nexscope_seo_model_answer_observationSingle fixed model answer observation with no web search and at most512 output tokens. Nullable fields preserve missing evidence. Provider observations and estimates do not establish actual account performance. No additional calls or fallback.
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | Trim/NFC; Unicode code point limit500; newline and tab allowed. No tools/history/web options. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnly, non-destructive, openWorld), but the description adds real behavioral context beyond them: a hard 512-token output cap, no tools/history/web access, nullable fields that preserve missing evidence, and no fallback or retry. That last point is valuable because it warns the agent that a thin result is final, not retriable.
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 short sentences with no filler, but structure is weak: the typo 'at most512' and the boilerplate 'Provider observations and estimates do not establish actual account performance' obscure the front-loaded takeaway rather than sharpen it.
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 must convey the return shape, and it only gestures at it via 'nullable fields preserve missing evidence' without saying what an observation contains. The constraints (token cap, no search, no fallback) are complete, but what the agent receives remains under-specified.
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?
Single parameter with 100% schema description coverage that already documents trimming, NFC, the 500 code-point limit, and newline/tab allowance, so the schema carries the load. The description only echoes 'no web search' and adds no prompt semantics 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?
It signals the tool produces a 'single fixed model answer observation' with no web search and a 512-token cap, which hints at an SEO/AI-answer observation call. But 'observation' is an opaque output noun; the description never states what is actually produced or returned, and it names no sibling it differs from among the many SEO tools.
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 guidance and no alternative named, despite close-sounding siblings such as nexscope_google_ai_mode_search or nexscope_seo_ai_search_citation_sample. The 'no additional calls or fallback' note is a constraint on the call, not guidance on selecting this tool over another.
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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