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

Beyond the annotations, the description discloses a meaningful side effect (uncertain pauses the session) and a non-effect (never a send receipt). It does not cover auth, reversibility, or error behavior, but annotations already cover the destructive/read-only profile.

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 short sentences carry all essential information with no filler. The outcome values are front-loaded, followed by the important side effect and the exclusion.

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 three-parameter tool, the description covers purpose, valid inputs, a key side effect, and what it does not do. It does not describe the response or prerequisites, but the tool is straightforward and the missing details are unlikely to block correct 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?

The description adds semantic value for the outcome parameter by listing the only valid values. However, session_id and observation_id are left entirely to their schema titles, and the meanings of the outcome values themselves are not explained. With 0% schema coverage, this is partial compensation only.

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 ('Acknowledge') and resource ('client review') and enumerates the four outcomes, so it's clear what the tool does. It also clarifies that this is not a send receipt, which helps separate it from preview/reply actions, though it does not explicitly contrast any sibling tool by name.

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 clear context for when to use the tool: acknowledging client review with one of four outcomes. The warning that 'uncertain pauses the session' and that it 'never [is] a send receipt' provide some when-not guidance, but no sibling alternative is explicitly named.

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=false and destructiveHint=false, so the description is not solely responsible for safety disclosure. It adds useful context by stating the change affects a 'synthetic image' and does not access WeChat, which clarifies the non-real-world impact. However, it does not explain return values, side effects, or prerequisites, which is acceptable given the demo scope.

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?

A single sentence that communicates the demo-only nature, the action, the resource, and a key constraint (no WeChat access). Every word earns its place; the structure is front-loaded with the most important qualifier ('DEMO ONLY').

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 zero-parameter, no-output-schema demo tool, the description is sufficiently complete to allow an agent to understand its purpose and scope. It lacks details like expected outcome or call sequence, but given its simplicity and demo purpose, these omissions are minor.

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 has zero parameters with 100% schema description coverage, so the description need not document parameters. Per the baseline for 0-parameter tools, a score of 4 is appropriate; the description's mention of 'synthetic image' provides semantic context for the operation, which is more than the empty schema offers.

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 a specific action ('change the synthetic image') and resource ('synthetic image'), with an explicit scope ('without accessing WeChat'). The 'DEMO ONLY' prefix signals its demo nature, distinguishing it from the observation and status sibling tools, though it does not name a sibling 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?

There is no explicit guidance on when to use this tool versus the listed siblings (get_status, start_observation, poll_changes, etc.). 'DEMO ONLY' implies a demo context, but no clear conditions or alternatives are provided, leaving an agent to infer usage.

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 and destructiveHint=false, and the description aligns with those by saying 'Report'. It adds useful context about what the status covers, especially 'explicit sending limitations', but it does not disclose details like staleness or error behavior, which is acceptable given the annotation coverage.

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, front-loaded sentence that names three distinct status dimensions without wasted words. It is compact and communicates the tool's scope efficiently.

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 zero-parameter, read-only status tool, the description is nearly complete: it tells the agent what kind of information will be reported. The main gap is the lack of any guidance about when checking status matters relative to the observation lifecycle, but the low complexity and strong annotations make this acceptable.

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 has zero parameters and the schema is fully self-documenting, so there is little for the description to add. The baseline of 4 applies because there is no parameter burden on the description.

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 ('Report') and names concrete resources: backend availability, observation expiry, and sending limitations. It clearly reads as a read-only status tool and does not overlap semantically with siblings like poll_changes or acknowledge_observation, though it does not explicitly name any sibling.

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 guidance is given about when to call this tool versus alternatives such as poll_changes or preview_reply. An agent can infer that status checks belong here, but the description provides no explicit context, prerequisites, or exclusions.

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?

The description says the tool will 'invalidate pending drafts,' which is a destructive/canceling effect on pending data, yet the annotations declare destructiveHint=false. This directly contradicts the annotation and could mislead an agent about the tool's safety profile.

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 concise, information-dense sentences. The first states the core action and side effect; the second states the restart consequence. There is no filler or redundant repetition of the schema.

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 zero-parameter tool with no output schema, the description covers the action, the side effect, and the restart implication. It is largely sufficient, though it could explicitly name the restart tool or clarify whether a successful pause returns confirmation.

