is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must carry the full burden for parameter meaning. It fully explains host_name: 'ESXi host name exactly as shown in vCenter inventory (FQDN or IP). Errors if not found. No host listing here — get names from vmware-monitor list_esxi_hosts.' And target: 'Optional vCenter/ESXi target name from config.' This adds format, source, error behavior, and optionality, which is far beyond the schema's bare string type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with '[READ] Get the software iSCSI adapter state and configured send targets for an ESXi host,' which uses a specific verb (Get) and resource (software iSCSI adapter state and send targets) and clearly scopes to an ESXi host. It distinguishes from siblings by explicitly naming related tools (storage_iscsi_enable, storage_iscsi_add_target, storage_iscsi_remove_target) as actions that follow this status check.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance: 'Use this before storage_iscsi_enable / storage_iscsi_add_target / storage_iscsi_remove_target to check prerequisites, and afterwards to verify the change took effect.' It also names an alternative for host listing ('get names from vmware-monitor list_esxi_hosts') and clarifies that this tool does not list hosts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses behaviors beyond the annotations: it reads via the vSAN Management SDK, returns null with a message instead of a fabricated false when config is absent, and only errors if the cluster name is not found. It also declares 'No side effects,' reinforcing the readOnlyHint and idempotentHint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is detailed yet each sentence adds value: it covers return format, SDK details, edge-case behavior, error handling, alternatives, and limitations. The structure is logical with a summary paragraph, notes, and args, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description fully explains the return dict fields and the null behavior. It also covers error conditions and explicitly differentiates from sibling tools, making it complete for an AI agent to decide on and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates well: it explains cluster_name is 'exactly as shown in vCenter (case-sensitive)' and errors if not found, even directing how to get cluster names. The target parameter is described only as 'Optional vCenter/ESXi target name from config,' which is somewhat thin but acceptable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get vSAN data-efficiency (deduplication + compression) status for a cluster.' It uses a specific verb ('Get') and identifies the resource ('vSAN data-efficiency status'), and it distinguishes itself from siblings by referencing 'Use vsan_capacity for space usage and vsan_health for disk-group layout.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is provided: 'Use vsan_capacity for space usage and vsan_health for disk-group layout' directly points to alternatives. It also states exclusions, such as 'vSAN Global Deduplication and vSAN-to-vSAN replication are NOT exposed here' and advises using the UI for those.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only and idempotent hints, and the description adds valuable behavioral details: the return envelope structure and that 'All matches are returned, so truncated is always false'. This goes beyond the annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: a clear summary, usage guidance, return behavior, and parameter list. Every sentence contributes meaning, and the most important information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
It covers purpose, usage context, parameter semantics, return format, and sibling relationships. With no output schema, the description's explanation of the response envelope and truncation behavior makes the tool self-contained for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions (0% coverage), but the description's Args section fully explains each parameter—ds_name, path, pattern, target—including defaults and examples. This perfectly compensates for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Browse files in a datastore directory' and distinguishes itself from the sibling scan_datastore_images by explicitly saying to prefer that tool for deployable images. This makes the specific purpose and resource unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives explicit guidance: use for arbitrary files or a glob, prefer scan_datastore_images for deployable images, and mentions that ds_name comes from list_all_datastores. This provides clear context on when to use this tool and when not.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, idempotentHint, etc.), the description reveals important behavioral traits: it reads a specific local file (~/.vmware-storage/image_registry.json), results may be stale, filtering is performed entirely in memory, and 'truncated is always false' due to that behavior. This adds significant context beyond the structured annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with a one-line summary, followed by a clearly separated details section and an 'Args:' block. Every sentence adds value: the staleness caveat, the live-listing alternative, the return envelope explanation, and the parameter semantics. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only list tool with optional filters and no output schema, the description is complete. It details the return envelope structure ('items', 'returned'/'total'/'truncated'), explains edge cases (empty results, staleness), and covers both parameters. The presence of sibling tools is addressed with the explicit alternative, making the context fully understood.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden. It explains both parameters: image_type as a case-insensitive file extension filter with examples ('ova', 'iso', 'ovf', 'vmdk'), and datastore as an exact name filter. It also clarifies that omitting either parameter returns all types/datastores, which is not obvious from the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with '[READ] List deployable images (OVA/OVF/ISO/VMDK) from the local cache registry' — a specific verb, resource, and scope. It also distinguishes from the sibling tool scan_datastore_images by stating 'instant, no vCenter connection or datastore I/O' and later recommending the sibling for live listings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool ('instant', cached registry) and provides a direct alternative: 'For a live listing use scan_datastore_images instead.' It also notes that results 'may be stale or empty if no scan has run,' setting accurate expectations for cached data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (destructiveHint=true), the description adds critical context: LUNs become inaccessible, the rescan side effect, error conditions, audit logging, and dry_run behavior. This goes far beyond the structured metadata.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the primary action, followed by a clear warning block, error conditions, reversal, logging, and argument details. