Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond annotations (which are neutral), the description discloses that this is a write operation ([WRITE]), that the alarm remains active with acknowledged=true, and that the action is audited. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with a one-line summary, then behavioral details, prerequisites, alternative, audit note, and an Args section. No unnecessary words or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the three parameters, no output schema, and low schema coverage, the description fully covers return format (dict with expected fields), prerequisites, error handling, and alternative tool, making it complete for agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema coverage, the description adds full semantic meaning for each parameter: entity_name is a VM/host/cluster name from list_vcenter_alarms, alarm_name is exact definition name with example, target is a vCenter target from config with default behavior.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'acknowledge' and resource 'vCenter alarm' with the critical nuance that it marks as seen without clearing, distinguishing it from the sibling reset_vcenter_alarm.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit context: requires prior use of list_vcenter_alarms, error condition for unknown pairs, and directs to reset_vcenter_alarm for full removal. Could briefly state when not to use (e.g., if clearing is needed), but the alternative is well noted.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses write operation, replacement behavior, works on/off state, audit log location, and error conditions beyond annotations, which only indicate not read-only and open world.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with clear sections: operation, behavior details, prerequisite, audit info, parameter descriptions. Efficiently uses space without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given annotations and output schema exist, the description covers enough context: behavior, error cases, and parameter details. Complements structured fields well.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Adds detailed meaning for each parameter: vm_name as exact vCenter name, iso_ds_path with bracket format example, target as optional from config. Schema had no descriptions, so this is highly valuable.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool mounts a datastore ISO into a VM's virtual CD-ROM drive, and distinguishes from sibling tools like browse_datastore which is for finding ISOs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides guidance to find ISOs first with browse_datastore, explains behavior with existing CD-ROMs and IDE controller requirement, and notes target can be omitted. Does not explicitly list when not to use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Describes the clone process steps (full copy, reconfigure, snapshot, power on) beyond annotations. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Concise: one-line purpose, process summary, then structured Args list. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers tool purpose, process, and parameters well. Could mention prerequisites (e.g., source VM exists) but output schema exists for return values, so adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Args section explains all 7 parameters in detail, fully compensating for 0% schema description coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly specifies it batch clones VMs from a source gold image, distinguishing from single clone (vm_clone) and linked clone (batch_linked_clone_vms) siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies full clone use case but does not explicitly contrast with batch_linked_clone_vms or vm_clone. No when-not-to-use or alternative guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations show readOnlyHint=false and destructiveHint=false. Description adds '[WRITE]' indicating mutation, sequential deployment, failure handling ('one VM's failure is recorded and the rest continue'), and auditing. Good additional context beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured: summary line, usage guidance, behavioral details, then args and returns. No redundant sentences; every line adds value. Front-loaded with purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers all aspects: YAML spec structure, defaults and overrides, sequential behavior, error handling, auditing, parameter descriptions, and return format. Given complexity, description is complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description compensates fully: explains spec_path as 'Local filesystem path to the deploy.yaml specification file' and target as 'vCenter/ESXi target name from config.yaml; omit to use the default target.' Clear and sufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool deploys multiple VMs from a YAML spec, using specific verb 'Deploy' and resource 'multiple VMs'. It distinguishes from sibling tools by listing alternatives for single VM deployments.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states 'Use for fleet provisioning' and lists when to prefer other tools like deploy_vm_from_template, vm_clone, etc. Provides clear context for when to use this tool versus alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description explicitly states '[WRITE]' indicating mutation, and explains the copy-on-write sharing behavior. Annotations (readOnlyHint=false, destructiveHint=false) are consistent with the write operation. No contradictions. The description adds valuable context about the disk sharing mechanism beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two paragraphs: a summary line, a behavioral note, and a parameter list. It is mostly concise but repeats parameter names unnecessarily in the bullet list. Front-loading is good with the summary. Could be slightly tighter but overall efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers purpose, parameters, and key behavioral info (copy-on-write). It does not mention prerequisites (e.g., source VM and snapshot existence) or error conditions. Given the tool has an output schema (so return values are documented elsewhere) and annotation depth, it is largely adequate for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description provides a bullet list explaining each of the 8 parameters, including optional overrides and defaults. This adds substantial meaning beyond the schema's name and type alone, fully compensating for the lack of schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with '[WRITE] Batch create linked clones from a VM snapshot (fastest batch provisioning),' which clearly states the action (batch create), resource (linked clones from VM snapshot), and key differentiator (fastest). This distinguishes it from sibling tools like batch_clone_vms (likely full clones) and deploy_linked_clone (single clone).