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

The readOnlyHint annotation already signals a safe read operation. The description adds useful behavioral context by stating that results include entity properties, tags, management zones, and relationship counts, and it emphasizes the single-type constraint. No contradiction with annotations 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 only two sentences, front-loads the core purpose, and immediately surfaces the critical entitySelector constraint. The result-content sentence adds valuable context without unnecessary 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?

For a discovery tool with full schema documentation and a read-only annotation, the description covers the main behavior, the core constraint, and the shape of results. It does not describe pagination or return structure explicitly, but the schema's limit parameter and the listed result fields provide sufficient 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?

The input schema covers all parameters and already documents entitySelector, mzSelector, time range, sort, limit, and environment_alias. The description mostly restates the entitySelector single-type rule already present in the schema, adding little new semantic meaning for 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 states a clear action ('Discover entities') with a specific resource ('Managed cluster') and method (EntitySelector syntax). It is distinguishable from sibling tools like get_entity_details because it implies a broader discovery/list operation, though it does not explicitly name any sibling.

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 gives a clear usage context: use it to discover entities via EntitySelector, and it highlights a critical prerequisite: exactly one entity type. However, it does not state when to prefer it over alternatives such as get_entity_details or get_entity_relationships, nor any 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 readOnlyHint annotation already covers the read-only safety profile, and the description does not contradict it. However, the description only adds the vague phrase 'detailed information' and does not disclose return shape, error behavior, or environment-specific behavior beyond the annotation.

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 a single short sentence with no filler and the core action is front-loaded. It is appropriately concise, though somewhat generic and lacking useful detail.

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 2-parameter read-only getter, the basic usage is clear and the schema fully documents parameters. However, with no output schema, 'detailed information' is vague and does not clarify what details are returned or how they differ from related entity tools.

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 100%, with both entityId and environment_alias already explained in the schema. The description itself adds no parameter-level meaning, so the baseline score of 3 applies.

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 uses a specific verb 'Get' and resource 'entity', and signals single-entity scope via 'a specific entity'. However, it does not differentiate from sibling tools like get_entity_type_details or get_entity_relationships, leaving the agent to infer which 'details' tool is intended.

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?

No guidance is provided about when to use this tool versus alternatives such as discover_entities, get_entity_relationships, or get_entity_type_details. There are no exclusions, prerequisites, or explicit condition-based recommendations.

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 readOnlyHint annotation already signals a safe read operation, and the description aligns with this by using 'Get'. It adds some value by clarifying that both incoming ('from') and outgoing ('to') relationships are included, but it does not disclose response structure, pagination, or any other behavioral details.

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 a single sentence that is front-loaded with the primary action and resource, with no redundant words or filler. Every part of the sentence contributes meaningful 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 read-only query with two clearly described parameters, the description is mostly adequate. However, with no output schema, the description does not clarify what shape the relationship data takes or whether results are grouped by direction, leaving some ambiguity for an agent trying to interpret the response.

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 100%, so both parameters are already well-documented. The tool description itself adds no additional meaning beyond the schema's parameter descriptions, so the baseline score of 3 is appropriate.

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 ('Get'), the resource ('relationships'), and the scope ('a specific entity... to and from other entities'). This distinguishes it from sibling tools like get_entity_details or discover_entities by operation and resource type, though it does not explicitly name an alternative.

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 the appropriate use case: when an agent needs relationship data for a specific entity. However, it provides no explicit guidance about when to prefer this tool over related siblings such as get_entity_details or discover_entities, and no exclusions or alternatives are mentioned.

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 readOnlyHint annotation already declares this is a read-only operation, but the description adds no behavioral context beyond restating that details are returned. There is no mention of response shape, environment handling, or error behavior, so the description does not meaningfully extend the annotation.

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 a single, direct sentence with no filler or redundancy. It is appropriately minimal for a simple read-only getter and is easy 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?

For a low-complexity read-only tool with fully documented parameters, the single-sentence description is minimally viable. However, there is no output schema and the description does not clarify what 'details' includes, so the agent has limited ability to anticipate the response content.

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 100%, with both parameters adequately documented in the input schema. The description does not add parameter-level detail, but it does not need to because the schema already carries the full semantic weight.

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 names a specific verb ('Get') and resource ('entity type details'), so the agent can tell this is a retrieval operation. It does not explicitly distinguish itself from siblings like get_entity_details or list_entity_types, but the 'entity type' scoping is clear enough.

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?

No guidance is given about when to call this tool versus alternatives such as list_entity_types or get_entity_details. The tool name implies it is for a specific entity type, but the description provides no explicit context, prerequisites, or 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?

