netcafe-tasks

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

Annotations already declare readOnlyHint=true and idempotentHint=true, and the description adds meaningful context: it performs a live fetch from a real China egress, reports specific metrics, and frames the result as a measurement rather than a guess. No contradictions with annotations. It does not mention rate limits or failure behavior, but annotations cover safety.

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, front-loaded with the action verb, and every word earns its place. No redundancy or filler.

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

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

The tool is simple (1 parameter, output schema provided). The description fully explains the tool's purpose, the measurement approach, and the key limitation of alternatives. Return values are already covered by the output schema, so no further detail is needed.

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 the 'url' parameter described as 'Full URL to test, e.g. https://example.com'. The description restates the URL-fetching concept but doesn't add new parameter-level detail or format constraints beyond the schema. Baseline 3 is appropriate.

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

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

The description clearly states a specific action ('Fetch a URL from a real mainland-China network egress') and the resource/scope ('URL reachability from China'), with measurable outputs (HTTP status, latency, DNS resolution). This distinguishes it from all sibling tools, which are unrelated to network testing.

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 clarifies when to use the tool: to answer 'is my site/API usable from China?' and explicitly notes that a VPS abroad cannot provide this measurement. While it doesn't name a specific alternative tool, it gives strong contextual guidance and an implicit exclusion.

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 only give the generic mutation profile (readOnly=false, destructive=false, idempotent=false), while the description adds high-value behavior: it runs server-side with no client process, it stays silent unless the result actually changes, it requires a workspace token (?w=ws_...) for later management, and costs/capacity limits apply. These auth, notification, and cost traits go well beyond 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?

Purpose and the no-hosting constraint are front-loaded, then kinds are listed efficiently in a single inline enumeration. It is dense but every clause carries information; the beta pricing/capacity sentence is the softest, though still relevant to invocation expectations.

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 an output schema present, return values need not be described, and the description covers what remains: scheduling semantics, the four kinds, notification-on-change behavior, the workspace-token prerequisite, and cost posture. An agent has everything needed to pick a kind and invoke the tool correctly.

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

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

Schema coverage is 100% and the schema already documents notify_url and interval_seconds with their defaults, so the baseline is 3. The description adds genuine value by explaining what each kind consumes as 'input' (URL to watch vs question to re-research) and what kind selection implies, which the bare string-typed kind field does not convey.

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+resource ('Create a task that runs on a schedule in our cloud'), clarifies hosting responsibility ('you do not keep anything running'), and enumerates four distinct kinds with one-line explanations. This clearly separates it from siblings like list_tasks, get_task_runs, and delete_task, which operate on already-created tasks.

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 kind enumeration effectively tells the agent when each mode applies (watch_page vs daily_answer vs watch_reachability vs pipeline), including the cross-reference to create_pipeline for the pipeline kind. However, it never explicitly states when not to use this tool or routes to sibling tools for viewing/managing tasks, so it stops short of full when/when-not 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 indicate destructive and idempotent behavior, but the description adds useful context: it also removes run history and stops the task, implying termination of active runs. 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, direct sentence that immediately conveys the action and scope. No wasted words.

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

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

For a simple delete tool with one parameter, output schema, and annotations covering safety, the description is complete. It explains the action and the additional effect on run history, leaving no critical gaps.

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

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

Schema coverage is 100% with task_id described as 'From list_tasks.' The description adds no additional parameter meaning, so the baseline of 3 applies.

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

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

The description clearly states the verb 'remove' and the resource 'scheduled task', and further specifies scope by mentioning 'run history'. This distinguishes it from siblings like create_task and list_tasks.

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 explicit when-to-use or alternative guidance is provided. The description implies usage for stopping and removing a task, but does not state exclusions or reference sibling tools. The schema hint 'From list_tasks' is a minor prerequisite hint, but the description itself lacks usage 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds billing context ('User charge is $0.00') and hints at result-change detection, which is genuine extra information, but it does not describe pagination, ordering, or retention limits on run history.

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 tight sentences with the core payload described first and the cost note last; nothing is padded. The cost sentence is slightly tangential but still useful information for the caller.

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 an output schema present, the description need not explain return structure, and it correctly focuses on purpose. Annotations cover safety and the schema covers parameters, leaving only minor gaps around run ordering, retention, and when to prefer list_tasks.

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%: both limit (max 20, default 5) and task_id (source tools named) are documented in the schema itself. The description adds no parameter detail, so the 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 names a specific resource ('recent runs of one scheduled task') and enumerates what each run yields (return value, change status, cost metadata), which clearly separates it from list_tasks and create_task. It stops short of explicitly naming the sibling it is not, so it is clear but not fully differentiated.

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: call this to inspect a task's run history. There is no explicit when-to-use statement, no mention of prerequisites (a valid task_id), and no exclusion or alternative such as list_tasks for enumerating tasks.

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, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds useful context about the response contents (next run times, run counts, platform cost) and a beta pricing note, but discloses nothing about pagination, ordering, or limits.

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 core listing behavior front-loaded. The beta pricing sentence is arguably extraneous to tool selection but is brief and does convey cost-relevant context.

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

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

For a zero-parameter, read-only list tool with an output schema and full annotation coverage, the definition supplies enough to call it correctly. It need not describe return structure since an output schema exists.

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 takes zero parameters, so per the rubric the baseline is 4. There is nothing for the description to disambiguate, and it does not introduce confusion about inputs.

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 ('Show scheduled tasks') and even enumerates the returned facets (next run times, run counts, cost metadata). It does not, however, distinguish itself from the sibling get_task_runs, which an agent could plausibly confuse with a task-listing 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?

There is no statement of when to use this tool versus get_task_runs (run history) or create_task/delete_task. The listing intent is inferable from the name, but no explicit context, prerequisites, or alternatives are given.

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, idempotentHint, and destructiveHint. The description adds valuable behavioral traits not visible in annotations: deterministic, calls no model, costs nothing, and never runs out of quota. 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?

Four dense sentences, front-loaded with the core purpose in the first sentence and supported by recipes, cost/quota guarantees, and when-to-use guidance. Every sentence earns its place; no filler or repetition.

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 the simple context (single required string parameter, rich annotations, and an output schema), the description is complete. It covers the tool's behavior, return value highlights, performance/cost characteristics, and usage context without leaving important gaps.

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

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

The input schema already describes the 'task' parameter with examples, and schema coverage is 100%. The description adds the nuance 'plain language (any language)' and emphasizes that example calls are generated, providing modest additional 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 clearly states the tool's purpose with a specific verb+resource: describe a task and get back exactly which tools on the server do it, with ready-to-run example calls. It explicitly distinguishes itself from sibling tools by positioning itself as the meta-guide that prevents 'reading the whole catalogue and guessing.'

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?

Provides explicit when-to-use guidance: 'Call this FIRST when you are not sure what this server offers.' It also clarifies the intended use case (plain-language task discovery) and contrasts with the alternative of scanning the catalogue manually, which is sufficient for a meta-tool.

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