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for fast batch provisioning by mentioning 'fastest batch provisioning' and specifying linked clones via copy-on-write. However, it does not explicitly state when to use this tool over alternatives or provide when-not-to-use guidance. It lacks explicit exclusions or comparisons with siblings like batch_clone_vms.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, fully covering the tool's safe, non-destructive nature. The description adds the '[READ]' prefix which reinforces this but does not introduce new behavioral traits. While the description provides operational context (discovering files), it does not disclose additional behaviors like rate limits or authentication requirements, which are not needed given 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: a single-line header and a short paragraph with a bulleted argument list. Every sentence adds value, and there is no redundant or extraneous text. The structure front-loads the purpose and immediately provides actionable details, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (4 params, output schema present), the description covers all essential aspects: purpose, usage context, and parameter details. The existence of an output schema means the description doesn't need to explain return values. The description is complete for its scope, though it could optionally mention that it lists file metadata (implied by 'browse'). There are no significant gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has no descriptions for any of the 4 parameters (0% coverage). The description compensates with a clear docstring explaining each parameter: datastore_name (required), path (default root), pattern (with glob examples), and target (optional). The examples for pattern are particularly helpful. While the explanations are functional and minimal, they add necessary meaning that the schema lacks, meriting a score of 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action: 'Browse files in a vSphere datastore directory.' It specifies the resource (datastore directory) and the operation (browse, implied read). It also gives context by mentioning file types (OVA, ISO, VMDK) and a typical use case (before deploying VMs). This provides a specific and unambiguous purpose, differentiating it from sibling tools like '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.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use this to discover...files on datastores before deploying VMs,' which gives a clear context for when to use the tool. However, it does not provide exclusions or compare it directly to sibling tools like 'scan_datastore_images' or 'vm_deploy_from_ova', leaving some ambiguity about when to choose this over alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Description claims idempotent behavior, but annotations set idempotentHint to false. This is a direct contradiction. Other behavioral details are fine but the contradiction outweighs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is well-structured with sections, but slightly verbose. However, every sentence adds value. Could be tightened without losing clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers purpose, prerequisites, idempotency, comparison to siblings, parameters, and return values. Output schema exists but description still adds helpful return examples. Complete for a write tool with these constraints.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has 0% description coverage, but description fully explains each parameter: cluster_name (destination, created with cluster_create), host_name (FQDN example), target (from config.yaml, optional). Adds crucial context beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the verb 'Move' and resource 'ESXi host into a cluster', and distinguishes from registering new hosts and from cluster_remove_host. It clearly differentiates itself among siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when to use (move managed host into cluster), when not to use (first-time registration), alternatives (cluster_remove_host, cluster_info), and prerequisite (host already in vCenter inventory).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate write (readOnlyHint=false). Description adds detail about modifiable settings (HA, DRS, drs_behavior) and target parameter. No mention of side effects or permissions, but adequate given annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with header and list. Every sentence adds value, but could be slightly more compact. Still very clear.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers inputs comprehensively. Output schema exists, so return not needed. Lacks mention of preconditions or limitations, but overall sufficient for a reconfig tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% coverage, so description fully explains all 5 parameters, including allowed values for drs_behavior and acceptable inputs for ha and drs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states 'Reconfigure cluster HA/DRS settings' with specific verb and resource. Differentiates from siblings like cluster_create, cluster_delete, etc.