The readOnlyHint annotation already signals this is a safe read operation. The description adds some useful context by mentioning verification of connections and authentication services, but it does not explain any caveats such as potential delays or what 'verification' entails in practice.

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?

A single, focused sentence that front-loads the main purpose and includes the key behavioral detail about verifying connections. No filler or redundant wording.

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 zero-parameter read-only tool, the description is reasonably complete: it tells the agent what information to expect and what verification is included. It could slightly benefit from naming the returned data shape, but this is not critical for invocations with no parameters.

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 tool has no parameters and the schema is trivially fully covered, so there is no parameter semantics burden for the description. A baseline of 4 is appropriate because there is nothing additional the description needs to explain.

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 a specific action ('Get information') and a specific resource ('all connected Dynatrace Managed clusters'), and adds the verification of connections and authentication services. This distinguishes it from sibling tools that focus on problems, metrics, logs, entities, events, SLOs, or security problems.

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 when this tool is useful—when the agent needs an overview of connected Dynatrace Managed clusters or connection/auth status. However, it does not explicitly mention alternatives or state when not to use it, leaving some inference to the agent.

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 annotations declare readOnlyHint=true and the description's 'Get' semantics are consistent with that — no contradiction. However, the description contributes no behavioral context beyond the annotation: no mention of response contents, error behavior, or the fact that ALL_ENVIRONMENTS aggregates results across environments. Since the safety profile is already carried by the annotation, the description adds nothing extra.

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?

A single 10-word sentence with zero filler, front-loaded with the verb. The word 'specific' adds the lookup-vs-list distinction, so every word earns its place. It is appropriately sized for the information it conveys, though brevity comes at the cost of workflow guidance captured elsewhere.

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 two-parameter read tool, the 100%-covered schema and readOnlyHint annotation handle most needs, and the environment_alias parameter description is notably thorough. Gaps remain: there is no output schema, so return values are not described, and no guidance is given on the list-then-get workflow. Adequate but with clear 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?

Schema description coverage is 100%, and both parameters are well documented in the schema: eventId identifies the target and environment_alias explains the get_environments_info cross-reference plus the ALL_ENVIRONMENTS special value. Per the baseline rule for high schema coverage, the description need not repeat parameter details, and it adds none.

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 states a specific verb-resource pair: 'Get detailed information' about 'a specific event,' which clearly differentiates this from list-oriented siblings like dynatrace_managed_list_events and resource-specific detail tools like get_problem_details or get_slo_details. It does not explicitly name or contrast any sibling, so it stops short of a 5, but the resource term makes the intent 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?

No guidance is given about when to call this tool versus alternatives. It does not mention that dynatrace_managed_list_events is the natural precursor for obtaining an eventId, nor does it state any exclusions or selection criteria. Usage context must be inferred entirely from the tool name.

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 readOnlyHint annotation already covers the safety profile, and the description adds no behavioral context beyond a generic 'Get detailed information.' It does not disclose what details are returned, whether the metric must exist, or any response characteristics. No contradiction exists, but the description contributes little beyond the annotation.

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 a single front-loaded sentence with no filler or redundancy. It is appropriately concise for the tool's simple 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?

With no output schema, the description should indicate what 'detailed information' includes or how the result differs from querying metric data. It also lacks any usage context or distinction from closely related metric tools, leaving an agent to guess the tool's exact role.

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 100%, so the schema already documents both parameters. The description itself adds no parameter-level meaning, so the baseline score of 3 applies.

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 uses a specific verb ('Get') and clearly identifies the target resource ('specific metric'), making the core purpose understandable. However, it does not differentiate from sibling tools like query_metrics_data or list_available_metrics, so the distinction must be inferred from the tool name.

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?

No guidance is given about when to use this tool versus alternatives such as query_metrics_data or list_available_metrics. The environment_alias parameter references get_environments_info for obtaining aliases, but this is parameter-level instruction, not usage guidance for choosing this tool.

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, so no contradiction exists. The description adds useful context about the content returned (evidence details, affected entities, tags, management zones), but it does not discuss rate limits, authentication, pagination, or error behavior. Given the read-only annotation covers the safety profile, this is adequate but not exceptional.

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 short sentences. The primary purpose is front-loaded, and the critical identifier caveat appears immediately after. There is no redundant phrasing or filler.

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 read-only detail tool with two required parameters and no nested objects, the description provides the essential context: what data will be returned and which identifier to supply. The schema covers parameter semantics, and the readOnlyHint covers safety, so no critical information is missing.

