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

With no annotations provided, the description bears the full transparency burden. It discloses the dependency on a prior snapshot/diff and defines the output as a unique CSS selector. It does not cover failure modes or exact return type, but these are minor for a simple conversion 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?

The description is a single sentence that leads with the core action and resource, then provides the prerequisite. Every word is necessary and there is no redundant information.

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 tool with no output schema, it is mostly complete: it states what is returned, the required prior step, and the automation use case. The main gap is that it doesn't mention the return format (e.g., string) or error behavior, but these are not critical for the tool's intended use.

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%; the only parameter 'uid' is already described as 'Stable uid from the snapshot output.' The tool description merely reinforces 'snapshot uid' without adding new meaning, so it stays at the baseline of 3 with no additional semantic contribution.

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 uses a specific verb 'Return' and clearly defines the resource: a unique CSS selector for a snapshot uid. It also names the intended downstream use (chrome-devtools-mcp click/fill), which distinguishes it from sibling tools like get_node or snapshot_index that likely return node data rather than selectors.

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 explicitly states a precondition (requires smart_snapshot or snapshot_diff first) and identifies the use case (for click/fill). It does not explicitly name alternatives or exclusions, but the context makes it clear when to use this tool, which is adequate for this utility.

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?

No annotations are provided, so the description carries full burden. It discloses that it returns specific node data and requires a prior snapshot, but it does not mention error behavior (e.g., invalid uid) or explicitly state that it has no side effects.

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?

One sentence that front-loads the action and outputs, with no filler. Every clause adds value, and the prerequisite is clearly stated.

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?

Simple tool with one parameter and no output schema. Description covers purpose, exact return items, and prerequisite. It lacks error/no-result behavior, but given the simplicity, this is adequate and fits well within the snapshot workflow indicated by siblings.

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?

Input schema has 100% coverage with 'Stable uid from the snapshot output.' The tool description reinforces this by saying 'one snapshot uid' and 'Requires prior smart_snapshot or snapshot_diff,' but adds no new syntax or format details. Baseline 3 for full schema coverage.

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 uses the specific verb 'Return' and enumerates exact outputs (role, path, DOM geometry, CSS selector) for a single snapshot uid. This clearly distinguishes it from siblings like smart_snapshot or snapshot_diff which create snapshots/diffs.

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 explicitly states a prerequisite: 'Requires a prior smart_snapshot or snapshot_diff.' This gives clear context for when the tool can be used, but it does not mention alternatives or exclusion cases.

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?

No annotations are provided, so the description carries the transparency burden. It discloses the tool reads the most recent snapshot and returns specific fields (role, name, path), and explains the dependency on prior calls. However, it doesn't explicitly state side-effect safety (though 'search' implies read-only) or behavior when no snapshot exists.

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, each serving a purpose: stating the action and target, describing return fields, and giving a prerequisite. No redundant information 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?

The description covers the tool's purpose, dependency, and return shape, which is especially useful given there is no output schema. It lacks error-case handling, but for a simple search tool with well-documented parameters, it is sufficiently 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 already provides full descriptions for both parameters (100% coverage), so the description doesn't need to add parameter details. It neither repeats nor contradicts the schema, but adds no extra semantic value 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 uses a specific verb ('Search') and resource ('most recent smart_snapshot tree'), making the tool's function clear. It distinguishes itself from sibling tools like snapshot_index or get_node by focusing on keyword search over a snapshot.

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 explicitly states to call smart_snapshot or snapshot_diff first, establishing a clear prerequisite and usage order. It does not name alternative tools for other scenarios, but the guidance is sufficient for when to use this tool.

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?

No annotations are provided, so the description carries the transparency burden. It lists the reported data but omits side effects (e.g., clearing diagnostic buffers when 'clear' is true) and does not define the scope of 'recent' errors. This is a moderate level of disclosure.

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, direct sentence that front-loads the action ('Report') and concisely lists all included data. No redundant words 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?

The description lists the data categories but does not specify the output format or the structure of error/exception details. With no output schema and no annotations, this creates ambiguity about the return value, making the description only partially 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 single parameter 'clear' is fully documented in the schema with a clear explanation (100% coverage). The description adds no additional parameter semantics, so the baseline score of 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?

The description clearly identifies the tool's purpose with a specific verb ('Report') and enumerates exact data points (URL, title, readyState, loading flag, console errors, exceptions, network requests). This distinguishes it from sibling snapshot/search tools, which focus on DOM or visual state.

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 alternatives or how it fits into a workflow. It simply states what it reports, leaving the agent to infer use cases.

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 mentions saving to disk and returning a file path, which is core behavior, but does not cover potential side effects (e.g., disk cleanup, overwriting, permissions) or error conditions. The token-saving benefit is useful context but not a behavioral trait in the safety sense.