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Purpose is obvious from description, but no explicit when-to-use or exclusionary guidance relative to siblings. Still, the context is clear enough for an agent to infer usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds behavioral context beyond annotations: it notes the tool fails on duplicate names or invalid drs_behavior, ensures no partial state, and mentions audit logging. It does not contradict annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a front-loaded purpose, followed by error details, next steps, and parameter documentation. It is slightly lengthy but every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (6 parameters, write operation), the description is complete: it covers creation, error handling, subsequent actions, audit, parameter meanings, and return value. No gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, but the description's Args section fully documents each parameter, including defaults, constraints (e.g., drs_behavior only effective when drs=True), and optional behavior (datacenter defaults to first). This adds significant meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates a new empty cluster with optional HA/DRS. It uses a specific verb+resource and distinguishes from sibling tools like cluster_configure and cluster_delete.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use the tool (creation), mentions failure conditions, and references sibling tools (cluster_add_host, cluster_configure) for subsequent steps. It does not explicitly state when not to use it, but provides enough context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description goes beyond annotations by specifying the [WRITE] operation and the condition for deletion. Annotations indicate destructiveHint=true, and the description reinforces that. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with a clear first line summarizing the purpose and condition, followed by a brief parameter list. Every sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a delete tool with an output schema (not shown), the description covers the precondition, basic operation, and parameters. It does not explain return values, but that is acceptable given the output schema's presence.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description explains both parameters ('name' as the cluster to delete, 'target' as optional vCenter target) despite the schema having 0% description coverage. This adds meaningful semantics beyond the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Delete' and the resource 'cluster', with a specific condition 'empty cluster (no hosts must remain)'. It distinguishes itself from sibling tools like cluster_create and cluster_add_host by specifying deletion and the prerequisite.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states the precondition 'no hosts must remain', which guides when to use the tool. However, it does not mention alternatives or explicitly state when not to use it, but the context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already label it as read-only and idempotent. The description reinforces that (no side effects) and adds details about what the return contains and error handling. No contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a header, usage hints, and parameter/return details. It is slightly verbose but front-loaded with the essential purpose. Not wasteful, but could be tightened.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

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 specifies return format (Dict with name, host_count, hosts, ha_enabled, etc.) and error handling. Combined with annotations, it provides complete context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema coverage, the description explains each parameter: 'Exact cluster name' for 'name' and 'vCenter target name from config.yaml; omit to use the default target' for 'target', adding critical usage context not present in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description begins with 'GET detailed cluster information' and lists specific components (member hosts, HA/DRS config, resource capacity), clearly stating its purpose. It distinguishes itself from sibling tools like cluster_add_host and cluster_configure by explicitly mentioning usage context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states 'Read-only, no side effects' and advises use before cluster_add_host/cluster_remove_host and to verify cluster_configure changes. This provides 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.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description aligns with annotations (readOnlyHint=false, destructiveHint=true) by prefixing with '[WRITE]' and detailing removal. It adds context about the maintenance mode requirement, which annotations do not cover. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise (two sentences plus parameter list) and front-loaded with the action and condition. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the key prerequisite and parameter semantics. With an output schema present, return values are not needed. However, it does not mention error conditions if the host is not in maintenance mode, which would be helpful for complete context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Given 0% schema description coverage, the description provides basic explanations for each parameter (e.g., 'Cluster to remove the host from'). However, it lacks detail on formatting or constraints, and the description for target is minimal.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Remove a host from a cluster') and the necessary condition ('host must be in maintenance mode'). It effectively distinguishes this from sibling tools like cluster_add_host.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a clear prerequisite (maintenance mode) but does not explicitly mention when not to use this tool or suggest alternatives. It implicitly differentiates from sibling tools focused on adding hosts.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate write, non-destructive, non-idempotent. The description adds that the converted VM cannot be powered on, providing context beyond annotations. It does not mention potential irreversibility or return format, but output schema exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, starting with '[WRITE]' prefix, then a clear action sentence, a note on post-conversion behavior, and parameter details. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple conversion tool, the description covers action, prerequisite, and outcome. It mentions the relationship with deploy_vm_from_template. Missing are permissions or error conditions, but output schema handles return info.