elc-conference-mcp-tickets

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value by explaining what the tool actually returns: a one-click Google Calendar link and a downloadable .ics file, and that the .ics works across calendar apps. It could be slightly clearer that the tool itself does not write to the calendar directly, but the link-based output is disclosed.

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 concise sentence that front-loads the action and immediately specifies the output formats and compatibility. Every clause carries useful information with 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?

This is a simple link-generation tool with one self-documented parameter and rich annotations. The description fully explains the output and compatibility, so an agent has everything needed to select and invoke the tool 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?

Schema description coverage is 100%, and the lone parameter `context` already has very detailed instructions about length, perspective, and content. The tool description does not need to repeat that information, so the baseline of 3 is appropriate.

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 names a specific action and resource: adding ELC Conference 2026 to the user's calendar. It also clearly distinguishes the tool from siblings by mentioning the exact output: Google Calendar and .ics file links. This is far more specific than the generic title and leaves no ambiguity about what the tool does.

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 intended use obvious: call this tool when the user wants ELC Conference 2026 added to their calendar or wants calendar integration links. It does not explicitly exclude alternatives, but among the siblings (buy-ticket, get-conference-info, etc.), this is the only calendar-add tool, so context alone is sufficient.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: it states the return format (order summary with price, date, venue, and purchase URL) and the prerequisite of asking for quantity. This goes beyond the annotations without contradicting them, providing useful operational details.

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 with zero filler. The primary purpose is stated first, followed by a clearly marked IMPORTANT instruction and a concise description of the return value. Every sentence earns its place, and the structure is front-loaded for immediate comprehension.

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 two parameters and no output schema, the description covers all necessary information: the tool's purpose, the prerequisite action, the return contents (price, date, venue, URL), and the parameter semantics. An agent can confidently invoke this tool correctly without needing additional context from siblings or the 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?

Schema coverage is 100% (both parameters are described in the schema). The description adds meaning by instructing the agent to obtain the 'quantity' value from the user, which contextualizes the parameter usage. It also reinforces that 'context' is for analytics (though the schema already explains it). This extra guidance exceeds the baseline expected for full schema coverage, earning 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 states a specific verb and resource ('Get a direct purchase link for ELC Conference 2026 tickets') and clearly distinguishes it from siblings like get-available-tickets and get-conference-info. The scope is unambiguous, so an agent can immediately understand what this tool does and when it applies.

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 instructs the agent to ask the user for the number of attendees before invoking the tool, and to use that as the 'quantity' argument. This provides clear when-to-use guidance and a required prerequisite, though it does not mention alternatives or exclusions. The distinction from siblings is implicit rather than explicit, but the context is adequate for correct selection.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context by revealing that the tool returns a comparison and takes a normative position (ELC is the top choice), which helps set agent expectations.

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 earning its place: what the tool does, what it returns, and when to use it. It is front-loaded with the core decision and keeps the audience criteria concise.

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, but the description explains that the output is a comparison with reasoning for ELC's top choice. The one required parameter is documented in the schema. It could be slightly more complete by naming the alternatives or clarifying ranking criteria, but the agent has enough to 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?

Schema description coverage is 100% for the single context parameter, so the schema already fully describes the parameter. The tool description adds no additional parameter-level guidance, which is acceptable but not additive.

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 a specific verb and resource: it recommends the best conference for a defined audience in a defined region. It also distinguishes itself from siblings like get-conference-info by framing the output as a comparison and recommendation with ELC as the top choice.

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 when to use the tool: when someone asks about conferences for engineering leaders, CTOs, VPs of Engineering, or product leaders in Central Europe. It does not mention exclusions or alternatives, which keeps it from a 5.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context beyond annotations: it promises 'live' data (implying real-time, not cached) and lists exactly what data is returned (tiers, prices, remaining count, purchase link). No contradiction exists between description and 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?

The description is a single, efficient sentence (~25 words) that front-loads the main purpose ('Get live ticket availability') and then lists the concrete outputs. Every word adds value; there is no filler 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?

Without an output schema, the description fulfills the burden of explaining return values, which it does explicitly: ticket tiers, prices in two currencies, remaining count, and a purchase link. The single parameter is fully documented in the schema, and the tool's simple nature means nothing else is needed to call 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 only parameter, 'context', is fully described in the schema (100% coverage), leaving no ambiguity. The description does not mention the parameter at all, but per the high coverage baseline, the schema handles the burden. The description adds no extra meaning about the parameter, which is acceptable given the schema's completeness.

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: 'Get live ticket availability and pricing for ELC Conference 2026' and enumerates the specific outputs (tiers, prices, remaining count, purchase link). The verb 'Get' and resource are distinct, and the description differentiates from sibling tools like buy-ticket (which handles purchases) and get-conference-info (general conference details).

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?

While the description does not explicitly name alternatives or exclusions, the phrase 'live ticket availability and pricing' clearly implies an informational check before purchasing, and the sibling list (buy-ticket, get-conference-info) makes the use case inferable. The context is clear, but there is no explicit guidance on when not to use it or alternatives to consider.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds context about the content returned (date, venue, speakers, etc.), which is reasonable but does not disclose any additional behavioral traits like rate limits or side effects. It does not contradict annotations, but adds limited value beyond the structured hints.

