Dokpod

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds some context by revealing that comparison uses summaries and key chunk excerpts, but it does not disclose the return format, whether output is a generated narrative, or how chunk selection works. OpenWorldHint=false also provides context, but behavioral transparency beyond that is minimal.

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. It communicates the action, object, and mechanism efficiently, earning its place fully with zero 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?

With no output schema and only a terse description, the definition lacks clarity on what the tool returns (e.g., a summary of similarities/differences, a list of excerpts) and how the result should be interpreted. It also omits guidance on prerequisite setup, such as how to obtain document IDs. The description is not sufficient for a 3-parameter tool with no structured return documentation.

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%, so the description must carry meaning. It maps document_id_1 and document_id_2 to 'two documents' and links excerpt_chunks to 'key chunk excerpts,' which gives an agent a rough semantic understanding. However, it doesn't explain the exact role of excerpt_chunks (e.g., number of chunks per document or total) or any constraints on IDs, leaving notable ambiguity.

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 ('Compare'), a clear resource ('two documents'), and the method ('using summaries and key chunk excerpts'). It clearly differentiates from all sibling tools, none of which perform document comparison, and leaves no ambiguity about the tool's core function.

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 a use case (comparing two documents) but gives no explicit guidance on when to choose this tool over alternatives like semantic_search or summarize_document. There are no exclusions, prerequisites, or conditions stated, so an agent is left to infer usage from the name and verb alone.

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 destructiveHint=false, so the safety profile is covered. The description adds the partial-vs-exact matching behavior, which is useful context beyond the annotations. It does not disclose additional behaviors like case sensitivity or result limits, but with annotations carrying the safety burden this is adequate.

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 concise sentences. The first front-loads the core action and scope, and the second adds a clear usage trigger. Every word earns its place 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?

For a simple read-only filename lookup with complete parameter schema and safe annotations, the description covers the essential context. It does not explain the return structure or edge cases like case sensitivity, but given the low complexity and the presence of a clear usage trigger, it is sufficiently 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?

Schema description coverage is 100%, with both 'filename' and 'exact' already documented in the input schema. The description's phrase 'exact or partial filename' reiterates but does not significantly extend the schema's parameter documentation. Baseline 3 applies because the schema handles parameter semantics.

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 ('Find'), a specific resource ('vault files'), and a clear matching criterion ('exact or partial filename'). It also distinguishes itself from semantic-search siblings by tying usage to explicit filename references, so an agent can quickly tell this apart from tools like semantic_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 description explicitly says when to use this tool: 'when the user mentions a specific file name, PDF title, or screenshot name.' It does not explicitly name alternatives or state when not to use it, but the usage context is clear enough for most cases.

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 destructiveHint=false, so the safety profile is covered. The description adds the selection-by-two-IDs behavior but provides no details about error cases, such as what happens when the chunk is not found, or whether the full chunk content is returned. 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 a single sentence with no filler, and the verb and required identifiers are front-loaded. 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 simple read-only fetch with two required string parameters and no output schema, the description states the operation and required inputs. It does not specify the response structure or chunk content, but the low complexity and clear title make this an acceptable level of completeness.

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%, so the description must compensate. It only restates the parameter names in prose ('by document_id and chunk_id') without explaining what a chunk is, the format of the IDs, or how they relate. This adds minimal semantic value 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 uses a specific verb 'Retrieve' and names the resource 'specific chunk', with explicit identifiers (document_id and chunk_id) that define the operation's scope. It is clearly distinct from sibling tools like semantic_search or list_media, which have different purposes.

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 usage context is implied: an agent would use this tool when it already has both a document_id and a chunk_id. However, there is no explicit when-to-use guidance or mention of alternatives, so the agent must infer the appropriate invocation scenario.

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 cover the read-only, non-destructive nature, so the description's job is lighter. It adds the useful detail that the result is 'full' and includes captions, frames, and transcript, but it does not disclose response size, error behavior, or media-type constraints. This is adequate given the existing annotation 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?

