GoAI Moat Social Media Content Strategy

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does describe the output content (pillars, hooks, CTAs, tags, reminders) which is the core behavior, but it does not disclose side effects, whether this is a pure generation operation, or any limitations. The existence of an output schema relieves it of explaining the return format. Adequate 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?

A single dense sentence, front-loaded with the main purpose (generate rolling calendar) followed by compact specifics. Every clause earns its place: pillar rotation, per-item hook/CTA/tag, and reminder inclusion. 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?

For a generation tool with 100% schema coverage and an output schema present, the description plus structured data is fairly complete. It explains what the calendar contains and the schema documents all five parameters with defaults and bounds. The only missing piece is usage routing, which is scored separately under usage guidelines.

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%, so the baseline is 3. The description references the domain concept of '七大选题支柱' (seven topic pillars) which could inform the category parameter, but it never explicitly ties description content to any parameter. It adds no syntax or format details beyond what the schema already documents.

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 ('生成一个滚动内容日历' – generate a rolling content calendar) and enumerates exactly what it produces: seven topic pillar rotation, hook/CTA/tag suggestions, and sales event reminders. This clearly distinguishes it from siblings hook_framework and platform_playbook, which focus on single dimensions (hooks, platform playbooks) rather than a full calendar.

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 zero guidance on when to use this tool versus alternatives. No mention of prerequisites, exclusions, or how it relates to the sibling tools hook_framework and platform_playbook. An agent must infer the boundary between generating a calendar and using the hook or platform playbook tools.

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?

No annotations are provided, so the description carries the behavioral disclosure burden. It does communicate that the tool returns generated text artifacts and implies a non-mutating operation, but it does not describe how the parameters influence the output, any operational constraints, or whether external state changes occur. Minimal but not absent.

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 one compact sentence that front-loads the return value and then states the use case. Every phrase earns its place, and there is no filler or redundant repetition of the title.

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 low complexity, clear parameter schema, and presence of an output schema, the description is largely complete for invoking the tool correctly. It lacks explicit guidance on when to prefer this tool over siblings, but the sibling names are distinct and the usage context is clear.

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%, so the baseline is 3. The schema already explains product_angle and audience clearly with concrete examples; the description adds no additional parameter insight, which is acceptable because the schema does the heavy lifting.

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 ('返回' / returns), a concrete resource ('短视频钩子框架库 + 黄金 5 段分镜脚本骨架'), and the exact purpose: writing scripts that retain viewers in the first 3 seconds. This clearly differentiates it from sibling tools like build_content_calendar and platform_playbook.

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 a clear use context: '用于写出前 3 秒留人的脚本' (for writing scripts that hook viewers in the first 3 seconds). It does not explicitly name alternatives or state when not to use this tool, so it stops short of a full 5.

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 behavioral burden. It implies a read-only retrieval operation via '返回' and lists what the returned playbook covers, but it does not disclose edge cases such as unsupported platform handling or whether the output is deterministic. There is no annotation contradiction, but no deeper behavioral context is added.

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 sentence that front-loads the main resource and then uses a colon-delimited list to enumerate the playbook contents. There is no redundancy with the schema and every element earns its place.

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 only two parameters, full schema coverage, and the presence of an output schema, the description is largely sufficient for an agent to invoke the tool correctly. The main missing element is explicit guidance about when to choose this tool over its siblings.

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%, and the schema already documents both parameters, including the default platform and an example for category. The description adds no extra parameter semantics, so the baseline score of 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 uses a specific verb (返回) and a specific resource (single-platform content strategy playbook), and enumerates its contents: algorithm preferences, formats, duration, posting frequency, hooks, CTA, tags, and taboos. This clearly distinguishes it from sibling tools like build_content_calendar and hook_framework, which are narrower in scope.

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 '单个平台' makes the input scope clear, and the tool is obviously intended for retrieving a per-platform strategy playbook. However, it does not explicitly name sibling tools or state when not to use them, so it falls just short of full explicit routing.

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