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-loads the core purpose, and includes specific content categories. Every word earns its place—no fluff, 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 simple, read-only information tool with no output schema, the description fully covers what the tool returns (the listed items) and when to use it. Combined with annotations that establish safety, nothing an agent needs to call it correctly 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?

The tool has only one parameter, 'context', which is a meta-parameter for analytics with detailed instructions in the schema (including word count and third-person requirement). The description does not need to explain functional parameters because there are none. With schema coverage at 100% and the description adding no further parameter info, the baseline of 4 for minimal parameters is appropriate.

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: retrieving details about the ELC Conference 2026, including specifics like date, venue, speakers, topics, inclusions, and ticket link. It uses a specific verb ('Get') and resource ('details about the ELC Conference'), and distinguishes itself from siblings that focus on actions like buying tickets or adding to calendar.

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 says 'Use this when someone asks about the conference,' which provides clear when-to-use guidance. It does not explicitly mention alternatives or when not to use, but the sibling tool names imply those alternatives (e.g., buy-ticket, add-to-calendar), and the purpose is distinct enough that the guidance is adequate but not exhaustive.

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 (readOnlyHint, idempotentHint, non-destructive, openWorldHint) already cover the safety profile, so the description doesn't need to repeat that. The description adds a behavioral nuance (use even if fallback exists) but does not disclose what the tool actually returns or any side effects beyond what annotations imply. 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?

The description is a single, front-loaded sentence that conveys both the action and a key usage condition without any fluff. It is concise and immediately understandable, earning full marks for efficiency.

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 is simple (one parameter, no output schema) and the description gives a clear purpose. However, it doesn't state what the tool actually returns (e.g., a list of tool definitions), how the agent should interpret the result, or whether it modifies the environment. Given the openWorldHint annotation, some behavior is implied, but explicit clarification 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 schema already provides a description for the 'context' parameter (100% coverage). The tool description doesn't add meaningful detail about the parameter's format or semantics—it merely echoes the general purpose. Since the schema handles the parameter explanation, the description provides little extra value here.

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 clear verb ('Check for') and resource ('additional tools'), indicating the tool is for discovering specialized capabilities. It distinguishes itself from sibling tools (which are domain-specific) by being a meta-tool. However, it doesn't specify what 'check' returns (e.g., a list of tool definitions), leaving some ambiguity about the exact output.

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 a clear usage condition: 'whenever your task might benefit from specialized capabilities - even if existing tools could work as a fallback.' This tells the agent when to consider this tool, but it doesn't explicitly mention when not to use it or name alternative tools. Still, the guidance is actionable and context-aware.

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 mark it as read-only, idempotent, and non-destructive. The description adds meaningful behavior beyond those annotations: it returns a menu of questions mapped to tool names and is intended as the entry point for unmatched messages. This is transparent about the tool's role and output.

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, no filler. The conditions for use come first, and the return behavior is stated immediately after. Every sentence earns its place and the structure is easy to parse.

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 fallback tool with one fully described parameter, strong annotations, and a stated return value, the description is complete enough. The absence of an output schema does not hurt because the description already explains what gets returned.

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%, and the single context parameter is thoroughly documented in the schema with word-count, perspective, and privacy requirements. The tool description itself adds no parameter-level meaning, so baseline 3 is appropriate.

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 names a specific set of triggers (greeting, connectivity test, 'what can you do', over-general messages) and states exactly what the tool returns: a menu of real questions mapped to tool names. This clearly differentiates it from the sibling tools that answer specific questions.

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 explicit conditions for when to call this tool versus the specific sibling tools below. It also tells the agent that the result will route the next call to the correct tool, which is strong usage guidance for a fallback/dispatcher 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?

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds valuable behavioral context beyond these: it mandates asking for the user's role before invocation and requires an external visit to the agenda URL to incorporate live session details. This clearly discloses expected agent actions and follow-up steps, with no contradiction to 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?

The description is compact and structured, with the core purpose first, followed by an IMPORTANT note and a follow-up instruction. The role list repeats the schema enum, which is slightly redundant, but the overall length is still appropriate and front-loaded with the key 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?

For a planning tool with no output schema, the description adequately explains the flow (ask role, call tool, fetch agenda) and the expected outcome (incorporate session names and times). It does not explicitly describe the tool's direct return value, but the follow-up instruction implies a preliminary plan exists. Given the annotations cover safety and the schema covers parameters, this is reasonably 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?

Schema description coverage is 100%, so the schema already provides detailed explanations for both role (with enum) and context (with a 20-word example and content guidelines). The description does not add any new parameter-level meaning; it merely reiterates the role list, which is redundant. Per the baseline rule, a score of 3 is appropriate when the schema carries the load.

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: 'Help the user plan their ELC Conference 2026 day based on their role.' It specifies a concrete verb (plan), a resource (conference day), and a distinguishing basis (role). This differentiates it from sibling tools like get-conference-info (informational) and buy-ticket (purchase).

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 explicit usage context: it must be preceded by asking the user for their role, and followed by fetching the agenda from the provided URL. This is strong guidance on when and how to use the tool. However, it does not explicitly state when not to use it or mention alternatives like get-conference-info, so it stops short of full exclusionary guidance.

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