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

With no annotations, the description carries the full burden, and it does disclose some behavior: token management/auto-optimization, multi-modal context, and full document content access. It omits anything about whether the call is read-only, whether it incurs provider cost or latency, and whether history is maintained across calls. Some useful traits, but the safety and cost profile is absent.

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?

Front-loaded with the tool's role, which is good, but the text is padded with an emoji and says 'comprehensive' twice ('comprehensive knowledge queries' / 'comprehensive responses'). 'Intelligent token management' and 'Automatically optimizes for token limits' restate the same idea. Roughly half the content 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 six parameters, no annotations and no output schema, the description should explain what a call returns and how it behaves, but it stays at a marketing level. Nothing tells the agent the shape of the answer, whether citations/documents come back, or how multi-modal content is surfaced, leaving a real gap for a 6-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 description coverage is 100%, so all six parameters (message, tags, types, provider, maxResults, useMultiModal) are already documented in the schema. The description only loosely gestures at 'multi-modal context' and token optimization, adding no syntax or format detail beyond the schema. Baseline 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 states it is a RAG-powered conversational query tool, which is a specific enough verb+resource to distinguish it from kms_get_document, kms_list_documents and kms_get_stats. However, it claims to be the 'Primary tool for comprehensive knowledge queries' without distinguishing itself from kms_search, kms_intelligent_search or kms_multimodal_search, all of which sound equally applicable. The 🚀 and repeated 'comprehensive' are promotional rather than clarifying.

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 statement of when to use this tool versus the search siblings, and no prerequisites or exclusions. Claiming to be the 'Primary tool' is a mild routing hint but gives the agent no decision rule when several sibling search tools exist. An agent could not tell from this text whether kms_chat should be preferred over kms_intelligent_search.

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?

No annotations are provided, so the description carries the full burden. 'Retrieve' implies a read-only operation and the description usefully discloses the return payload (content, transcriptions, metadata), but it is silent on permissions, whether access is logged, and output format or pagination 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?

A single front-loaded sentence with the action, key, and payload in order. Every clause earns its place and nothing is repeated from the 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?

For a simple one-parameter read tool with no annotations and no output schema, the description covers the essential retrieval semantics and return contents. It stops short of stating read-only guarantees or error behavior when an ID is not found, which would be the remaining value-add.

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 is one parameter with 100% schema coverage; the schema already documents documentId as a UUID string. The description adds only the redundant 'by ID' framing, so it neither compensates nor detracts — the baseline of 3 for a fully-covered single param 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?

Names a specific verb (Retrieve) and resource (document) with the lookup key (by ID) and the payload returned (full content, transcriptions, metadata). It implicitly separates itself from the search/list siblings by being ID-based rather than query-based, but never names an alternative to sharpen that distinction.

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 phrase 'by ID' implies the precondition (you must already have a documentId), which is the only usage guidance present. There is no explicit when-to-use versus kms_search or kms_list_documents, and no exclusions or prerequisites 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?

With no annotations, the description carries the full burden, and it does disclose the categories of data returned (counts, processing status, performance metrics), which implies a read-only reporting operation. It stops short of stating cost, permissions, freshness, or whether the call is expensive, so it only partially compensates for the missing 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?

One front-loaded sentence with no filler sentences and the resource named early. 'Comprehensive analytics and statistics' is mildly redundant padding but not wasteful enough to hurt 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?

For a zero-required-parameter read tool with full schema coverage and no output schema, the description adequately previews return content (document counts, status, performance metrics). Adding the effect of includeProcessingDetails would make it airtight, but nothing essential 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 single parameter (includeProcessingDetails) is fully documented in the schema with its default. The description adds no syntax or meaning beyond the schema, 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?

States a specific verb ('Get') and resource ('analytics and statistics about the KMS system') and enumerates the content returned: document counts, processing status, performance metrics. It is clearly not a search/chat tool, so it separates from the kms_search/kms_chat siblings by implication, though it never names them explicitly.

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 on when to call this versus kms_list_documents or kms_get_document for counts/status, and no prerequisites or conditions stated. The agent must infer that 'stats' means aggregate reporting rather than document retrieval.

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?

With no annotations, the description carries the full burden and largely fails. It never discloses that this is a read operation, that the 'intelligent query analysis' and 'routing' likely incur extra latency/cost versus plain search, what 'full content access' actually returns (full documents vs. snippets), or how results are ordered and paged.