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description adds meaning for both parameters: 'vm_name' must be powered off, and 'target' is optional and from config. This compensates for the lack of schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool converts a powered-off VM to a vSphere template, using specific verb and resource. It distinguishes from the sibling deploy_vm_from_template by noting the template serves as a clone source, establishing differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description specifies the prerequisite (VM must be powered off) and the outcome (cannot be powered on). It implies use when a template is needed for cloning, but does not explicitly exclude alternatives like vm_clone or deploy_vm_from_ova.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses write nature ([WRITE]), near-instant characteristics, dependency on source VM, and audit trail. Annotations confirm readOnlyHint=false, no contradictions. Could mention consequences if source VM is deleted, but overall good.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with summary, detailed explanation, Args list, and Returns. Efficient but slightly long; however, every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers cloning process, dependencies, alternatives, parameter details, and return values. Output schema exists but description also explains return. No gaps for an 8-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% description coverage, but the 'Args' section explains each parameter's purpose, constraints, and defaults, adding significant meaning beyond the schema titles. For example, 'target: vCenter/ESXi target name from config.yaml'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states 'Create a linked clone from a VM snapshot' and contrasts with siblings: 'use vm_clone or deploy_vm_from_template for fully independent copies'. The verb and resource are specific.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use ('fastest provisioning method for test/dev fleets') and when not ('for fully independent copies'). Provides prerequisite: 'Requires the source VM to have the named snapshot — run vm_list_snapshots first'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses upload time scaling with OVA size, failure behavior before resource creation, and audit logging. Annotations already indicate non-read-only; description adds valuable context beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is thorough but not overly verbose; the 'Args' section is well-structured. A minor reduction in explanation length could improve conciseness, but every sentence serves a purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers purpose, usage, behavior, all parameters, return value, and references to config.yaml. Even with an output schema, the description provides complete context for the tool's operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so description fully compensates by explaining all 8 parameters with constraints (e.g., local path must be readable, vm_name must not exist, defaults for optional params).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it creates a VM by importing a local .ova file, using 'Create' as the verb and specifying the resource type. It distinguishes itself from siblings like deploy_vm_from_template and vm_clone.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly specifies when to use this tool (for local .ova files) and when not (for vSphere templates, cloning existing VMs), naming alternative tools directly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate write operation (readOnlyHint=false). The description adds value by listing optional behaviors like power_on and snapshot creation, which go beyond the annotation information. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the main action, followed by a concise list of arguments. Every sentence is informative and necessary, with no wasted words. Well-structured for agent parsing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers all input parameters and the main action. With an output schema present, the return type is handled. Missing are prerequisites or error scenarios, but overall it is sufficiently complete for a tool of this complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully explains all 8 parameters in the Args section, providing clear meaning for each. This adds essential value beyond the input schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Deploy a new VM by cloning from a vSphere template' which is a specific verb-resource combination. It distinguishes this from sibling tools like deploy_linked_clone and deploy_vm_from_ova by specifying the source as a template.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no explicit guidance on when to use this tool versus alternatives such as vm_clone or deploy_linked_clone. It lists parameters but does not mention use cases, prerequisites, or trade-offs.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds useful behavioral details: it returns alarms with severity, entity name/type, alarm name, acknowledged flag, and trigger time. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise: one-line summary, then a clean list of return fields, then args. Every sentence adds value with no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema (not shown but indicated), the description covers the tool's purpose, return fields, parameters, and usage hints. It is adequately complete for a read-only listing tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description fully compensates by explaining each parameter: target is an optional vCenter target name defaulting to config, limit is a max count with a hint to use when many alarms are active. This adds significant meaning beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'List' and the resource 'active/triggered alarms across the vCenter inventory'. It distinguishes from sibling tools like acknowledge_vcenter_alarm and reset_vcenter_alarm by focusing on listing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides usage guidance for the optional parameters (target defaults, limit use case). It does not explicitly state when not to use this tool versus alternatives, but the sibling tools are clearly different actions, making it adequate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate write operation. Description adds valuable behavioral details: gotcha about clearing all matching alarms, response 'scope' field, and that it clears back to normal. Exceeds what annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Concise with front-loaded purpose. Uses [WRITE] marker, gotcha, and Args list. Could be more structured but efficient overall.