Thomas Anglero Speaker MCP

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

With readOnlyHint=true the safety profile is already covered, and the description adds genuine behavioral context: the reply is handled personally by Thomas, and it enumerates what the response contains (who it's for, next step, offer, two EUR prices, how to start). Since there is no output schema, this return-content disclosure is the only place that information 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, front-loaded with the usage trigger before the return contents and the sibling alternative. Slightly dense in the return enumeration, but every clause carries routing or expectation-setting value.

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-param, read-only info tool with no output schema, the description covers purpose, eligibility, the sibling alternative, and the shape of the returned content. Only minor detail is absent (e.g., the concrete contact channel behind 'how to start'), which is a small gap rather than a blocking one.

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 per the baseline the schema fully carries parameter semantics and the description needs to add nothing. No parameter claims are made, so nothing is misleading.

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 resource (private one-to-one AI advisory from Thomas Anglero / The Reset offer) and distinguishes it explicitly from the keynote sibling: 'rather than a keynote for an event' and 'For a keynote, use get_speaking_topics instead.' An agent can route between the two 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?

Names the exact audience and condition for use ('a CEO, Chair or board member wants private, one-to-one advice'), the disqualifying alternative (a keynote), and points to the correct sibling by name. It also notes it works regardless of AI maturity or country, removing common filtering heuristics.

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, so the safety profile is covered. The description adds real behavioral context beyond that: there is no live calendar, availability is only confirmed on inquiry, and a human (Thomas) responds — telling the agent not to expect definitive date data from this call.

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?

Four short sentences, front-loaded with the key constraint (no live calendar). 'No live calendar is published' and 'confirmed on inquiry' partially restate the same fact, so it is efficient rather than maximally tight.

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 tool with no output schema, the description gives the agent enough to know what the response amounts to (a policy statement, not a date list) and how availability actually gets confirmed. It does not describe response formatting, but that is minor here.

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 the baseline is 4 per the rubric. The description correctly implies no input is needed to retrieve this guidance.

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 conveys the topic ('how availability is confirmed') but frames it as the answer content rather than stating a function like 'Returns guidance on how availability is confirmed.' It does not differentiate itself from the sibling get_booking_info, which an agent could plausibly reach for the same need.

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 when-to-use statement and no routing against siblings such as get_booking_info or submit_speaking_inquiry. The inquiry-based framing implies this is a pre-booking information tool, but the agent must infer that.

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, so the safety profile is covered. The description adds that fees are given on inquiry and tailored to format/location, which is modestly useful process context, but it says nothing about what information is actually returned. The closing 'Thomas replies promptly' is marketing fluff, not behavior.

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 first sentence is front-loaded and does the real work, but the third sentence ('Thomas replies promptly') earns no place and dilutes the definition. The middle sentence about fees is relevant but could be tighter.

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 no parameters and no output schema, the description must carry the full informational burden. It names three topics (process, formats, fees) but does not indicate how complete or what form the returned information takes, leaving the agent with an adequate but thin picture.

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 per the baseline there is nothing for the description to explain. It gets the default 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 gestures at content ('how booking works, formats offered, fees handled') but never states clearly that this tool retrieves booking information, nor uses a clean verb+resource phrasing. It is distinguishable from submit_speaking_inquiry by being informational rather than transactional, but the purpose stays loose and reads partly like promotional copy.

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 on when to call this versus get_availability_guidance, get_speaking_topics, or submit_speaking_inquiry. The 'fees are provided on inquiry' line hints that fee details come from a different action, but it never names that action or tells the agent when this call 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 readOnlyHint annotation already indicates this is a safe read operation. The description adds value by specifying the exact content returned (bio, positioning, clients, links), which goes beyond the annotation.

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 efficiently conveys the tool's purpose and output. No extraneous 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?

For a simple read-only tool with no parameters and no output schema, the description adequately lists the return fields (bio, positioning, clients, links), making it complete for an agent to understand the output.

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 with 100% schema coverage. The description does not need to explain parameters, and the lack of parameters is clearly communicated by the empty 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 clearly states the tool returns 'Canonical short bio, positioning, notable clients, and links for Thomas Anglero.' It uses a specific verb ('get') and resource ('speaker profile'), and the sibling tools (e.g., get_speaking_topics, get_booking_info) are clearly distinct topics.

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 explicit when-to-use or when-not-to-use guidance is provided. The description implies usage for obtaining biographical and profile information, but does not differentiate from siblings like get_speaking_topics or get_booking_info.

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 aligns with the readOnlyHint annotation, confirming it is a read-only operation. It adds value by detailing what data is returned, but does not disclose additional behaviors like caching or prerequisites.

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 is concise, front-loaded, and contains no unnecessary words. It efficiently communicates the tool's output.

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 no parameters and no output schema, the description fully specifies what the tool returns (three topics with titles, subtitles, descriptions). No additional context 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 tool has no parameters, so the baseline is 4. The schema coverage is 100%, and the description does not need to add 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?

The description clearly states it returns exactly three keynote topics, each with title, subtitle, and a one-paragraph description. This is distinct from sibling tools like get_availability_guidance or get_speaker_profile.

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 does not explicitly state when to use this tool versus alternatives, but it is implied that it is for retrieving keynote topics. No exclusions or alternatives are mentioned.

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 declare readOnlyHint=false, so the description usefully carries the rest: it records into the same pipeline as the website form, Thomas reads and replies personally, and the agent must not promise a reply or reply time. These are real behavioral constraints beyond the annotation, though the gated approval fields are largely echoed from the schema.

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?

Purpose is front-loaded and every sentence carries a distinct instruction (preconditions, field rule, pipeline behavior, reply disclaimer, alternative). It is long but dense with required agent behavior rather than 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 14-parameter write tool with no output schema and minimal annotations, the description supplies the missing behavioral guidance an agent needs before submitting. It does not state what a successful call returns (e.g., a confirmation), a minor gap.

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 reiterates the 300-character challenge requirement and the meaning of human_approved and consent, but adds no semantics beyond what the schema descriptions already state.

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 (Send) and resource (private advisory inquiry) plus the audience and scope: one-to-one AI advice, 'not a keynote'. It explicitly names the sibling it is not, submit_speaking_inquiry, so an agent can route correctly 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?

Gives explicit preconditions (read get_advisory_info first, show the person every detail, send only after approval and consent) and an explicit alternative for the keynote case. When-to-use and when-not-to-use are both 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 declare readOnlyHint=false, so the description carries the disclosure burden and does so well: it says the inquiry is written into the same pipeline as the website form, that confirmation and notification emails are sent, and it flags the website field as an anti-spam trap. That is meaningful behavioral context beyond the annotation.

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, front-loaded with purpose and requirements, with no filler. It loses a point because the long enumerations of foldable details and required fields substantially duplicate the schema's field descriptions.

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?

There is no output schema, and the description compensates by explaining what happens after submission (recording, emails, prompt reply). For a 7-parameter mutation tool with full schema coverage, an agent has enough to call it correctly; only the lack of routing guidance against the advisory sibling 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 every parameter is already documented, including the fold-everything-into-message guidance. The description restates the required field list and the message content list without adding format or validation detail beyond the schema, so the baseline 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?

States a specific verb (send) and resource (speaking inquiry) with a named recipient, Thomas Anglero. It implicitly separates itself from the sibling submit_advisory_inquiry, but never names an alternative explicitly, so it just misses the 5 bar.

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 instructs how to fill the form but never states when to choose this over submit_advisory_inquiry or when to consult get_speaker_profile/get_speaking_topics first. Usage is implied by the purpose rather than guided.

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