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

Annotations only cover the safety profile (readOnly, openWorld, non-destructive); the description adds substantial behavior beyond them: binary bodies and text-less PDFs return errors, long bodies are windowed and continued from cache, network safety/proxy/cancellation/size limits persist through fallbacks, and it is explicitly not an authenticated browser. These are exactly the operational caveats an agent needs.

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?

Front-loaded with the core action, then dense but purposeful sentences covering return format, pagination, focus retry, error cases, and the auth boundary. No filler and no repetition of the schema or annotations.

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-value documentation is not required, and the description still covers error outcomes, extraction limitations, pagination continuation, and the unauthenticated boundary. Nothing needed to invoke it 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 description coverage is 100%, so the baseline is 3, but the description adds real semantics: offset continuation should use the cached read rather than a new request, and focus should be dropped on a miss because a miss is not evidence of absence. That goes beyond the schema's parameter descriptions without restating them.

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 first sentence gives a specific verb (read/fetch) and resource (a known HTTP(S) URL) plus a distinguishing constraint ('without searching again') that separates it from the search siblings. It also states the return shape (readable HTML or locally extracted PDF text with retrieval route). An agent can select this over fused_search or x_search without opening either schema.

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?

It clearly sets the context of use (a URL you already know, avoiding a re-search) and gives concrete recovery guidance: 'A focus miss is not evidence of absence: retry without focus.' It stops short of explicitly naming the search siblings as the alternative when the URL is unknown, so routing is implied rather than spelled out.

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 cover the safety profile (readOnlyHint, openWorldHint, non-destructive), and the description adds substantial behavior beyond them: returns ranked extracts plus source attribution and execution diagnostics including failures/warnings, scores do not verify claims, agreement across engines is not independent corroboration, request-local choices do not alter persistent defaults, and disabled engines are skipped with warnings.

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?

Front-loaded with the primary use case and the routing decision, and most sentences carry distinct information. However, it runs long and contains mild redundancy, e.g. 'do not delay research or require Jev setup' restates the preceding clause and 'choose by the evidence need' restates the routing rule already given.

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 14-parameter tool with nested objects, enums, and an output schema, the description covers routing, fallbacks, parameter defaults, return contents, and caveats about interpreting results. Nothing an agent needs to invoke it 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%, so the baseline is 3. The description still adds non-obvious meaning: engines should normally be omitted, request-local selections are not persisted, community adds X voices and shares the final max_results budget, and engine_pool takes precedence over the deprecated layer alias.

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 ('general-purpose multi-engine search') and explicitly distinguishes itself from siblings: x_search for X-only tasks, fetch_page for reading decisive sources, and adaptive_search for intent-guided evidence selection. An agent can route between these without opening a schema.

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?

Explicit when-to-use ('vast majority of public-web research tasks', 'direct retrieval, varied query angles or explicit source control'), explicit when-to-prefer-the-alternative (adaptive_search for medium-to-high difficulty or noisy results), and explicit fallback behavior if Jev is unavailable. The selection criterion is stated as a principle ('choose by the evidence need') rather than left to inference.

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 provide readOnlyHint=false and destructiveHint=false, but the description adds critical behavioral context: layer=show causes no change, while free/api persist a new default and require authorization. It also discloses the compatibility mapping (legacy api maps to hybrid, not strict api pool), which goes beyond the structured fields.

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 dense but mostly earns its length, with the default behavior and key warning front-loaded. The 'free = free' and 'api = api' phrasing is slightly redundant and could be tightened, but it remains efficient and readable.

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 tool with one optional parameter, full schema coverage, and no output schema, the description covers all essential context: default behavior, persistence side effects, authorization requirement, engine_pool mapping, and the alternative tool for single searches. Nothing an agent needs to call it 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%, but the description adds meaning beyond the enum descriptions by explaining the engine_pool implications of each value: free maps to engine_pool=free (keyless), api maps to engine_pool=hybrid, and legacy api does not map to the strict api pool. This is valuable semantic nuance that the schema alone does not convey.

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 names a specific resource (the search layer) and a clear action set: inspect with layer=show or persist a new default with free/api. It also explicitly differentiates this tool from fused_search, making its purpose and scope 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?

The description gives explicit when-to-use guidance: use layer=show to inspect, only change the default when authorized, and for a single search use fused_search.engine_pool instead. This routes the agent to the correct sibling in the exact condition that matters.

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 cover the safety profile (readOnlyHint=true, destructiveHint=false), so the bar is lower. The description adds genuine value beyond them: it discloses the diagnostic surfaces returned and warns that empty results do not authorize changing credentials, permissions, or defaults — a meaningful behavioral caveat for an agent acting on ambiguous results.

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?

Two front-loaded sentences: the first defines scope, the second carries the caution. No filler, though the second sentence packs three distinct warnings and is slightly dense.

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 need not be described. With zero parameters and annotations covering the safety profile, the description supplies everything an agent needs to call this correctly, including the caveat about interpreting empty results.

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 tool takes zero parameters, so there is nothing for the description to disambiguate. Baseline of 4 applies; the description neither helps nor hurts parameter understanding.

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 names a concrete resource and enumerates what it exposes: cache activity, engine configuration readiness, and recent searches. It clearly reads as a diagnostics tool, distinct from the search/retrieval siblings (fused_search, fetch_page, search_layer), though it never names an alternative explicitly.

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?

It gives interpretive guidance ('inspect result warnings', 'empty results do not prove absence') but never states when to call this tool versus the search siblings or when not to. Usage is implied by the diagnostics framing rather than spelled out.

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 cover readOnly/openWorld/no-destructive, and the description adds substantial context: credential-free vs authenticated coverage, that results include source attribution and diagnostics, that author/date filters require verifiable metadata and unverified candidates are dropped, and that coverage may be incomplete, stale or empty. It even warns that a sample does not establish platform-wide sentiment. This is exactly the kind of behavior disclosure annotations cannot supply.

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?

Six compact sentences, each carrying distinct information (capability, auth, output, filter constraint, coverage limits, interpretation caveat). Front-loaded with the core capability and free of filler, though the telegraphic style gives it a slightly dense, checklist feel.

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 an output schema present, the description needn't explain return values, and it correctly focuses on credentials, filter constraints and coverage limitations. For a 9-parameter, open-world search tool it covers what an agent needs to call it responsibly, though it never clarifies the division of labor with the sibling search tools.

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 parameter baseline is 3. The description earns above baseline by adding a behavioral constraint on the filter parameters: author/date filters require verifiable metadata and unverified candidates are omitted, which tells the agent those parameters may silently narrow results. It still doesn't add syntax or format detail beyond the schema.

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 and resource ('Find X/Twitter posts, account material or available thread content'), so an agent immediately knows the domain and operation. It does not, however, distinguish this tool from siblings like fused_search or search_layer, leaving the agent to infer the boundary. Clear but not differentiating.

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?

Usage context is implied ('Credential-free retrieval is supported; configured authentication can improve coverage') and caveats are given for when filters work, but there is no explicit when-to-use guidance relative to the sibling search tools. The mode selection (keyword/semantic/user/thread) is left entirely to the schema. Adequate but with a clear gap in routing guidance.

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