Plaud

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

Beyond the annotations, the description adds useful behavioral context: the distinction between permanent and session-only connections, how to pass the token, and what happens with no arguments. It does not fully describe the response for a token call, but no annotation contradiction 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?

Two sentences cover the core action, recommended setup, alternative session-only flow, and no-argument behavior with almost no filler. The structure is scannable and front-loaded.

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-optional-parameter auth tool with no output schema and annotations covering safety/idempotence, this description is nearly complete. It covers all call variants and the link retrieval behavior, though it could briefly state what happens after a successful token-based login.

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

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

Schema coverage is 0%, so the description carries the burden. It explains that token is an optional JWT pasted by the user and that omitting it returns the login link. This is helpful, though it does not fully specify token constraints or the success 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 description states a specific action: authenticate with MCP.AI by logging in through a browser and using an access token. It is detailed enough to be distinguished from sibling tools like connect or marketplace, even without explicitly naming them.

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

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

It gives explicit usage paths: configure a permanent Authorization header, pass a token for a session-only login, or call with no args to get the login link. It never explicitly contrasts this with a sibling tool like connect, so it misses the highest bar for 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value beyond those annotations by explaining the two concrete return-state behaviors: fully connected returns authenticated:true with empty pending[], and missing credentials returns connect_url plus per-install URLs.

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 with no filler. The main purpose is front-loaded, and the conditional return behavior is clearly and compactly explained.

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, no-output-schema tool, the description covers the main behavioral cases: connected versus missing credentials. It could mention partial connection states or the exact shape of pending[], but the description is sufficiently complete for a simple status check.

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

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

The input schema has zero parameters, so the baseline is 4. There are no parameters for the description to clarify, and it correctly focuses on behavior and return states instead.

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

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

The description opens with a specific verb and resource: 'Returns connection status and URLs.' It clearly distinguishes itself from siblings like authenticate by describing a read-only status/URL-reporting behavior rather than an authentication flow.

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 checking connection status and retrieving URLs when credentials are missing, but it does not explicitly state when to use this tool versus alternatives like authenticate. There is no direct when-to-use or when-not-to-use guidance, only an implied context.

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

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

The description discloses that invoke works even when the MCP is not installed, runs one-off without bloasting the tool list, and returns connect or checkout/top-up links when credentials or payment are missing. It also states that writes require workspace owner/admin and that search/describe flag installed_in_toolkit vs installed_in_workspace. None of this appears in the annotations, so the description adds substantial behavioral context beyond them.

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?

Despite being long, almost every sentence earns its place: purpose, core flow, key invoke exception, install-vs-invoke rule, billing/feedback/request routes, permission note, and prompt library. It is front-loaded with the catalog/running purpose before diving into flow. It could be improved by breaking the one wall of text into bullets or short labeled sections, so it gets a 4 rather than 5.

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 23-parameter, 14-action tool with no output schema, the description covers the core workflow, exception behavior, permission requirements, and the separate prompt-library feature. It does not document each parameter or return shape, but the action-level semantics are sufficient for an agent to route correctly across most scenarios. A fully complete definition would add per-parameter notes and output expectations.

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 the burden for parameter meaning. It maps the action enum to behaviors and explains concepts like prompt_vars ('{{variables}} filled') and prompt_slug (shareable mcp.ai/p/<slug> link). However, with 23 parameters, many like limit, query, immediate, tier_slug, cancel_reason, prompt_targets, and request_details are not individually described, leaving gaps in parameter-level 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 opens by defining the tool as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' which clearly establishes its role. It enumerates the capability requests it covers and sketches the search → describe → invoke flow. It loses one point because it is an umbrella for many sub-actions rather than a single verb+resource, and sibling differentiation is implicit rather than explicitly contrasted.

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

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

It gives explicit decision rules: 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use' and says list_tools lists what is callable right now. It also assigns report_bug, request_mcp, subscribe/cancel, and search_prompts/get_prompt/publish_prompt to specific intents, so an agent knows when to use which mode. This is strong when-to-use guidance, not vague.

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, idempotentHint=true, and destructveHint=false, so the safety profile is covered. The description adds useful behavioral context beyond annotations by disclosing bulk/batched execution via file_ids and by specifying what the returned notes contain.

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 short sentences with no filler. The main purpose is front-loaded, and the bulk behavior is separated clearly.

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 tool with no output schema, the description gives enough about the return content and batch support. However, the undocumented account parameter and the lack of any note about the file_id/file_ids interaction leave a noticeable gap for an agent preparing a call.