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, mentions response 'scope' field. Covers pre-requisite actions and clearing behavior. Missing permission requirements but adequate for sibling context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has 0% description coverage, but description includes a dedicated Args section with explanations for all three parameters, adding full meaning beyond schema types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it clears triggered vCenter alarms to normal state. Uses specific verb and resource. Does not explicitly differentiate from sibling 'acknowledge_vcenter_alarm', but the write nature is clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides usage context: use after resolving underlying issue, and use list_vcenter_alarms to find parameters. But does not mention when to use alternatives like acknowledge_vcenter_alarm, missing explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate a safe read operation (readOnlyHint=true, destructiveHint=false). The description adds specific caching behavior (file location ~/.vmware-aiops/image_registry.json) and scope (all accessible datastores). No contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is four concise sentences. The first sentence states the purpose, second and third explain caching and usage, and the last defines the parameter. No extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given one optional parameter, rich annotations, and no output schema, the description covers purpose, caching behavior, and parameter meaning. It could mention what the tool returns, but the caching explanation partially addresses that.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description compensates by clearly explaining the single optional parameter 'target' as a vCenter/ESXi target name from config. This adds meaning beyond the schema's type and nullability.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states '[READ]' and specifies scanning all accessible datastores for deployable images (OVA/ISO/OVF/VMDK). This clearly distinguishes it from siblings like browse_datastore, which browses files generally.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says results are cached for fast lookup via list_cached_images and to run this to refresh the cache. This provides clear usage context, though it does not explicitly state when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses sequential execution, failure behavior (stops immediately, keeps plan file, returns rollback_available flag), and success behavior (deletes plan file). No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear title line and bulleted Args section. However, it is slightly verbose; minor trimming could improve conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Lacks explicit output schema, but describes return of rollback_available flag. Could mention more about return value structure or open world behavior, but adequate for a plan execution tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully explains both parameters: plan_id is the ID from vm_create_plan, and target is an optional vCenter/ESXi target. This adds critical context beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states 'Execute a previously created plan step by step.' The verb 'execute' and resource 'plan' are specific, and it distinguishes itself from sibling tools like vm_create_plan and vm_rollback_plan by describing the execution step and post-failure behavior.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use (after vm_create_plan), what happens on failure (stops, returns rollback_available flag), and directs to ask user and call vm_rollback_plan if needed. Provides clear context and alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds context beyond annotations by explaining that cancelling a TTL prevents auto-deletion. Annotations already indicate it is destructive and not read-only, so the description aligns and adds value.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise: two lines with a clear purpose statement and a parameter explanation. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has a single parameter, and the description covers its role. An output schema exists but is not described, which is acceptable as the description focuses on input. The context is sufficient for an agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter, vm_name, is described as 'Name of the VM whose TTL should be cancelled.' The input schema provides no description for this parameter, so the description fully compensates and explains its role.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Cancel' and the resource 'TTL for a VM', and includes a parenthetical explaining the effect. It distinguishes from sibling tools like vm_set_ttl and vm_list_ttl.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description indicates when to use the tool (to cancel a TTL) but does not explicitly state when not to use it or mention alternatives. However, the context is clear for the intended use case.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds behavioral details beyond annotations: 'Powers off the VM first if it is running, then reverts to the named snapshot.' This supplements the destructiveHint=true annotation. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise: a titleline, two explanatory sentences, and an Args block. Each sentence adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers purpose, behavior, and parameters adequately for a VM reset tool. It could explicitly mention that the snapshot must exist or error conditions, but it is sufficient given the output schema is present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema description coverage, the description includes an Args block explaining all three parameters: vm_name (required), snapshot_name (default 'baseline'), and target (optional vCenter/ESXi target). This adds meaning beyond the input schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Revert a VM to its baseline snapshot (Clean Slate)' using a specific verb and resource, distinguishing it from the sibling general revert tool vm_revert_snapshot by specifying the baseline snapshot and including the power-off behavior.