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 100%, so the schema already fully documents both parameters. The description repeats the key caveat about using UUID problemId rather than displayId, which is helpful reinforcement, but it adds little beyond what the schema already states. A score of 3 reflects that the schema carries the parameter documentation burden.

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 states a specific verb and resource: 'Get detailed information about a specific problem.' It also lists the kinds of details returned (evidence, affected entities, tags, management zones) and explicitly distinguishes the identifier to use (UUID problemId from list_problems), which helps separate it from sibling detail and list 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 gives a clear contextual instruction: use the problemId from list_problems output, NOT the displayId. This effectively tells the agent where the required input comes from. It does not explicitly name alternative tools or state when not to use this tool, but the purpose and input source are unambiguous.

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, and the description adds meaningful behavioral context by specifying what the response includes: CVE details, affected entities, vulnerable components, code locations, and technical analysis. No contradiction exists, and the added content detail goes beyond the annotation.

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 a single focused sentence that leads with the action and target, then lists the key content areas. There is no filler or redundant restatement of the tool name.

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?

With no output schema present, the description reasonably explains what information will be returned, listing several concrete categories. Combined with the thorough parameter descriptions and the readOnly annotation, the agent has enough context to call it correctly, though a note on response structure or error behavior would make it fully 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?

The schema description coverage is 100%, so both parameters (securityProblemId and environment_alias) are already well documented. The tool description does not add parameter-level meaning, but with full schema coverage, the baseline of 3 is appropriate.

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 states a specific verb ('Get detailed information') and a specific resource ('a specific security problem'), and enumerates the content areas (CVE details, affected entities, vulnerable components, code locations). This clearly distinguishes it from sibling list/detail tools, especially list_security_problems and get_problem_details.

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 this tool is used when a specific security problem's details are needed, and the schema parameter notes the ID comes from list_security_problems. However, it does not explicitly state when to prefer this over get_problem_details or list_security_problems, leaving routing partially to inference.

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?

readOnlyHint=true aligns with the read-only nature of 'Get detailed information,' so there is no contradiction. The description adds little behavioral context beyond the annotation, such as return format, rate limits, or prerequisites, but for a simple read-only detail tool the annotation covers the main safety trait.

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 a single, front-loaded sentence with no wasted words. It states exactly what the tool does without redundancy or filler.

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 schema and read-only annotation make the tool callable: required parameters are clear, and timeFrame/from/to/environment_alias semantics are documented. However, there is no output schema and the description does not summarize what 'details' include or mention that an SLO ID must first be obtained via list_slos, leaving some ambiguity for an agent evaluating whether this tool answers a specific question.

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 100%, with all five parameters documented including formats, conditional usage, and environment-alias behavior. The description itself adds no parameter semantics, so the baseline of 3 applies because the schema carries the parameter documentation burden.

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 uses a clear verb ('Get') and a specific resource ('detailed information about a specific SLO'). It differentiates itself from sibling list_slos by targeting one specific SLO, and from other get_* tools by naming the resource.

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 gives no explicit when-to-use guidance or alternatives. It implies the user already knows an SLO ID, but it does not mention using list_slos to obtain an ID or when to prefer this tool over list_slos. The only cross-tool reference, get_environments_info, appears in a parameter description rather than usage 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 already declare readOnlyHint=true, and this description aligns with that. The description adds value by stating that results include aggregation types, dimension definitions, and technical metadata — useful behavioral context beyond the read-only flag. However, it does not mention pagination behavior or the possibility of a large result set beyond the limit parameter.

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?

One clean sentence that states the primary action, scope, optional filter, and result contents. Efficient and front-loaded with the verb and resource. 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 read-only listing tool with 100% schema coverage and detailed parameter descriptions, the definition is mostly complete. It could mention that the output is a list of metric definitions rather than values, but the description's mention of technical metadata already hints at that. Given the absence of an output schema, a slightly clearer statement of the return shape would help, but overall it is 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?

Schema description coverage is 100%, so the baseline is 3. The description adds a bit about the overall output contents (aggregation types, dimensions, metadata) but does not materially enrich the individual parameter semantics beyond what the schema already provides. The parameter descriptions are already detailed and self-sufficient, so this is slightly above baseline.