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 parameter meaning. It explains file_ids for batched execution and file_id is inferable as the required single-file selector, but it leaves the account parameter completely undocumented and does not clarify the relationship between file_id and file_ids.

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 resource (AI-generated notes from a recording) and the content of those notes (compact summary, action items, key topics). This clearly distinguishes it from sibling tools like plaud_get_transcript and plaud_get_recording.

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: retrieve AI notes rather than raw transcript or recording. It also adds a concrete usage note about bulk execution via file_ids, but it does not explicitly state when to prefer this tool over siblings or provide 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 description adds the behavioral trait of bulk execution (accepting multiple file_ids), which is not covered by the annotations. However, it does not disclose other behavioral aspects like error handling, response format, or whether it returns partial data. The annotations already cover read-only, idempotent, and non-destructive nature, so the added value is moderate.

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

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

The description is extremely concise, consisting of two short sentences. It is well-structured, with the primary purpose stated first and the bulk support note second. No unnecessary words or repetition – it effectively communicates the core functionality in a minimal space.

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 complete enough for a basic understanding but lacks important context. It does not specify what 'details' include (e.g., metadata, transcription, audio URL) or any return format. Given the existence of sibling tools for notes and transcript, it's unclear if this tool returns all of that or just basic info. The absence of output schema also leaves room for ambiguity, making it less than 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 includes three parameters (account, file_id, file_ids). The description only partially explains file_ids (bulk support) and does not clarify the role of 'account' or 'file_id' individually. Given the low coverage (only one parameter is implicitly mentioned), the description adds minimal semantic value beyond the schema's type definitions.

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 that the tool retrieves details of a Plaud recording by ID, using a specific verb ('get details') and resource ('recording'). It is distinct from siblings like plaud_get_notes or plaud_get_transcript, though it doesn't explicitly contrast with them. The term 'details' is somewhat vague but sufficient for a basic understanding.

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 does not provide guidance on when to use this tool versus alternatives. It only mentions bulk support via file_ids, which is more about parameter usage than selection criteria. There is no indication of scenarios where this tool is preferred over others, such as when a full recording object is needed versus just notes or transcript.

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 read-only, idempotent, and non-destructive behavior, and the description adds what the response contains (timestamps, speaker attribution) and the bulk execution mode. It does not contradict annotations and provides meaningful operational context beyond them.

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 short, front-loaded sentences: the core behavior comes first and the bulk note second. Every word earns its place with no repetition of the tool name or schema.

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 retrieval tool, the description covers the output content and the bulk option, and the annotations cover safety. It is slightly incomplete on account/parameter interplay, but given the low complexity this is a solid, usable definition.

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 explains file_ids as the bulk batch input and ties the transcript to a recording (file_id), but it leaves account completely unexplained and does not clarify the relationship or precedence between file_id and file_ids.

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 that the tool returns a complete transcript with timestamps and speaker attribution for a recording, a specific verb/resource pairing. This clearly distinguishes it from sibling tools like plaud_get_recording and plaud_get_notes by naming the transcript content.

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

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

It implies when to use the tool (when a transcript with speakers is needed) and how to batch with file_ids, but it never explicitly contrasts with alternatives or states when not to use it. The bulk-support note is useful usage context, but routing/exclusion guidance is 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds no behavioral context—it does not mention authentication requirements, potential errors, or what the returned data contains. Since it adds nothing beyond the name, it fails to enrich the annotation-only picture.

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, succinct sentence with no filler or redundant detail. It is appropriately front-loaded and matches the trivial complexity of the tool. Nothing is over-explained or missing in terms of structure.

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

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

For a tool with no output schema, the description should at least hint at what fields the user data contains (e.g., name, email, ID). It only says 'user data' without any elaboration, leaving the agent uncertain about the shape of the response. Given the tool's low complexity, a few more words about the return payload would make it 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 tool has zero parameters, and the schema description coverage is 100% (empty schema). Per the rubric, 0 parameters earn a baseline of 4. The description does not need to explain parameters, and it correctly abstains from inventing any.

