GoAI Moat Competitor AI Signals

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

No annotations exist, so the description carries the full burden, and it delivers meaningful behavioral context: tone guidance ('先给价值、不吓唬' – lead with value, don't scare) and an integrity constraint ('未观察项不虚构' – never fabricate unobserved items). These go beyond the basic purpose and genuinely shape agent expectations. It doesn't address side effects or auth, but for a pure generation tool these are largely moot, so the disclosed traits justify a 4.

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 two dense sentences with no filler: purpose is front-loaded, and tone, length, and the non-fabrication constraint are packed efficiently into the tail. It earns its length, though it's not maximally compact since it carries a quote/title that adds a little cultural flavor without extra instruction.

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?

An output schema exists, so return values are covered structurally and need no description. The description covers product, length, tone, and integrity, which is reasonable for a 2-parameter tool. The main gap is operational context: no guidance on sequencing relative to siblings or what a prepared 'signals' input should look like, leaving completeness slightly short of what an agent navigating three related tools needs.

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 'competitor' and 'signals' are documented in the schema, so the baseline is 3. The description does add a modest cross-reference that the signals format matches score_tsi, which helps the agent prepare valid input, but it contributes no additional syntax or value semantics beyond that, keeping it at the baseline.

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: it generates a custom brief framework ('生成...定制简报框架') for a named publication and returns a 4-6 page structural skeleton with factual statements of observed signals. This clearly identifies what the tool produces and its scope. It doesn't explicitly differentiate from siblings (get_signal_framework, score_tsi), though the format reference to score_tsi hints at the relationship, so it stops short of a 5.

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 when-to-use or when-not-to-use guidance is given, and no alternatives are named. The description never tells the agent that signals must be gathered/scored first (e.g., via score_tsi) or how this tool relates to get_signal_framework. The '格式同 score_tsi' note implies a prerequisite but leaves it implicit; an agent gets no explicit trigger conditions or sequencing.

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 behavioral disclosure burden. It adds useful context by noting the tool is 'free' and that it returns the complete framework, but it does not explicitly mention read-only behavior, permissions, side effects, or any guarantees beyond the output contents.

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, front-loaded sentence that delivers the essential purpose and one key trait ('free') with no redundancy. It is highly concise and well-structured.

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 tool with an output schema, the description covers the core purpose and the contents of the returned framework. The 'free' note adds practical context. However, it omits any usage conditions or timing guidance, so it is not fully complete.

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 has zero parameters, so the baseline is 4. No parameter-specific information is needed, and the description does not attempt to add any, which 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 ('returns the complete framework') and resource ('seven types of public signals'), listing the concrete components (signal, data source, meaning, weight, detection method). It does not explicitly differentiate from sibling tools, so it falls short of a 5.

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 no guidance on when to use this tool versus the siblings generate_brief or score_tsi. It only states what it does, leaving the agent to infer usage context without any exclusions or conditional routing.

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 burden of behavioral disclosure. It does explain that signals can be provided in list or dict form and that statuses must be observed/unobserved/unknown, which adds useful context. However, it does not explicitly state whether the operation is read-only, whether there are side effects, or how validation errors are handled.

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 compact and front-loaded, opening with the core purpose and then immediately providing the input format details. Both sentences earn their place, and the examples improve clarity without unnecessary verbosity.

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 input format and general purpose, and an output schema exists. However, it references '七类信号' without enumerating those seven categories, leaving an agent to guess the exact expected signal IDs. It also does not point to get_signal_framework as a way to obtain the framework, which would make the tool fully callable.

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%, but the description adds significant value by specifying the exact accepted formats for signals (list[dict] or dict), showing concrete examples, and enumerating the allowed status values. This goes well beyond the schema's minimal '七类信号观测结果（见上）'.

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 ('算 TSI 转型活跃度指数并分级') and a clear resource ('一家企业'). It is easily distinguished from siblings such as generate_brief and get_signal_framework, which serve different purposes.

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 implies usage when an enterprise's TSI score and grade are needed, but it does not explicitly state when to use this tool versus the sibling tools or mention any prerequisites, such as first retrieving the signal framework. The context is clear but not fully articulated.

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