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

The description explains that the tool runs with the signed-in user's permissions and accesses knowledge bases accordingly, which is important for authorization awareness. It also outlines thread management behavior. Since no annotations are provided, this description carries the full burden and covers key behavioral aspects.

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 efficient and informational, with no redundant content. Each sentence adds value, from the core action to the permission context and thread handling instructions.

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

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

The description covers the essential usage context, including authorization and thread management. While the output format is not described, the presence of an output schema reduces the need to spell out return values. Overall, it is sufficiently complete for practical use.

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

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

All three parameters are explained in the description: assistant_id (how to find it), message (the question), and thread_id (optional, for continuing conversations). This fully compensates for the absence of schema-level descriptions.

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

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

The description clearly states the tool's primary function: sending a message to a Qlik Answers assistant and receiving a response. It distinguishes itself from sibling tools like qlikcloud_get and qlikcloud_delete by focusing on chat interaction.

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 provides clear guidance on how to use the tool, including the behavior of thread_id for conversation continuity. While it doesn't explicitly say 'use this instead of other tools', the context is unambiguous given the chat-specific purpose.

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 provided, the description fully carries the transparency burden. It discloses that deletion moves items to the Recycle Bin, that permanent deletion is impossible, that Spaces are blocked, and that already-recycled items are refused outright.

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

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

The description is well-structured with bullets and an IMPORTANT callout, but some phrasing is redundant (e.g., 'with exactly their permissions: you can only retire resources you are allowed to move' and the repetitive admin wording). Still, the extra detail is mostly purposeful.

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

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

The description covers the operation's side effects, limitations, required user confirmation, and unsupported cases. Since an output schema exists, omitting return-value details is acceptable, and nothing critical is missing 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?

The schema only says 'Path' with no description, so the tool description must compensate. It does so by giving an example path, listing supported path prefixes, and stating which resource types are accepted or rejected.

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 deletes a Qlik Cloud resource at a given API path, and enumerates exactly which resource types are supported, blocked, or unsupported. This distinguishes it from sibling tools like get, login, and health.

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 explicit usage guidance: tell the user what will be deleted and wait for confirmation before calling. It also explains when deletion is blocked (spaces, already-recycled items) and that no alternative deletion route exists.

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 provided, the description carries the full transparency burden and does so thoroughly: it states read-only behavior, permission-based filtering, one-page-at-a-time pagination, and the truncation indicator behavior. It also notes the user context under which requests run.

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

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

The description is well structured with clear paragraphs and an Args section, but it includes some redundant meta-commentary about naming and repeated emphasis on being the only read tool. It remains focused and readable, though slightly longer than strictly necessary.

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

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

The description covers the API surface, argument usage, pagination behavior, truncation reporting, and permissions context. Since an output schema exists, not detailing every return field is acceptable; the description provides enough context 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?

The input schema provides no parameter descriptions, but the description compensates by explaining path formats with an example, query_params with a concrete example, fetch_all semantics, and the max_pages ceiling. Each parameter gains meaning beyond the raw schema.

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

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

The description clearly states the tool reads anything from Qlik Cloud over REST and is the only read tool in this server. It explicitly differentiates from sibling tools like qlikcloud_delete and qlikcloud_login 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?

It gives explicit guidance on when to use this tool versus the official Qlik MCP Server, and explains when to set fetch_all for 'all' queries or counts versus single-record lookups. This leaves no ambiguity about tool selection or pagination use.

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

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

The description discloses what the tool reports (tenant, identity, roles, session storage, token refresh) and clarifies permission context (runs with user's own permissions, no elevated access). It does not explicitly mention side effects, but for a health check this is likely read-only and the description adequately conveys that.

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 mostly concise and well-structured, with the primary purpose and usage stated upfront. The final sentence about non-admin identity is somewhat verbose but adds valuable context about permissions, so it is acceptable.

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 provides sufficient context for a no-parameter health check: it explains what the tool does, when to run it, and what information it returns. It does not detail error handling or output schema, but these are not essential 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, so the baseline score of 4 applies. The description adds no parameter-specific information, but none is needed given the absence of parameters.

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

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

The description clearly states the tool's purpose: to check the connection and report which Qlik Cloud account is in use. It uses a specific verb ('Check') and identifies the resource (connection/account), making the tool's function unmistakable.

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 guidance on when to use the tool ('Run this first when anything looks wrong'), which is useful for an agent. It does not explicitly contrast with sibling tools, but the use case is sufficiently 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?

With no annotations provided, the description carries the full burden of disclosing side effects. It clearly states that the tool opens the user's browser, shows a consent screen, and that subsequent actions use the user's identity and permissions. It also explains the behavior of 'force' and 'switch_account', including that switch_account implies force.

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 appropriately concise while covering essential behavior. Every sentence contributes meaningful information: the core action, side effects, usage triggers, and parameter explanations. There is minimal redundancy, and the structure with an Args section improves readability.

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 login tool with two optional boolean parameters, the description is complete. It explains the action, the side effects, the conditions for use, and the meaning of both parameters. The output schema is not shown, but for a login flow the return value is secondary; the description provides enough context 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?

The JSON schema provides only names and defaults with no descriptions, so the description must compensate. The Args section explicitly explains both parameters: 'force' means sign in again even if a session exists, and 'switch_account' means re-authenticate as a different account and implies force. This fully covers the 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 clearly states the tool's function: 'Sign in to Qlik Cloud as yourself, in your browser.' It identifies the specific resource (Qlik Cloud) and the action (login), and it is obviously distinct from sibling tools like logout, health, and delete.

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

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

The description provides explicit usage conditions: 'Call this when a tool says you are not signed in, or when the user asks to sign in or switch accounts.' It also warns against speculative calls because it opens a browser window, giving clear guidance on when not to use it.

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

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

With no annotations, the description carries the full burden of revealing side effects. It explicitly states that it revokes the token, deletes the stored session, and removes access entirely, which is transparent. It lacks details about error behavior or confirmation of success, but the core effects are clearly disclosed.

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

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

The description is concise and well-structured. It starts with a one-sentence summary, then elaborates on the mechanics and implications, and finally lists the parameter with its explanation. Each sentence serves a purpose without redundancy.

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

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

The description covers the tool's action, side effects, and parameter meaning, and it references the login tool for context. It does not mention the output format (though the output schema is stated to exist but not shown), but for a logout operation, the expected outcome is straightforward. Overall, it is complete for practical use.

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

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

The schema defines all_accounts as a boolean, and the description explains its meaning: 'Also remove every other stored account for this tenant.' This adds clear semantic value beyond the schema's bare type definition.

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

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

The description clearly states the tool's purpose: 'Sign out of Qlik Cloud and remove the stored session.' It further explains the effect of revoking the token and deleting the session, making the action unambiguous.

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

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

The description provides context for when to use the tool by referencing the need to call qlikcloud_login again after logout, implying it is used after a session is no longer needed. However, it does not explicitly compare with sibling tools like qlikcloud_get or qlikcloud_delete, so guidance on when not to use it is less direct.

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