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

Annotations already supply readOnlyHint beyond which the description adds meaningful context: it returns 'raw Markdown from Jina Reader' and clarifies the tool is non-interactive (no login, click, form, or visual inspection). This disclosure exceeds the annotation and helps the agent calibrate expectations. A 4 reflects the extra value without being exhaustive.

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, zero fluff. The core purpose is front-loaded, followed by usage exclusions and a note on return format. Every sentence serves a purpose—no repetition or filler.

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 single-parameter read-only tool, the description completely covers what the agent needs: when to invoke it, what it returns, and what it is not for. No output schema is present, but the return type is disclosed. Nothing essential is missing.

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 sole parameter (url) is fully documented in the schema with a detailed description ('Exact HTTP(S) URL... pass source URLs unchanged'). Schema coverage is 100%, so the description does not need to add parameter info; the minimal restatement adds no extra meaning 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?

States a specific verb+resource: 'read, quote, summarize, or verify page text' from an exact HTTP(S) URL. It distinguishes itself from siblings web_search and x_search by clarifying it consumes their URLs, and differentiates from Browser/curl/shell by its non-interactive read-only role.

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?

Explicitly defines when to use (exact URL known, text-read task) and when not (URL discovery, need login/click/form/visual). Names alternatives (Browser, curl, shell) and states preference conditions. Provides clear routing guidance.

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?

Annotations already declare readOnlyHint=true, so the bar is lower. The description adds useful behavioral context beyond that: complementary queries may run in parallel, stopping after an authoritative source, and the tool returns the raw xAI Responses API body. This gives the agent a clear picture of execution behavior and output format without contradicting the read-only hint.

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 paragraph with five sentences, each serving a distinct purpose: usage trigger, parallel query allowance, stop condition, sibling differentiation, and follow-up. There is no fluff, and the most critical information is front-loaded. It is slightly dense but each clause 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 the tool's simplicity (one parameter), no output schema, and read-only annotation, the description covers all essential aspects: when to use, alternatives, follow-up actions, operational heuristics, and the return format. An agent can confidently invoke it correctly without additional context.

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 parameter 'query' is already well-described as 'The question or search query to investigate'. The description does not add additional syntax, formatting, or examples beyond the schema. It mentions parallel queries, but that is not specific to the parameter's meaning. Given full schema coverage, the baseline 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 clearly states the tool's purpose: discovering current information across the public web when no exact URL is known. It uses a specific verb ('discover') and resource ('public web'), and distinguishes itself from sibling tools (x_search for X-only content, web_fetch for page verification). This leaves no ambiguity about what web_search does.

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?

Explicitly states when to use the tool ('when no exact URL is known and current information must be discovered'), when not to (use x_search for X-only content), and the follow-up action (call web_fetch after finding a page to verify). It also provides operational guidance on parallel queries and stop conditions, making the decision tree fully transparent.

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?

Annotations only declare readOnlyHint=true; the description adds meaningful behavioral context beyond that: complementary queries may run in parallel, stopping/termination behavior, conditions for deepening, and the return format ('raw xAI Responses API body'). No contradiction with the read-only annotation.

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?

Five functional sentences with the primary purpose front-loaded and every sentence earning its place — scope, routing, stopping, deepening, and fetch delegation. Slightly dense but appropriate given the multiple behavioral rules it must convey.

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?

Comprehensive for a search tool covering multiple content types with parallelism, termination, and delegation rules. With no output schema present, the description still discloses the raw response body. Nothing an agent needs to invoke this correctly is missing.

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% since the query parameter is fully documented ('The question or search query to investigate'). The description adds little parameter-specific detail beyond the schema, so the baseline of 3 applies. Parallel-execution hints imply query handling but don't add syntax or format value.

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 resource (X posts, accounts, threads, replies, trends) with a clear search intent, and explicitly routes around siblings by saying 'Prefer it over web_search for X content.' An agent can distinguish x_search from web_search and web_fetch without opening schemas.

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?

Provides explicit when-to-use scope (X content), preference over web_search, a stopping condition ('Stop when the requested official post or account result is found'), a deepen-only-on-conflict rule, parallel-execution guidance, and explicit delegation to web_fetch for external pages. This is model guidance with clear exclusions.

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