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 the tool returns data about the authenticated Plaud user ('Dados do usuário Plaud autenticado'). The verb is implied but clear from context, and the resource (user) is distinguished from sibling tools that handle notes, recordings, and transcripts. It is not a tautology and conveys the core purpose.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention that this is the go-to for retrieving the current user's profile, nor does it compare with sibling tools like plaud_get_notes. For a simple getter it might seem obvious, but explicit context is 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 readOnly, idempotent, and non-destructive behavior. The description adds valuable behavioral detail beyond annotations: query is a case-insensitive substring, dates are inclusive YYYY-MM-DD, and with a filter it auto-paginates up to 5×100 and returns all matching results. No contradiction 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?

Two short sentences with the purpose front-loaded and no filler. The filter and pagination details are packed efficiently in the second sentence without redundancy.

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

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

The description conveys the core purpose and filter behavior well, but it omits the meaning of account/page/page_size and does not describe the return shape, which matters because there is no output schema. The no-filter pagination behavior is also left implicit.

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% and there are 6 parameters, so the description must compensate. It precisely documents query, date_from, and date_to semantics, but it does not explain account, page, or page_size, leaving a meaningful portion of the parameter surface undocumented.

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

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

The description opens with 'Lista gravações Plaud', naming a concrete verb (list) and resource (recordings). This clearly distinguishes it from sibling tools like plaud_get_recording, plaud_get_notes, and plaud_get_transcript by scope and action.

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 for when this tool is appropriate: listing Plaud recordings with optional filters. It does not explicitly name alternatives or exclusion conditions, but the listing scope versus the sibling get-style tools is evident from the description and tool names.

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 tool is not read-only, not destructive, and idempotent. The description adds useful behavioral context by instructing the caller to include recent messages for reproduction, but it does not describe side effects (e.g., ticket creation), expected response, or whether the report is submitted anonymously. This is adequate given the annotation coverage 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?

Two sentences with no filler. The first sentence states the core purpose, the second delivers the key usage instruction. Every word earns its place, and the critical guidance (include conversation for reproduction) is front-loaded and concise.

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 sufficient for a simple call: the user's complaint goes in 'message', and 'conversation' aids reproduction. However, it overstates the conversation requirement (it is optional with a default), omits the 'context' parameter entirely, and does not mention what happens after submission. Given no output schema and three parameters, more detail would help an agent invoke it correctly every time.

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 mentions the 'conversation array' and its purpose, but the schema defines 'conversation' as a string, not an array, which could mislead. It does not explain the required 'message' parameter or the optional 'context' parameter. The description only partially clarifies 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 action ('Report') with clear targets ('a bug, missing feature, or send feedback'), making the tool's purpose immediately obvious. It is distinct from all sibling tools, which are authentication, marketplace, or Plaud-related operations, so there is no ambiguity with alternatives.

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 indicates when to use the tool: whenever the user wants to report a bug, request a missing feature, or provide feedback. It also gives a practical hint to include the conversation array for reproduction. No exclusions or alternatives are needed because sibling tools serve entirely different purposes.

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 provide readOnly, idempotent, and non-destructive hints, which fully cover safety expectations. The description adds no extra behavioral details (e.g., caching, errors), but given the annotations, it is sufficient.

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 redundancy. It is appropriately concise for a trivial, no-argument tool.

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 version query, the description adequately implies the return value (versions). It does not specify exact output format, but given the lack of an output schema, it provides enough context for an agent to use 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?

There are zero parameters, so schema coverage is complete. The baseline for high coverage is 3, and the description adds no parameter-specific information because none exist.

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 and specifically states the tool's function: showing current MCP platform and adapter versions. It distinguishes itself from siblings like 'toolkit_info' which might display different information.

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 tool has no parameters and is a simple query, so usage context is unambiguous. It does not explicitly mention when to use it over alternatives, but its purpose is inherently clear and self-contained.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context by specifying what the returned state contains, though it does not mention caching, freshness, or authentication prerequisites.

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 sentence, front-loaded with the action and resource, followed by a compact enumeration of returned data. Every phrase adds value and nothing is wasted.

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-argument read-only inspection tool, the description is mostly complete: it states the resource and the main output categories. It stops short of specifying the exact response structure or whether authentication is required first, but the given detail is sufficient for straightforward 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?

There are zero parameters, so the schema is trivially complete and there is no parameter meaning for the description to add. The baseline of 4 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 ('Returns') and a concrete resource ('current toolkit state'), then enumerates the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from sibling info/connection tools like show_version or authenticate.

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 'current toolkit state' gives a clear use case for status inspection, and the enumerated contents make it obvious it is the diagnostic/status tool. However, it does not explicitly contrast it with siblings such as show_version or authenticate, nor state when not to use it.

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