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 clearly indicates a non-destructive export operation and describes the output format, but does not mention potential side effects, resource implications, or any special considerations. This is adequate but not rich.

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 is immediately informative and free of filler. The key action, scope, and output format are all front-loaded 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 zero-parameter export tool with an output schema present, the description fully conveys what the tool does and its output format. There is no missing information needed for an agent to select and invoke it correctly.

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 accurately reflects that with 100% coverage. The description adds meaning by explaining what the output bundle contains, fulfilling the parameter semantics baseline for a parameterless tool.

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 ('Export') with a clear resource ('the full registry') and output format ('EML bundle'). The parenthetical clarifies structural detail (one listing per message), distinguishing it from sibling tools like publish, search, subscribe, and pull.

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 makes the tool's function obvious but does not explicitly state when to use it versus alternatives. Sibling names provide context, but no direct comparison or exclusion is given, so guidance is only implied.

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 does not disclose whether the operation is read-only, whether it affects the outbox state, or any rate limits. The term 'List' suggests a read, but the tool could have side effects like marking items as sent, which is not addressed.

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 of eight words, front-loaded with the action and resource, containing no 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?

Given the simple zero-parameter tool and the presence of an output schema, the description covers the core function. However, it does not provide any context on when to use this tool versus the sibling tools, making it slightly incomplete for an agent with all tools available.

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, so the schema already provides all necessary information. The description correctly adds no redundant parameter details.

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 'List' and clearly identifies the resource as 'listings queued for mesh broadcast (unsent)', which unambiguously distinguishes it from sibling tools like marketplace_publish or marketplace_search.

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 it is for viewing unsent broadcast queue items but does not explicitly state when to use it versus alternatives. No exclusions or alternative tool references are provided.

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. It discloses a key behavioral trait: the tool stores locally and broadcasts over the mesh via SMTP relay, giving insight into its side effects. However, it omits important details such as idempotency, overwrite behavior, or error handling, which leaves some behavioral ambiguity.

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 concise: it fronts the main purpose, uses a bullet list for kinds, and adds the storage/broadcast behavior in two short lines. There is no redundant or filler text; every sentence serves a purpose.

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 core purpose, the kind taxonomy, and essential behavior (local storage + mesh broadcast). An output schema exists, so return values are handled separately. However, given the 9-parameter complexity, the lack of documentation for optional parameters and their interrelationships leaves some gaps, making it not fully 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 has zero descriptions for parameters, so the description must compensate. It does explain the 'kind' parameter and its three values, which is valuable. However, the remaining eight parameters (tags, owner, payload, ttl_seconds, broadcast_to_mesh, etc.) receive no explanation, leaving most of the parameter semantics unresolved.

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 'Publish a listing to the global marketplace', a specific verb+resource statement that clearly identifies the tool's function. It further elaborates the three listing kinds (mcp_server, knowledge, idea), which distinguishes it from sibling tools like search, pull, and export.

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 usage for sharing new content on the marketplace and explains the kind taxonomy, but it does not explicitly state when to use this tool versus alternatives (e.g., export or outbox). It provides context but no exclusions or direct comparisons to 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?

No annotations are provided, so the description carries the burden. It discloses spool directory defaults and the file-processing mechanism (*.eml, X-Marketplace-Kind header), which adds useful context. However, it does not state whether pulling consumes or deletes messages, whether it is idempotent, or any side effects – leaving ambiguity about the operation's impact.

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 each detail about defaults and processing earns its place. No fluff or 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?

Given the tool's simplicity (one optional parameter, output schema present), the description covers the core behavior, spool location, and file format. It lacks explicit side-effect disclosure (e.g., whether messages are removed), which would make it more complete, but the output schema likely covers return values, so no explanation there is needed.

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 schema has 0% coverage, but the description fully explains the only parameter (spool_dir) by specifying the default resolution ('env ACP_INBOX or ./spool/executor'). This gives clear meaning and behavior beyond the bare schema definition.