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says 'Use this to reset a lab/dev VM to a clean starting state after a task completes,' providing clear context for when to use it. However, it does not explicitly state when not to use it or compare with alternatives like vm_revert_snapshot.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate non-readOnly (write), non-destructive, non-idempotent. The description adds value by specifying the default placement behavior, the power_on option, and the target parameter for connection. It does not contradict annotations and provides useful context beyond structured fields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise: a brief summary line followed by a structured parameter list. Every sentence provides necessary information without redundancy. It is front-loaded with the core action and efficiently uses markdown-like formatting.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 6 parameters (2 required) and an output schema, the description covers all parameters, defaults, and basic behavior. It could mention potential side effects (e.g., cloning time) but is sufficiently complete given the annotations and output schema presence.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully compensates by listing each parameter with clear explanations (e.g., 'vm_name: Source VM (or template) name'). This adds significant meaning beyond the raw schema types and defaults.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Clone a VM' with a [WRITE] prefix, specifying the core action. It distinguishes itself from sibling tools like batch_clone_vms and deploy_linked_clone by detailing the full clone behavior and optional placement parameters, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to omit to_host/to_datastore ('lands on source's host+datastore'), providing some guidance. However, it does not explicitly contrast with alternatives like batch_clone_vms or deploy_linked_clone, leaving the agent to infer when to use this tool over them.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses key behaviors: creates a powered-off VM, fails before creation if datastore not found, and audit logging. Annotations provide readOnlyHint=false and destructiveHint=false, which align. The description adds context about failure and auditing but could mention other side effects like resource consumption.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a leading summary, detailed behavior, Args section, and Returns. Every sentence adds value, no redundancy. It is concise yet comprehensive.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool complexity (8 params, many sibling tools, output schema present), the description covers all necessary aspects: purpose, usage, parameters, behavior, and error conditions. It is complete without reliance on output schema details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description provides detailed explanations for all 8 parameters, including defaults, constraints (vm_name must not exist), and advice on omitting optional parameters. With schema coverage at 0%, this is essential and adds significant meaning beyond the input schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates an empty VM with specific hardware sizing, and distinguishes it from related tools like deploy_vm_from_ova and vm_clone. The verb 'Create' and the resource 'empty VM' are specific, and it differentiates from sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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: to create a blank VM for manual setup, and when to use alternatives (attach_iso_to_vm, deploy_vm_from_ova, deploy_vm_from_template, vm_clone) for ready-to-run guests. This provides clear guidance on tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Adds [WRITE] marker, describes validation, target existence check, rollback info generation. No annotation contradictions. Provides rich behavior beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with front-loaded info, but slightly verbose. Each sentence adds value, but could be more concise without losing meaning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Even without output schema, describes return value (plan dict with plan_id, steps, summary). Covers all necessary context for a complex multi-step tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Fully compensates for 0% schema coverage by explaining operations as list of dicts with 'action' key, listing allowed actions, giving example, and describing target as optional vCenter/ESXi target.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates an execution plan for multi-step VM operations, lists allowed actions, and provides an example. It distinguishes from siblings like vm_apply_plan and vm_rollback_plan.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states auto-trigger when 2+ steps or 2+ VMs, and mentions showing plan to user before calling vm_apply_plan. Lacks explicit when-not-to-use, but context implies it's for planning multi-step operations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond annotations, the description discloses that memory snapshots are heavier and allow resume, quiesce requires VMware Tools, and target specifies the vCenter/ESXi target. However, it does not mention prerequisites like VM power state for memory snapshots.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise, front-loading the purpose with a single sentence and then listing parameters with brief explanations. Every sentence is informative with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (6 parameters, related sibling tools, output schema exists), the description covers the main aspects. It explains parameter effects but could mention that a memory snapshot requires the VM to be powered on. Overall, very good.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description must explain parameters. It provides useful explanations for memory, quiesce, and target, and clarifies vm_name and snapshot_name. While minimal, it adds meaning beyond the schema titles.