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 exactly two sentences. The first sentence states the primary purpose, and the second adds a practical benefit and follow-up action. It is front-loaded, efficient, and contains no irrelevant information.

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 simple tool with 4 optional parameters and no output schema, the description covers the main outcome (saves to disk, returns path) and gives a key optimization tip. It lacks explicit differentiation from sibling tools and does not address potential errors or edge cases, but the core functionality is adequately described.

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 baseline is 3. The description does not elaborate on parameter specifics, but it implies the tool produces a screenshot file; the schema already documents all parameters (format, quality, fullPage, directory) with individual descriptions. No additional semantic value is added.

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 action ('Takes a screenshot, saves it to disk, and returns the file path') with a specific verb and resource. It does not explicitly mention sibling tools, but the focus on saving to disk and returning a file path differentiates it from common alternative approaches like returning base64.

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 usage context by highlighting token savings ('Saves ~3000-5000 tokens per screenshot compared to returning base64') and instructs how to inspect the file ('Read the file with read_file if you need to inspect it'). It gives an implicit alternative (returning base64) but does not explicitly name or exclude sibling tools.

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 burden of behavioral disclosure. It transparently explains the filtering criteria (visible, interactive, meaningful), depth limiting, and deduplication behavior. It does not explicitly state whether the tool is read-only, but as a 'snapshot' this is implied. The inclusion of includeHidden and verbose parameters further clarifies default behavior, which the schema mirrors.

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 only two sentences and front-loads the primary action and outcome. Every piece of information is useful: what the tool returns, its key behaviors (filtering, depth limiting, deduplication), and when to use it. No fluff or repetition.

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 moderate complexity (3 optional params, no output schema), the description fully captures the purpose, filtering behavior, and usage guidance. It also points to take_snapshot as the alternative, which aids selection. The lack of output schema is compensated by the description of what the snapshot consists of ('nodes'). The tool is well understood from this alone.

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?

All three parameters are fully described in the schema (100% coverage), so the baseline is 3. The description adds semantic context by framing the tool as 'token-efficient' and 'semantic', which explains the purpose of verbose (disabled by default to save tokens) and maxDepth (limit depth to avoid huge dumps). This layer of meaning goes beyond the individual parameter comments.

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 returns a token-efficient semantic snapshot of the current page, filtering to visible/interactive/meaningful nodes with depth limiting and deduplication. This specific verb+resource+output distinguishes it from the sibling tools (snapshot_diff, screenshot_to_disk) and explicitly contrasts with take_snapshot.

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 second sentence 'Use this instead of take_snapshot to save context' gives an explicit, actionable usage directive. This directly tells the agent when to choose this tool over an alternative, satisfying the dimension fully.

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 disclosure. It describes the diff-only output, adds context about added/removed/changed nodes, and mentions token efficiency. It does not mention error handling for missing previous snapshot, but the dependency is implied.

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 sentences, front-loaded with the core purpose and followed by a usage tip. Every word earns its place, with no redundancy.

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 three optional parameters and no output schema, the description adequately explains purpose, usage, and return type. It lacks explicit failure behavior if no previous snapshot exists, but overall is sufficient for selection and invocation.

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 descriptions cover all three parameters, referencing smart_snapshot, giving 100% coverage. The tool description adds no extra detail about verbose, maxDepth, or includeHidden, so it meets the baseline for high schema coverage.

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 it returns only changes between the current page state and the previous smart_snapshot call, which is a specific verb and resource. This distinguishes it from sibling tools like smart_snapshot (full snapshot) and page_status.

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 explicitly instructs to use this tool on every step after the first to minimize token consumption, implying the first step should use smart_snapshot. This provides clear when-to-use guidance and names the alternative.

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?

No annotations are provided, so the description carries full burden. It discloses the dependency on prior snapshot creation and the columns returned, but does not explicitly state read-only behavior, return format, or potential side effects. The prerequisite and column detail add some value beyond a bare list.

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 sentences, front-loaded with the action and resource. The first sentence defines the output, and the second gives usage and prerequisites. No redundant or filler content; every sentence 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 low complexity (one optional parameter, no output schema), the description adequately covers purpose, columns, usage context, and a prerequisite. It does not explicitly describe the return format, but for a simple uid listing this is largely self-evident and the dependency guidance provides essential 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% for the single parameter maxResults, which includes description, default, min, and max. The description adds no additional information about this parameter, so the schema already does the heavy lifting, resulting in the baseline score of 3.

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?

Description states 'List uids from the most recent snapshot' with specific columns (role, name, path), clearly identifying the resource and action. It distinguishes itself from siblings like snapshot_diff and page_search by focusing on uid listing from a snapshot.

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 usage context ('Useful before page_search or get_node') and a prerequisite ('Requires smart_snapshot or snapshot_diff first'). However, it does not mention when not to use or name alternatives, so it falls short of a 5.

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