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive tool with an output schema, this description is exceptionally complete: it covers preconditions, side effects, error cases, reversibility, logging, and all parameters. An agent can safely exercise this tool based on the description alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the schema has 0% description coverage, the Args section in the description thoroughly explains every parameter, including constraints (e.g., address must be an IP literal, port range 1-65535, dry_run behavior). This fully compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Remove an iSCSI send target from an ESXi host's software iSCSI adapter, then rescan all HBAs and VMFS volumes.' This is a specific verb+resource+scope combination, and it is easily distinguished from siblings like storage_iscsi_add_target and storage_iscsi_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit preconditions are provided: 'first verify the target exists (storage_iscsi_status) and that no datastores depend on it (list_all_datastores).' It also names the alternative for reversal (storage_iscsi_add_target) and warns when the tool errors, giving clear when-to-use and when-not-to-use context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (destructiveHint=false), the description adds rich behavioral context: 'Non-destructive: only triggers device and VMFS discovery (deletes nothing), but it is I/O-visible on the host and may take a minute or two with many paths. Audit-logged to ~/.vmware/audit.db. Returns a confirmation string; errors include remediation hints.' This discloses side effects, performance impact, auditing, and error handling, which annotations alone do not provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with purpose and organized into purposeful paragraphs: use case, safety/behavior, return value, and parameter details. Every sentence contributes value without redundancy or fluff; the length is justified by the complexity of the operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers all key aspects: purpose, when to use, side effects, duration, audit logging, return type, error hints, and complete parameter semantics. Despite not showing the output schema, the description mentions the return format ('confirmation string'), making the tool fully understandable for an agent to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates fully with an Args section explaining all three parameters: host_name (required, errors if not found), dry_run (preview behavior), and target (optional name from config). This adds meaningful semantics beyond the bare type/default information in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with '[WRITE] Rescan all HBAs and VMFS volumes on an ESXi host to discover newly presented LUNs and datastores,' which is a specific verb+resource+scope statement. It clearly distinguishes from sibling tools like storage_iscsi_add_target by focusing on rescanning storage hardware rather than managing iSCSI targets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit usage guidance is provided: 'Use this when a storage array presents new LUNs, or after out-of-band SAN changes.' It also names alternatives and exclusions: 'Not needed after storage_iscsi_add_target / storage_iscsi_remove_target — those rescan automatically.' This fully addresses when and when-not to use the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint=true annotation already signals a safe read operation. The description adds behavioral specifics: returns vsan_enabled=false with an explanatory message when vSAN is not enabled instead of erroring, and errors only if the cluster name is not found. This goes beyond the annotation by clarifying error semantics and edge-case behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Each sentence earns its place: summary, return format, edge-case behavior, sibling references, safety note, and parameter specifics. No redundancy or filler. The structured Args section is not verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description compensates by enumerating the exact return fields: cluster_name, vsan_enabled, datastore_name, total_gb, used_gb, free_gb, usage_pct. It also covers error conditions, non-vSAN fallback behavior, and alternative tools. This is a complete picture for a read-only capacity query.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description carries the burden. It explains that cluster_name must be 'exactly as shown in vCenter' and errors if not found, and target is an 'Optional vCenter/ESXi target name from config.' This provides semantic guidance the schema omits.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with '[READ] Get space usage of a cluster's vSAN datastore for capacity planning.' It clearly identifies the specific operation (get space usage), the resource (vSAN datastore), and the scope (cluster). It further distinguishes itself from siblings by pointing to vsan_health for disk-group layout and list_all_datastores for non-vSAN datastores.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs when to use this tool: for vSAN datastore capacity planning. It directly names alternatives: 'Use vsan_health for disk-group layout and host details; use list_all_datastores for non-vSAN (VMFS/NFS) datastore usage.' Also notes 'No side effects,' giving context on safe usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it readOnly/idempotent, and the description adds behavioral specifics: 'If vSAN is not enabled, returns vsan_enabled=false with a message rather than an error,' 'overall_health is reported as "unknown",' and 'No side effects.' This enriches beyond the structured hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured with a READ tag, a one-sentence purpose, a return-format block, notes, and arg explanations. Every line adds value, and the formatting makes it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers return payload, error behavior, health limitations, and an alternative tool. Given the tool's read-only nature and no output schema, it provides sufficient contextual information for an agent to select and invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no property descriptions (0% coverage), but the description details both args: cluster_name must be exact as shown in vCenter and errors if not found; target is an optional vCenter/ESXi target from config. This fully compensates for the schema's lack of semantic information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with '[READ]' and explicitly states 'Get vSAN enablement status, host count, and per-host disk-group layout for a cluster,' naming a specific verb and resource. It also distinguishes itself from sibling tool vsan_capacity by noting 'Use vsan_capacity for space usage instead.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly names vsan_capacity as the alternative for space usage, and clarifies that detailed health checks require vCenter UI. This gives clear context on when the tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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