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

With no annotations, the description carries the full burden. It does disclose a genuine behavioral trait — that Grok auto-selects or merges sources — which is useful routing context. However, it says nothing about permissions, rate limits, result volume, or return shape.

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?

Three short sentences with the core behavior front-loaded. There is mild redundancy between 'comprehensive results' and 'complete picture ... from social media AND web sources', but nothing that impedes comprehension.

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 three-parameter search tool with no output schema and no annotations, the description covers the source-selection behavior but omits result format, result volume, and how the date range interacts with the two sources. Adequate but with clear gaps.

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 each parameter is self-documented, so the baseline is 3. The description adds no syntax, format, or scope detail beyond the schema (e.g., it never clarifies that from_date/to_date apply only to the X half of the search).

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 and resource ('search both X and the web') and distinguishes itself from its single-source siblings (search_x, search_web_via_grok) by emphasizing 'simultaneously' and 'combine both'. It never names the siblings explicitly, but the differentiation is unambiguous.

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?

'Best for getting a complete picture of a topic from social media AND web sources' gives a positive usage cue, but there is no when-not guidance and the alternatives (search_x, search_web_via_grok) are never named as the preferred choice for single-source queries.

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 full behavioral burden. It does disclose the return shape ('summarized results from web pages') and that results are real-time, which is genuine added context, but says nothing about authentication, rate limits, cost, or freshness caveats.

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?

Three tight, front-loaded sentences with no wasted clauses; the mechanism and return format come early. 'General knowledge' is slightly filler-ish but not enough to detract.

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 read-only search tool with fully documented params and no output schema, the description covers purpose, return shape, and typical use cases. The only meaningful gap is the absence of sibling routing.

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 both query and allowed_domains are already documented with format and constraints (comma-separated, max 5). The description adds nothing about either parameter, so the baseline 3 applies.

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 (Search) and resource (the web) with mechanism (via Grok), and the 'web' scope implicitly differentiates it from the sibling search_x. It does not, however, explicitly name or distinguish itself from search_combined, which likely also touches the web.

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 sentence 'Useful for current events, documentation, news, and general knowledge' implies when the tool fits but offers no when-not guidance and no routing to search_x or search_combined. Usage is left to inference from the topic list.

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 full burden, and it does disclose something beyond the name: that results are Grok-summarized with original user quotes, which sets expectations for output shape. However, it says nothing about authentication, rate limits, result volume, or failure behavior, which are meaningful gaps for an unannotated external-API tool.

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?

Three sentences, front-loaded with the core action and corpus, then capability and output expectations. Every sentence contributes, though 'Powered by Grok's x_search' is closer to marketing context than actionable guidance.

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?

No output schema exists, and the description compensates by describing returns as summarized results with original quotes. Combined with 100% parameter coverage in the schema, an agent has enough to call it correctly; only auth/limits behavior is left unaddressed.

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 schema already documents query, date bounds, and handles. The description's line 'Supports filtering by date range and specific X handles' restates the schema rather than adding format, syntax, or limit details (the 10-handle cap lives only in the schema). Baseline 3 applies.

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 and resource ('Search X (Twitter) for real-time posts, discussions, and trends'), which is concrete and distinguishable from the sibling web-search tools by naming the X/Twitter corpus. It never names the siblings explicitly, so the differentiation is implicit rather than stated.

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 'real-time posts, discussions, and trends' implies the use case (current social sentiment/topics), but there is no explicit when-to-use or when-not guidance and no mention of search_web_via_grok or search_combined as alternatives. An agent must infer the routing decision from the corpus name alone.

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