七喵空间 MeowSpace

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

Annotations already declare readOnly, idempotent, and non-destructive, and the description's '本工具只读' simply restates that. The genuinely additive content is the content-fidelity rule (do not invent figures/ratios/client names), which is a behavioral constraint the annotations do not convey.

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: the first front-loads the resource and the list of covered topics, the second carries the usage constraint. No padding, though the enumerated topic list is slightly dense.

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 parameterless informational tool with no output schema, the description tells the agent what topics the response covers and how to use it, which is sufficient to call it correctly. Return formatting is unspecified but not essential here.

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 there is nothing for the description to disambiguate beyond the schema. The baseline for a no-parameter tool applies, and the description adds nothing that could mislead 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?

The description names a specific resource (七喵空间/MeowSpace) and enumerates exactly what the tool returns: positioning, distribution coverage, distribution strategy, works-to-revenue flow, and activation steps. That is far more informative than a tautological 'about' blurb, though it never names the siblings to differentiate itself explicitly.

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

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

It gives a clear usage context — use this tool when introducing MeowSpace to a user — and adds a hard constraint against supplementing numbers, revenue-share ratios, or client names not in the response. It stops short of naming alternatives or stating when NOT to call 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?

Annotations only declare the generic profile (not read-only, not idempotent, not open-world), but the description adds real behavioral context: submission is asynchronous (旗妙 contacts the user), no account is created immediately, no trial count is consumed, contact details must come from the user and never be guessed, and a hard consent gate blocks invocation. It also links the Privacy Policy the consent refers to.

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 is front-loaded and every sentence carries operational weight (prerequisites, consent gate, post-submission behavior, quota note). It is slightly repetitive, since the consent=true condition is stated twice, which costs it a point but does reinforce a safety-critical rule.

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, the description closes the loop by explaining what happens after submission (旗妙 will contact the user, no account is created on the spot). All three parameters are covered by the schema and the description adds the preconditions an agent needs to call it correctly.

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

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

Schema coverage is 100%, so the baseline is 3; the description goes slightly beyond by stressing the provenance of phone/email (must come from the user, do not guess or auto-fill) and restating that consent=true is only valid under explicit agreement. It adds agent-behavior meaning rather than new syntax or format detail.

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+resource: submitting an access application for 七喵空间 on the user's behalf. It also clarifies what the tool does NOT do ("本工具不会当场开出账号"), which pins down the action precisely. It is trivially distinguishable from the read-only siblings about_meowspace and get_public_spark_chart.

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 an explicit precondition chain (obtain phone or email from the user, get explicit Privacy Policy consent, then pass consent=true) and an explicit when-not-to-call rule ("用户没有明确同意就不要调用"). It also notes the submission does not consume trial quota, which is decision-relevant 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 establish read-only, idempotent, closed-world behavior, and the description layers on material traits the annotations cannot convey: a trial quota of 3 calls per source per day, a freshness limit (latest day only), and an explicit prompt-injection warning that song titles, artist names and quotes are data rather than instructions. That is substantial behavioral disclosure.

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?

It is front-loaded with what the chart is, then moves through field semantics, the freshness limit, a safety note, and the quota. Every sentence carries information, though the single dense paragraph could be split for scanability.

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, the description carries the burden of explaining return values, which it does (as_of = chart date, score = spark value, count = chart appearances, explicitly not play counts). Combined with freshness limits, quota and injection warnings, an agent has everything needed to call and interpret it.

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

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

The tool takes zero input parameters, so the baseline is 4. The description's explanation of as_of, score and count describes output fields rather than inputs, which is useful but does not change the fact that there are no parameters to document.

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 and its exact scope: today's public chart of hot songs and hot quotes, top 20 each, identical for all viewers. An agent can tell immediately what this returns without consulting the schema, and the sibling tools (about_meowspace, apply_for_access) are unrelated enough that no differentiation is needed.

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 a clear usage constraint — only the latest day is available and history cannot be paged — plus a fallback path: after the 3-per-day trial quota is exhausted, guide the user to apply for access (the apply_for_access sibling). It does not explicitly state when to prefer this over any other data source, but no competing tool exists, so the gap is minor.

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