mdprint documentation

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds useful behavioral context by naming the valid documentation IDs and indicating the list-versus-read behavior based on the id parameter.

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 with no filler. It delivers the core purpose and parameter guidance 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 simple one-parameter, read-only tool with strong annotations, the description is complete enough for correct invocation. It covers both modes of operation and the accepted IDs, and no output schema is necessary given the simple 'list or read' semantics.

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%, yet the description compensates fully by explaining the sole parameter's meaning and enumerating valid values: getting-started, privacy, capabilities, or integrations. It also communicates the optional nature of id through the list-versus-read wording.

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 action ('List documentation sections') and the resource, and it enumerates the specific valid IDs. This separates it from sibling tools like get_example and get_product_info because it is explicitly about documentation.

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: omit the id to list sections, provide an id to read that section. However, it does not explicitly mention siblings or state when to choose get_docs over get_example, get_product_info, or list_examples.

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 convey read-only, idempotent, non-destructive behavior. The description adds valuable context beyond annotations: the result is Markdown, the examples are curated, and user documents are rejected. No contradiction with annotations.

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 with no filler. The main action and object are front-loaded, followed by a useful exclusion and allowed values.

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 one-parameter read-only tool with no output schema, this description covers the return type (Markdown), valid IDs, and what inputs are rejected. Nothing essential is missing for 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 schema provides no description (0% coverage) and only a pattern regex, so the description must compensate. It does so by naming the concrete valid ID values ('basic, tables or tasks'), giving the agent actionable parameter semantics.

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 clearly states a specific verb ('Read'), resource ('one curated Markdown example'), and selection mechanism ('by ID'). The singular 'one' and 'curated' differentiate it from list_examples, and the exclusion of user documents separates it from tools like get_docs or get_product_info.

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 curated examples only and explicitly states what it does not accept ('Does not accept user documents'), but it does not name alternative sibling tools or give explicit when-to-use-versus-other-tool 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 establish read-only, idempotent, non-destructive behavior, so the description does not need to repeat those. It adds useful context about the content returned (identity, browser capabilities, privacy, documentation links) and the non-conversion boundary, but it does not describe response format or any edge conditions.

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 with no filler. It front-loads the primary action and resource list, then follows with a clarifying negative constraint, making every word useful.

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, zero-parameter read-only tool, this description is complete. It states exactly what information will be returned and what the tool will not do, which is sufficient for an agent to invoke it correctly without an output schema.

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 empty, so parameter documentation is not needed. The description adds no param-specific meaning, but the baseline for a zero-parameter tool is appropriately high.

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 ('Read') and identifies a precise resource ('mdprint product identity, browser capabilities, privacy and documentation links'), giving a clear enumeration of what the tool returns. The negative statement 'Does not convert documents' further disambiguates it from conversion-related operations, though not from the direct 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?

The description implies this tool is for reading product metadata and explicitly says it does not convert documents, which signals a boundary. However, it does not mention when to prefer this over siblings like get_docs, get_example, or list_examples, leaving the selection 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 already cover the safety profile (readOnly, idempotent, non-destructive). The description adds useful scope information with 'curated public', clarifying that no private or user-specific data is returned, but it does not disclose output format or any listing behavior beyond that.

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 immediately conveys the action, resource, scope, and output. Every word earns its place, with no filler 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?

For a zero-parameter, read-only listing tool with strong annotations and no output schema, the description is sufficient. An agent can infer what the tool does and what it returns 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?

The tool has zero parameters, so there is no parameter documentation burden on the description. The baseline for zero-parameter tools is 4; the description need not compensate for any schema gaps.

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 ('List'), a well-scoped resource ('curated public Markdown examples'), and the key output ('their IDs'). This clearly distinguishes it from the sibling get_example, which presumably retrieves a single example.

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: listing examples and IDs is naturally a discovery step before fetching a specific example via get_example. However, the description never explicitly says when to prefer this tool over a sibling or 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.