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 lists available metrics in the Managed cluster with optional entity filtering, and specifies that results include aggregation types, dimension definitions, and technical metadata. The verb 'List' plus the resource 'available metrics' distinguishes it well from sibling tools like query_metrics_data, get_metric_details, and list_entity_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 when to use it: when the user wants to discover available metrics, optionally filtered by entity, rather than querying metric data or getting details of a single metric. It does not explicitly name alternatives or state exclusions, but the sibling names and tool name make the context reasonably 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 declare readOnlyHint=true, so the safety profile is covered. The description adds minimal behavioral context beyond that, such as the 'all available' scoping, but does not disclose output format, pagination, or other behavioral traits.

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?

A single, front-loaded sentence that states the verb, resource, scope, and purpose without any wasted words. It does not repeat schema or annotation 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 operation with one well-documented parameter and a readOnly annotation, the description is nearly complete. It could be improved by naming related tools as a next step, but nothing critical is missing.

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 100%, and the environment_alias parameter description is rich, explaining how to obtain the alias and the ALL_ENVIRONMENTS option. The tool description itself adds no additional parameter meaning, so the baseline of 3 applies.

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 uses a specific verb ('List'), a clear resource ('all available entity types'), and a scope ('Managed cluster'), plus the intent ('to understand what types of entities can be monitored'). This clearly distinguishes it from sibling tools like get_entity_type_details or discover_entities.

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 purpose clause implies this is a discovery/prerequisite step, but the description does not explicitly state when to use this tool versus alternatives such as get_entity_type_details or discover_entities. No exclusions or routing guidance is 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 declare readOnlyHint=true, so the read-only nature is established. The description adds useful context about returned content (event properties, management zones, severity/impact levels, metadata) but does not disclose pagination, ordering, or other behavioral traits beyond what the annotation covers.

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 a single front-loaded sentence that first states the operation and timeframe, then describes the result contents. It is concise, though 'for comprehensive analysis' is somewhat filler.

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?

With six parameters and no output schema, the description is adequate but not complete. It summarizes the expected result fields but doesn't address response format, pagination, or how this list operation relates to related detail tools such as dynatrace_managed_get_event_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?

Schema description coverage is 100%, so the parameters are already well documented. The description adds only the general notion of a timeframe and result contents, without adding meaning beyond the schema's parameter 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 names a specific verb and resource: 'List events from the Managed cluster within a specified timeframe.' It clearly indicates this is a listing operation for events, but it does not explicitly distinguish it from sibling read operations such as dynatrace_managed_get_event_details or list_problems.

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?

There is no guidance about when to use this tool versus the many siblings. No alternatives are named, no exclusions are given, and the description only implies a use case rather than stating conditions under which it should be selected.

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 readOnlyHint annotation already covers the safety profile, and the description is consistent with it. It adds the 'Managed cluster' scope and the notion of optional filtering, but does not disclose pagination, result shape, or time-window defaults beyond what the schema already states.

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?

One short, front-loaded sentence with no filler. It communicates the core action and optionality efficiently, and every word contributes to the 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?

For a read-only list operation backed by a rich 100%-covered input schema, the description is nearly complete. It does not mention output shape or sibling-selection guidance, but these are largely inferable from the tool name and the sibling list.

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 100%, so the schema already documents every parameter with meaningful details, including enum values and entitySelector examples. The description itself adds no parameter-level semantics, but the full coverage justifies the baseline score.

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?

States the verb 'List' and the resource 'problems' with a scope qualifier ('from the Managed cluster'). It clearly identifies the operation, but does not explicitly distinguish itself from siblings like get_problem_details or list_events, so it stops short of a 5.

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 offers no guidance about when to use this tool versus alternatives such as get_problem_details for individual problems or list_events for event data. 'Optional filtering' is a generic hint that does not help an agent choose correctly among siblings.

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 readOnlyHint annotation already covers the safety profile, so the description only needs to add value beyond that. It does add useful output context by listing the kinds of data returned (package names, technology details, vulnerable components, risk assessment). However, it does not disclose any behavioral quirks, defaults, limits, or relationship to environment aliases, though these are partially covered in the schema.

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 a single focused sentence that front-loads the verb and resource. It includes concrete output categories without unnecessary elaboration. The only slight filler is 'comprehensive,' but it does not meaningfully hurt clarity or 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?

There is no output schema, so the description should convey enough about the return value; it does list primary output categories, which is helpful. However, it omits any guidance about pagination limits, default time windows, or when to combine this with get_security_problem_details for deeper inspection. Given the schema covers most invocation details, the description is minimally viable but leaves several contextual 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?