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Create a snapshot of a VM', providing a specific verb and resource. It distinguishes from sibling tools like vm_delete_snapshot and vm_list_snapshots by focusing on creation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for creating snapshots but lacks explicit guidance on when to use this tool versus alternatives like vm_revert_snapshot or vm_delete_snapshot. No 'when not to' or alternative suggestions are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate destructiveHint=true and readOnlyHint=false. The description adds 'irreversible' and the power-off precondition, which are valuable behavioral traits 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with two sentences and a brief args list. It front-loads the purpose and is free of fluff, making it efficient for an AI agent to process.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity, the description covers the main purpose, preconditions, and parameters. It assumes the output schema handles return values, but omits potential error scenarios. Overall adequate for this context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description compensates by briefly explaining both parameters: 'vm_name: VM to delete. Must be powered off.' and 'target: vCenter/ESXi target name from config.' This adds meaning beyond the schema structure, though more detail on valid values could help.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it deletes a VM irreversibly, with a specific verb and resource. It distinguishes from sibling tools like vm_power_off or vm_clone by explicitly mentioning 'Delete' and 'irreversible'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a precondition (VM must be powered off) but does not explicitly compare to alternatives or state when not to use. While it implies usage for permanent deletion, lack of direct comparison to siblings like vm_power_off or vm_create_snapshot limits guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Disclosure includes that it frees disk space, does not change VM state, consolidation can be slow, operation is irreversible, audited to audit.db, and async behavior with task IDs. This adds significant context beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections, but slightly lengthy. However, each sentence adds value, so it is only marginally penalized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers preconditions (run vm_list_snapshots), side effects (slow consolidation), error handling (returns not-found message), async behavior, and audit logging. Complete given the tool's complexity and available annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully explains all 5 parameters: vm_name, snapshot_name, remove_children (default and effect), wait (default and blocking behavior), and target (usage). Adds meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (Permanently delete a named snapshot) and the resource (snapshot). It distinguishes from the sibling vm_revert_snapshot by noting it does not change VM state, and references vm_list_snapshots for exact names.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly explains when to use (to free disk space), contrasts with vm_revert_snapshot, advises running vm_list_snapshots first, warns about irreversibility and user confirmation, and explains async vs sync with wait parameter.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds the requirement of VMware Tools, which is useful behavioral context beyond annotations. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured: two lines for purpose/prerequisite, followed by a bullet-style Args list. Every sentence adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the 6 parameters and the presence of an output schema, the description covers prerequisites, parameter semantics, and read-only nature. It is complete for the tool's purpose.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description lists each parameter with concise explanations, e.g., 'vm_name: Target VM name.' This adds meaning beyond the schema's titles and types, fully compensating for the lack of schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description starts with '[READ] Download a file from a VM to local machine via VMware Tools', providing a clear verb and resource. It distinguishes from siblings such as vm_guest_upload (uploads) and aligns with readOnlyHint annotation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It states the prerequisite 'Requires VMware Tools running in the guest OS', which guides when the tool can be used. While it doesn't explicitly contrast with siblings, the context of file download is clear from the name and description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations provide readOnlyHint=false and destructiveHint=false. The description adds that it requires VMware Tools and that output is not captured directly, but does not disclose potential risks of arbitrary command execution or timeout behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the purpose, includes a prerequisite, return fields, and a practical note with example. It is concise but the note could be slightly condensed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description lists return fields (exit_code, stdout, stderr, timed_out) and explains the output limitation. However, it omits details on command timeout duration and possible output truncation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description includes an Args section with brief descriptions for all 7 parameters, adding meaning beyond the plain schema (e.g., 'Full path to program' for command). Defaults are mentioned for username.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description starts with '[WRITE]' and clearly states 'Execute a command inside a VM via VMware Tools,' providing a specific verb and resource. It distinguishes from siblings like vm_guest_download by explaining that output is not directly captured.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description notes the prerequisite (VMware Tools running), provides an example of capturing output via vm_guest_download, but does not explicitly mention when not to use this tool or alternatives like vm_guest_exec_output.