A single, compact sentence with no redundant wording. The essential content of the tool is front-loaded, and the parenthetical adds precise value without bloating the definition.

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, single-parameter lookup with annotations covering safety and no output schema, the description provides enough to select and invoke the tool correctly: what media_id targets and what the return includes. Nothing critical is missing for an agent to act.

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%: the only parameter, media_id, is described as 'Document ID' in the schema. The tool description does not add extra meaning about the format or origin of media_id, so it stays at the baseline for fully covered schemas.

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 verb ('Get'), a resource ('media description'), and the scope ('full AI-generated description for an image or video') with a concrete content breakdown (captions, frames, transcript). This distinguishes it from siblings like get_relevant_frames or semantic_search_media, which serve different retrieval purposes.

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?

Usage is implied: when you have a media_id and want the stored full description, this is the tool. However, there are no explicit statements about when not to use it or which sibling to prefer in overlapping scenarios, such as get_relevant_frames for frames alone.

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 establish that the operation is read-only and non-destructive. The description adds useful behavior context: it filters to the most relevant frame descriptions and is designed for low token usage. It does not mention any limits, ordering, or what happens when no frames match, but that is not essential for this simple read operation.

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 communicates target, filtering behavior, and the token-efficiency benefit with no redundant wording. Every phrase 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?

For a simple three-parameter read-only tool, the description covers the key return value (frame descriptions) and the relevance filtering, while the schema supplies parameter names and the default for top_k. It still misses explicit sibling differentiation and does not clarify how relevance results are ordered or limited, so it is adequate but not 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?

Schema description coverage is 0%, so the description must explain parameter meaning; it only implicitly maps 'video' to video_id and 'query' to query. top_k is never mentioned in the description, leaving its semantics entirely to the schema's bare name and default.

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 resource ('frame descriptions for a video') and a specific operation ('return only ... most relevant to a query'), so the tool's core purpose is clear. It does not explicitly contrast with siblings like semantic_search_media or get_media_description, so it lacks the explicit differentiation that would earn 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 implies the use case: when you need a compact, query-relevant subset of frame descriptions from a video, with low token usage. It does not state when to prefer an alternative, nor does it name any exclusions, so guidance is only implicit.

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 destructiveHint=false, so the safety profile is covered. The description adds the vault scope and output style but does not disclose pagination, ordering, or limits; for a simple list tool this is adequate but not rich.

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 sentence with no filler, front-loading the action, scope, and output. Every word contributes meaningful information, and the structure is immediately scannable.

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 one-parameter, read-only list operation with annotations covering safety, the description plus schema is sufficient for correct invocation. It could state the default when type is omitted or note pagination behavior, but these are minor gaps given the tool's simplicity.

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%, including the optional type enum with its own description, so the baseline of 3 applies. The description's mention of images and videos aligns with the type filter but adds no behavioral detail such as default behavior when type is omitted.

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 action ('List') and resource ('images and videos in the user's vault'), and signals the output form ('summaries and metadata'). This makes it distinguishable from siblings like semantic_search_media, which implies relevance-based retrieval, and get_media_description, which targets a single item.

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 as a listing/inventory tool but gives no explicit when-to-use guidance or alternatives. An agent must infer from sibling names that semantic_search_media is the search counterpart, so clear context exists but exclusions are absent.

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 establish readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds value by disclosing the return payload contains titles, tags, chunk counts, and status. It does not mention pagination, ordering, or potential absence of documents, which would be more transparent for a zero-parameter 'list all' operation.

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, no filler, and the primary action is stated first. The second sentence enumerates the return fields without unnecessary elaboration. 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?

For a no-parameter read-only list tool, the description is largely complete: it states the resource scope, the action, and the returned data fields. Since no output schema exists, the return-field list is important and provided. The only gap is guidance on large result sets or ordering, which is a minor omission for this simple 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?

The tool has zero parameters and the schema confirms this, so there are no parameter semantics to document. The description reasonably focuses on the output instead, which is the only meaningful facet an agent needs to understand.