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?

Only two sentences, so it is short, but the second sentence ('enhanced middleware for optimal search strategy selection') largely restates the first's 'intelligent... routing' and carries no actionable information. Not bloated, but not earning its words either.

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 4-parameter tool with a nested filters object, no output schema, and no annotations, the description omits the essentials: sibling differentiation, the cost/latency implication of the analysis step, and the response shape. It describes implementation machinery rather than what the agent needs to call it 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 description coverage is 100% and the nested filters object is documented field-by-field, so the schema does the heavy lifting and the baseline of 3 applies. The description adds no parameter meaning beyond the schema, e.g. it does not explain what includeAnalysis=true changes about the response.

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 verb+resource is identifiable (a search over KMS content), but the differentiating content is marketing jargon: 'advanced', 'intelligent', 'optimal'. It never states concretely what it does that kms_search does not, so an agent cannot distinguish the two siblings from the text alone.

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 when-to-use guidance, no when-not-to-use, and no mention of the obvious alternatives (kms_search, kms_multimodal_search). 'Advanced' vaguely hints at complex queries but the choice between siblings is left entirely 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?

With no annotations, the description carries the full behavioral burden. It implies a read-only listing and a recency order, but does not disclose pagination, sorting definition, default limit behavior, permissions, or result shape beyond 'documents'.

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 and front-loads the core action. The second sentence is somewhat generic, but it does provide a usage cue without unnecessary verbosity.

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 list tool with fully described optional filters, the definition is minimally adequate. However, without annotations or an output schema, it should say more about return behavior, ordering, and pagination to fully guide 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 all four filter parameters are already documented in the input schema. The description only says 'filtering options' and adds no parameter-level meaning beyond what the schema provides, making 3 the appropriate 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 states a specific verb and resource: list documents, scoped to recent ones, with filtering. This is clear enough to distinguish it from search-oriented siblings, but it does not explicitly name an alternative or contrast itself with kms_search or kms_intelligent_search.

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 phrase 'useful for browsing and discovering content' implies a usage context but gives no explicit when-to-use or when-not-to-use guidance. It does not tell the agent to prefer search tools for targeted queries or explain when listing is preferable.

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?

No annotations are provided, so the description carries the full burden. It discloses that it retrieves 'full content' and detects technical content across modalities, which is useful behavioral context. However, it says nothing about rate limits, permissions, result ordering, or whether results are deduplicated across content types.

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, tightly front-loaded with the core purpose first and modality/technical-detection details second. Minimal waste, though the second sentence is somewhat dense with comma-separated features.

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 4-parameter search tool with nested filters, 100% schema coverage, and no output schema, the description is adequate but lacks crucial routing information: when to use this vs kms_search / kms_intelligent_search. An agent has enough to invoke it but not enough to confidently select it.

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 four parameters and their semantics. The description adds no parameter-level detail beyond what the schema provides. Baseline 3 is appropriate when the schema does the heavy lifting.

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 a specific verb and resource: 'Enhanced multi-modal search with full content retrieval', and specifies the modalities covered (text, audio, video, video frames) plus technical content detection. Clear purpose, though it doesn't differentiate itself from siblings like kms_search or kms_intelligent_search.

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 when-to-use or when-not-to-use guidance is provided. The description doesn't explain how this differs from kms_search or kms_intelligent_search, leaving the agent to infer or guess which sibling to choose.

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?

No annotations are provided, so the description must disclose behavioral traits. It mentions full document content retrieval but doesn't specify return format, pagination, performance, or how results are ranked beyond vector similarity.

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 effective sentence that front-loads the core purpose. Slightly redundant with 'searches through text documents' 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?

Given no annotations, no output schema, and multiple similar siblings, the description is minimally viable but lacks differentiation and behavioral details (e.g., authentication, rate limits, result format).

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 schema already documents all parameters. The description adds no further meaning about query, limit, or threshold beyond what the schema provides.

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 a specific verb (semantic search) and resource (documents), and clarifies the search modality (vector similarity). However, it doesn't differentiate from close siblings like kms_multimodal_search or kms_intelligent_search, leaving the agent to guess which to use.

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 on when to use this tool versus alternatives such as kms_multimodal_search or kms_intelligent_search. Only implied usage based on the name.

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