Schema description coverage is 100%, so the baseline is 3 and the description does not need to repeat parameter details. The description does not add extra meaning to parameters like sort, limit, status, riskLevel, or entitySelector, but the schema already documents them thoroughly, including examples and constraints. The description's mention of risk assessment data loosely aligns with riskLevel but adds little 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 identifies the action ('List') and the resource ('security problems and vulnerabilities from the Managed cluster'), and it distinguishes this tool from sibling list_problems (general problems) and get_security_problem_details (single-problem detail). The mention of package names, technology details, and risk assessment data further clarifies what kind of listing this is.

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?

No guidance is given on when to use this tool versus alternatives such as list_problems or get_security_problem_details. The description does not state whether this should be used before fetching details, how it relates to the general problems API, or when filtering via entitySelector would be preferable. The usage context is only implicit from the tool name and schema.

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 annotation already declares readOnlyHint=true, and the description does not contradict it. It adds useful non-obvious behavioral context: evaluate=true requires limiting results to 25 or fewer. It also discloses the categories of returned data, which is helpful since no output schema is provided.

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 three compact sentences with no filler. It front-loads the core purpose, then summarizes return contents, and ends with a high-value constraint. Every sentence earns its place.

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 schema documents all 11 parameters, and the description adds result-content context and a critical usage constraint. It does not describe the exact output shape or pagination behavior, but the absence of an output schema is partially compensated by the results summary. Overall, an agent has enough information to invoke this 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?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful parameter interaction guidance beyond the schema by warning that evaluate=true forces a limit of 25 or fewer, which is not evident from the individual parameter 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 verb and resource: 'List Service Level Objectives (SLOs) from the Managed cluster.' It also enumerates the kind of data returned, which distinguishes this listing operation from the sibling get_slo_details tool.

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 gives clear context by framing this as a listing operation and includes a critical evaluate/limit constraint, but it does not explicitly tell the agent when to use list_slos versus get_slo_details or any other alternative. The distinction is inferable from the tool name and siblings, but not stated.

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, so no safety contradiction exists. The description adds useful behavioral detail beyond annotations: results include event types, expanded metadata fields (up to 8), and enhanced error detection, plus the managed-cluster limitation about structured syntax.

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?

Two sentences, front-loaded with the core action, then a precise limitation. No filler or repetition of schema content, and every sentence earns its place.

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?

With a rich 6-parameter schema covering all parameter semantics and a readOnly annotation, the description adds the key missing context: result shape and syntax limitations. It does not fully describe return structure, but for a log query tool this is sufficient for correct invocation.

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 100%, so the schema already documents all parameters including the 'query' guidance. The description reinforces the no-structured-syntax rule but does not add substantial meaning to individual parameters, keeping this at the baseline.

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 uses a specific verb ('Search') and targets a clear resource ('logs'), making the tool's function immediately apparent. It does not explicitly name or contrast sibling tools, but the log resource is distinct from metrics/events/entity tools in the sibling list.

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 clearly states how to use the tool: with simple text queries, not structured syntax. It also gives a concrete exclusion ('content:' or 'loglevel:'), helping the agent avoid invalid queries. It does not mention alternative tools, but there is no close log-query sibling to contrast with.

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 provide readOnlyHint=true, and the description adds useful behavioral context about querying metrics: large amounts of data can be retrieved, so entitySelector, timerange, and resolution must be constrained. It does not describe output shape or failure modes, but for a read-only tool with annotations this is reasonable coverage.

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 core purpose and then presents constraints compactly. It is efficient and every clause adds value, though the opening 'Must limit the amount of data being retrieved' is somewhat redundant with the three following 'must' clauses.

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, combined with the rich schema, covers the main invocation details and safety constraints. However, there is a notable mismatch: the description says entitySelector and resolution 'must' be used, while the schema marks them optional. It also does not describe the expected response shape, which is notable since there is no output schema. These gaps leave an agent somewhat uncertain about mandatory call requirements.

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 100%, so the baseline is 3. The description adds cross-parameter meaning beyond the schema by mandating a specific entitySelector, a narrow timerange, and a resolution aligned with that range (e.g., hours rather than minutes for multi-day data). This gives operational context not present in the individual parameter 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 operation ('Query metric data') and its primary filters (time range, metric selector), which distinguishes it from siblings like list_available_metrics or get_metric_details. It does not explicitly name a sibling, but the resource and filtering criteria are unambiguous enough for an agent to understand what this tool does.

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 gives explicit, actionable guidance: use a specific entitySelector, a narrow timerange, and a resolution matched to the timerange. However, it does not explicitly state when to avoid this tool or point to alternatives like list_available_metrics or discover_entities, so it stops short of full tool-selection guidance.

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