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses that the tool redirects output to a temp file, downloads it, and cleans up, which adds behavioral context beyond annotations. Annotations already indicate it's a write operation (readOnlyHint=false) and open-world (openWorldHint=true). The description does not contradict annotations and provides additional detail about the implementation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a one-line summary, bulleted process explanation, and a clear Args list. Every sentence provides value, and there is no verbose or redundant content. 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.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no output schema, but the description lists return fields (exit_code, stdout, stderr, timed_out, os_family). It explains the execution flow and OS detection. For a 6-parameter tool with no output schema, the description is nearly complete, though it could mention that the command may have side effects on the VM.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It includes an Args section that explains each parameter: vm_name, command, username (default 'root'), password, timeout (default 300), target (optional). This adds significant meaning beyond the schema's bare titles and defaults, fully covering all six parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Execute a shell command inside a VM and capture stdout + stderr.' It uses a specific verb (Execute) and resource (VM guest), and the [WRITE] tag distinguishes it from read-only siblings like vm_guest_download. The purpose is unambiguous and differentiated from vm_guest_exec by emphasizing output capture.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains the automatic OS detection and output capture mechanism, which helps the agent decide when to use this tool. However, it does not explicitly state when not to use it or mention alternatives like vm_guest_exec for fire-and-forget commands. The guidance is clear but lacks exclutions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses steps execute in order, stop on first failure, per-step timeout, and return dict structure. Annotations already indicate write (readOnlyHint=false) and non-destructive (destructiveHint=false); description adds behavioral details beyond annotations. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Concise at ~15 lines with clear sections: purpose, step types, arguments, return, example. No redundant sentences; every part adds value. Front-loaded with key info.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 6 parameters, complex steps array, and no output schema, the description provides return format, step examples, and default timeout. Minor gap: prerequisites (e.g., VM must exist) not stated, but otherwise complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description explains each parameter (vm_name, username, password, steps, timeout, target) and provides detailed step type examples. Adds meaning beyond bare schema, though could elaborate on target selection.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states 'Provision a VM by running a sequence of guest operations' with a clear verb (provision) and resource (VM), and distinguishes from sibling tools like vm_guest_exec (single exec) and vm_guest_upload (single upload) by combining multiple step types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use for multi-step provisioning ('Combines key injection, software installation, and service startup into a single call') but does not explicitly state when not to use or name alternatives like vm_guest_exec for single commands. Guidelines are implied but not explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate this is a write operation (readOnlyHint false) and not destructive. The description adds the prerequisite of VMware Tools and parameter explanations, but does not disclose side effects like file overwriting or permission requirements beyond the guest OS username/password.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise yet comprehensive, structured with a header, prerequisite note, and parameter list. Every sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the core functionality, prerequisites, and all parameters. An output schema exists, so return value detail is optional. Minor gap: could mention expected output (e.g., success status), but overall it is sufficiently complete for a file upload tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully compensates by explaining each parameter's purpose in the 'Args:' section, adding significant meaning beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool uploads a file from local machine to a VM via VMware Tools, using specific verb and resource. It distinguishes from siblings like vm_guest_download and vm_guest_exec which handle downloads and commands.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions the prerequisite of VMware Tools running in the guest OS, providing clear context. However, it does not explicitly state when to use this tool vs alternatives or when not to use it, leaving usage guidance implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint), the description adds that stale plans older than 24 hours are auto-cleaned, which is valuable behavioral context not captured by annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with two sentences, front-loads the [READ] tag, and every word adds value. No superfluous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple list tool with no parameters and an output schema, the description fully covers functionality, return format, and an important behavioral note (auto-clean). Complete for the context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are no parameters, so the description adds no parameter details. However, schema coverage is 100% and the description explains what the list returns, compensating for the lack of parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it lists pending/failed plans with a [READ] tag, and summarizes returned fields like plan_id, created_at, status, steps count, and VMs affected. This distinguishes it from sibling tools like vm_create_plan or vm_apply_plan.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.