apply_for_access替用户提交七喵空间的开通申请。必须先向用户本人要到手机号或邮箱（至少一项，不要猜、不要代填），并得到他对《隐私政策》（https://www.meowspace.cn/legal/privacy）的明确同意，再把 consent 传 true；用户没有明确同意就不要调用。提交后旗妙会联系用户；本工具不会当场开出账号。不计入试用次数。
| Name | Required | Description | Default |
|---|---|---|---|
| No | 邮箱。与 phone 至少填一项。 | ||
| phone | No | 中国大陆手机号，11 位数字。与 email 至少填一项。 | |
| consent | Yes | 用户本人是否已明确同意《隐私政策》。只有用户明确同意才传 true。 |
Changes observed during successful MCP inspections.
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.
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