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?

There are zero parameters, so the schema requires no additional documentation. The description still adds useful context by clarifying that the operation targets the 'current session' implicitly rather than through arguments.

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 action and effect: 'Pause the current session and invalidate pending drafts.' It clearly identifies the resource (current session) and the behavior, distinguishing it from sibling tools like start_observation and poll_changes.

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 clear context for when to use the tool: when the current session needs to be paused. It also implications about restart behavior ('Restart creates a new baseline'), which helps an agent understand the consequence. However, it does not explicitly name alternatives or state when not to use it.

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?

Beyond the annotations, the description adds valuable behavioral context: repeated polls retain the pending observation ID, and visual changes are explicitly not proof of a new incoming message. This helps the agent interpret results correctly, though it does not clarify the non-read-only implication from readOnlyHint=false.

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, all informative. The main return value is front-loaded, and each additional sentence earns its place by clarifying visual-change semantics and poll behavior. No wasted words.

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 what is returned, when to call it, and how to interpret results. It does not define 'pending observation ID' or address the potential side effects implied by readOnlyHint=false, but these are minor given the single parameter and simple nature of the tool.

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 0% and the description never mentions session_id. With only one parameter, its purpose is somewhat inferable from the tool name and context, but the description does not explicitly add meaning to the schema, so it fails to compensate for low 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 a specific action ('Return') and resource ('pending before/after chat images and raw OCR'), plus the timing condition ('after the polling interval'). It is distinct enough from siblings like get_status or acknowledge_observation, though it does not explicitly name alternatives.

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 implies when to use the tool ('after the polling interval') but gives no explicit guidance on when not to use it or which sibling to choose instead. Usage context is present but underdeveloped.

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?

The description adds meaningful behavioral context beyond the readOnlyHint and destructiveHint annotations: it confirms no paste/send side effect and discloses that semantic privacy classification is not enforced server-side. This is useful operational caveat information that annotations alone would not convey.

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 compact, front-loaded with the core purpose, and every sentence adds value: the no-send guarantee, client prerequisites, and privacy limitation. There is no redundant or filler content.

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 omits essential parameter semantics and has no output schema to explain the draft return format. It gives useful server-side caveats and preconditions, but a 3-required-parameter tool with zero schema coverage needs more explicit input/output guidance to be safely invocable.

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 0%, so the description carries the full burden of explaining session_id, observation_id, and text, but it does not define any of them. 'Latest observation' loosely relates to observation_id, yet the role of text and session_id remains unexplained, and the requirement of text is confusing given the tool 'returns' a draft.

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 a specific verb ('Return'), a clear resource ('unsent draft for the latest observation'), and explicitly disambiguates by saying it does not paste or send anything. This makes the tool's purpose immediately distinguishable from sibling tools like acknowledge_observation or poll_changes.

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 clear preconditions and context: the client must first identify new incoming text, merge bursts, and skip privacy questions. It does not explicitly name alternative tools or state when not to use it, but the usage context is concrete enough for an agent to decide when this preview step is appropriate.

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?

The annotations only supply readOnlyHint=false and destructiveHint=false. The description adds meaningful behavioral context: it does not launch a timer, requires a follow-up poll_changes call, and needs an image-capable client for later review. This goes beyond the annotation hints without contradicting them.

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 three short sentences, each with a distinct role: core purpose, timer clarification, and client requirement. There is no filler or redundancy, and the most important info is front-loaded.

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 tool has no output schema and two optional parameters that are unexplained. While the description covers the overall workflow, an agent cannot determine what duration_seconds vs. interval_seconds control or what the call returns, which is a significant gap for a tool with schema coverage of 0%.

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 0% and the description never mentions duration_seconds or interval_seconds. There is no explanation of how these settings affect the baseline capture, leaving all meaning to be guessed from parameter names and defaults.

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 opens with 'Capture baseline for the locally verified contact' – a specific action and target resource – and explicitly notes 'never reply to baseline history.' It also distinguishes itself from poll_changes by stating it does not launch a timer, making the tool's role clear among siblings.

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 direct sequential guidance: after this tool, 'The MCP client must call poll_changes.' It also sets a clear prerequisite ('Requires an image-capable client') and a behavioral restriction ('never reply'). It stops short of naming alternative observation-related tools or stating when not to use it.

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