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 and resource, 'List all documents in the user's Dokpod vault,' making the core action unmistakable. It also names the returned fields, which separates it from media-focused siblings like list_media and search-focused tools like semantic_search. It does not explicitly contrast with siblings, 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 clearly implies this is the tool for retrieving an unfiltered overview of all vault documents, with no parameters to narrow scope. However, it provides no explicit guidance about when to prefer find_documents_by_name or semantic_search instead. Usage context is present but alternatives and exclusions are left 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?

Annotations already declare the operation read-only and non-destructive. The description adds valuable behavioral context by stating it returns only the most relevant chunks and minimizes token usage, which informs the agent that output is distilled rather than full documents. This goes beyond annotation data without contradicting it.

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, tight sentence followed by a short, informative clause. Every word earns its place, and the core action is front-loaded. No filler or redundant restatement of the tool name is present.

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 is adequate for a simple semantic-search tool, especially given the annotations, but it omits key contextual details such as how filtering parameters affect the search and what the returned chunk structure looks like. Since there is no output schema, a bit more detail about the return format or behavior with no matches would improve completeness.

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 only 50%, and the description does not compensate for the undocumented tags and document_ids parameters. It does not explain that tags can filter results or that document_ids restrict the search scope; it only references the query concept implicitly. With half the parameters left unexplained, the description fails to add 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 names a specific verb ('Search'), a specific resource ('the user's document vault'), and the search method ('semantically'), which clearly distinguishes it from sibling tools like semantic_search_media or find_documents_by_name. The added detail about returning relevant chunks further clarifies its role as a chunk-level retrieval 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 implies a semantic-search use case but gives no explicit guidance on when to choose this tool over siblings such as find_documents_by_name or semantic_search_media. There is no mention of exclusions, preferred scenarios, or alternatives, leaving the agent to infer routing from the tool name and 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?

Annotations already indicate read-only, non-destructive behavior. The description adds useful behavioral context beyond annotations by stating that results are captions, frame descriptions, or transcript segments and that the output is intentionally minimal in tokens. 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 a single, well-structured sentence with the core action front-loaded and the return behavior stated immediately. Every phrase earns its place with no 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 four parameters, no output schema, and several closely related sibling tools, the description is too minimal. It leaves out how top_k and document_ids affect results, when to prefer this tool over semantic_search or get_relevant_frames, and the exact shape of the returned results.

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 only 50%, and the description adds no parameter-level meaning. It does not explain top_k or document_ids, and while query and type are documented in the schema, the description does not compensate for the undocumented 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 specific verb and resource: 'Search images and videos semantically' and clarifies the return types (captions, frame descriptions, or transcript segments). It is clear and distinct from a generic semantic search, though it does not explicitly name a sibling 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 tool is for semantic search over media content, but it does not say when to choose it over sibling tools like semantic_search, get_media_description, or get_relevant_frames. No exclusions or alternative routing 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 declare readOnlyHint=true and destructiveHint=false, establishing a safe read context. The description adds the behavioral trait 'without loading all chunks,' which provides some value about resource usage, but does not disclose return format or error behavior. This aligns with annotations without contradiction.

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

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

A single, front-loaded sentence with no filler. It communicates the essential action, resource, and a key behavioral qualifier efficiently.

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 one-parameter read tool with safety annotations, the description covers the basic purpose and resource. However, with no output schema, it leaves 'metadata' vague and does not explain what exact summary or metadata fields are returned, nor any prerequisites like document ownership.

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%, so the description must compensate, but it only refers obliquely to 'a document' and does not explain document_id beyond what the parameter name implies. No guidance on identifier format, origin, or examples is provided.

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 ('summary and metadata for a document'), and the phrase 'without loading all chunks' differentiates it from the sibling get_chunk, indicating a higher-level retrieval. This clearly distinguishes the tool's core function.

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 context for use: when a concise summary or metadata is needed and full chunk loading is not desired. However, it does not explicitly name alternatives or state when not to use this tool, stopping short of full usage routing.

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