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 function: 'Pull new marketplace listings from the inbound mesh spool' – a specific verb and resource. It is immediately distinguishable from sibling tools like publish, search, and outbox by focusing on inbound consumption.

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 context is clear: this tool retrieves new marketplace listings from a spool directory, with defaults explained. It doesn't explicitly mention when not to use it or name alternatives, but the purpose is unambiguous enough for an agent to select it for consuming inbound messages.

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 full burden of disclosing behavior. It reveals that this is a search operation and lists filter options, but does not mention authentication requirements, result ordering, pagination, or whether it is read-only. This is a basic description with minimal behavioral context.

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 action and followed by a compact list of filter options. Every word contributes to understanding, with no redundancy 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 search tool with an output schema, the description gives sufficient context: global scope, filterable fields, and implicit read-only intent. It does not explain 'limit' or result ordering, but these are not critical given the schema exists and the default limit is visible in the input schema. Overall, it is complete enough for an agent to use correctly.

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?

Since schema description coverage is 0%, the description must explain parameter meanings. It does so for kind (with examples mcp_server, knowledge, idea), domain (crypto, reverse, algo, embedded), tags, and query. However, it omits the 'limit' parameter, which remains undocumented. This partial compensation earns a 4.

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 with a specific verb ('Search'), a defined resource ('the global marketplace for listings'), and enumerates the filter dimensions. This distinguishes it from sibling tools such as marketplace_publish, marketplace_subscribe, and marketplace_export, which serve different functions.

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 the use case—searching listings—but provides no explicit guidance on when to prefer this tool over alternatives or when not to use it. It does not mention sibling tools or exclusions, so the agent must infer usage from the purpose.

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 available, the description carries the full burden of behavioral disclosure. It only lists data categories and does not state whether the operation is read-only, how data is aggregated, or any performance or limitation information. This is minimal 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 short fragment 'Marketplace statistics: totals, kinds, domains, peer instances.' It is extremely concise and front-loaded, with no fluff or repetition, making it easy to parse quickly.

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 absence of parameters and the presence of an output schema, the description mainly needs to convey what the statistics cover. It lists categories but is vague about what 'totals' and 'kinds' refer to, and does not describe the result shape. The output schema likely compensates, but a bit more detail would improve completeness.

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, so the empty input schema is fully covered. The description adds no parameter information, but none is needed; the baseline score for 0 parameters is 4.

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 as a statistics endpoint for the marketplace, listing specific data categories (totals, kinds, domains, peer instances). It is distinct from sibling tools like marketplace_search and marketplace_publish, though it lacks an explicit verb like 'retrieve' or 'get'.

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 alternatives such as marketplace_search or marketplace_export. The name and description imply it is for obtaining statistics, but no context, prerequisites, or exclusions are provided.

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 discloses important behavioral traits: the filter persists locally (MVP stage) and will later be wired to the relay fan-out. This goes beyond the bare schema, but with no annotations, it still omits details like whether subscriptions overwrite existing ones, authentication needs, or side effects on repeated calls.

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 long, front-loaded with the core purpose, and every sentence adds value—the MVP context is essential for setting expectations. 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?

While the description clearly states the purpose and gives an MVP note, it lacks any parameter semantics and doesn't explain how to construct the filter or what outcome to expect beyond persistence. Given no annotations and no schema descriptions, this is undercomplete for reliable 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 description coverage is 0% and the description provides no explanation of the 'kind', 'tags', or 'domain' parameters. The agent is left to infer their meaning from parameter names alone, which is insufficient for correct invocation.

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 begins with a clear, specific action: 'Register a subscription filter.' It not only identifies the verb and resource but also distinguishes it from siblings by mentioning its relationship to marketplace_pull, which clarifies its role in the marketplace workflow.

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 provides clear context by stating the filter is 'honored by marketplace_pull' and explains the current MVP limitation versus production wiring. This implies when the tool is useful, and while it doesn't explicitly exclude alternatives, the context is sufficient for an agent to understand its place among siblings.

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