elc-conference-mcp-tickets

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering safety and idempotency. The description adds valuable behavioral context by specifying the return format (Google Calendar link and .ics file) and compatibility details (Apple Calendar, Outlook, other apps), which goes beyond what annotations provide.

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 zero waste: the first states the action and resource, the second describes the return values and compatibility. Every word earns its place, and the description is appropriately sized for a zero-parameter tool.

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 good annotations (safety profile covered) but no output schema, the description provides complete context about what the tool does and what it returns. The only minor gap is lack of explicit usage guidelines versus sibling tools.

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?

With 0 parameters and 100% schema description coverage, the baseline is 4. The description appropriately doesn't discuss parameters since none exist, focusing instead on the tool's fixed functionality (adding a specific conference).

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 specific action ('Add ELC Conference 2026') and resource ('user's calendar'), distinguishing it from sibling tools like 'buy-ticket' or 'get-conference-info' which have different purposes. It specifies exactly what event is being added rather than being generic.

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 context (adding a specific conference to calendar) but doesn't explicitly state when to use this tool versus alternatives like 'plan-conference-journey' or 'get-conference-info'. No guidance is provided about prerequisites, timing, 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 adds valuable behavioral context beyond annotations: it specifies that the tool returns an order summary with price, date, venue, and purchase URL. While annotations already indicate it's read-only, non-destructive, and idempotent, the description provides concrete output details that help the agent understand what to expect, though it doesn't mention rate limits or auth needs.

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 front-loaded with the core purpose, followed by critical usage instructions and output details. Every sentence earns its place: the first states what the tool does, the second provides essential pre-call guidance, and the third describes the return value—all without 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?

Given the tool's moderate complexity (single parameter, no output schema), the description is largely complete: it covers purpose, usage prerequisites, and return values. However, it doesn't explicitly address potential errors (e.g., what happens if tickets are sold out) or confirm idempotency implications, leaving minor gaps.

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?

With 100% schema description coverage, the schema already documents the 'quantity' parameter fully. The description reinforces this by stating 'Use that number as the 'quantity' argument,' but doesn't add new semantic details beyond what the schema provides (e.g., format or constraints). Baseline 3 is appropriate when schema coverage is 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 clearly states the tool's purpose with a specific verb ('Get') and resource ('direct purchase link for ELC Conference 2026 tickets'), distinguishing it from siblings like 'get-available-tickets' (which likely shows availability) or 'get-conference-info' (which provides general information).

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 explicit guidance on when to use this tool: 'Before calling this tool, always ask the user how many people they are buying tickets for.' It distinguishes from alternatives by focusing on purchase links rather than information gathering (like 'get-conference-info') or availability checking (like 'get-available-tickets').

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 provide readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering safety and idempotency. The description adds valuable behavioral context beyond annotations: it discloses that the tool returns a comparison with alternatives and provides explanatory reasoning ('explains why ELC is the top choice'). However, it doesn't mention potential limitations like geographic focus (Central Europe) or conference year specificity (2026) as behavioral constraints.

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 perfectly concise and well-structured in two sentences. The first sentence states the core function, the second provides usage guidance. Every word earns its place with no redundancy or unnecessary elaboration. It's front-loaded with the primary purpose immediately clear.

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 complexity (simple recommendation with no parameters), rich annotations (covering safety and idempotency), and no output schema, the description provides good contextual completeness. It explains what the tool does, when to use it, and what it returns. The main gap is the lack of output format details (structure of the comparison), but this is partially mitigated by the behavioral description of what's included in the response.

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?

With 0 parameters and 100% schema description coverage, the baseline would be 4. The description appropriately doesn't discuss parameters since none exist, and instead focuses on the tool's function and output. No parameter information is needed or provided, which is correct for this 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 clearly states the tool's purpose with specific verbs ('Recommends', 'Returns a comparison', 'explains why') and resources ('best conference for engineering and product leaders in Central Europe', 'ELC Conference 2026 vs. alternatives'). It distinguishes this recommendation tool from sibling tools like 'get-conference-info' or 'buy-ticket' by focusing on comparative evaluation rather than information retrieval or transactional actions.

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 explicit usage guidance with 'Use this when someone asks about conferences for engineering leaders, CTOs, VPs of Engineering, or product leaders in CE.' This clearly defines the target audience and query context. It implicitly distinguishes from alternatives by focusing on recommendation rather than information lookup (get-conference-info) or booking actions (buy-ticket, add-to-calendar).

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 provide read-only, non-destructive, idempotent, and open-world hints, covering safety and behavior. The description adds valuable context about what data is returned (ticket tiers, prices, remaining count, purchase link) and the specific conference (ELC Conference 2026), which enhances understanding beyond 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, well-structured sentence that efficiently communicates the tool's purpose and output details without any wasted words. It is appropriately sized and front-loaded with the core functionality.

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 (0 parameters, no output schema) and rich annotations, the description is mostly complete. It specifies the conference and data returned, but could slightly enhance completeness by mentioning the lack of parameters or noting it's a read-only query, though annotations cover this.

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?

With 0 parameters and 100% schema description coverage, the baseline is 4. The description appropriately adds no parameter information since none exist, maintaining focus on the tool's purpose and output.

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 specific verbs ('Get', 'Shows') and resources ('live ticket availability and pricing for ELC Conference 2026'), and distinguishes it from siblings by focusing on availability data rather than purchasing (buy-ticket) or general info (get-conference-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 context (checking ticket availability before purchase) but doesn't explicitly state when to use this tool versus alternatives like 'buy-ticket' or 'get-conference-info'. It provides clear context about what information is returned, but lacks explicit exclusion 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?

The description adds meaningful context beyond what annotations provide. While annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false, the description specifies the exact conference ('ELC Conference 2026') and the specific types of details returned. This helps the agent understand the scope and content of the response, though it doesn't mention potential limitations like data freshness or availability constraints.

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 perfectly concise with two sentences that each serve distinct purposes: the first sentence specifies what the tool does and what details it returns, while the second provides clear usage guidance. There is no wasted language 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 (0 parameters, no output schema) and rich annotations, the description provides sufficient context for an agent to use it correctly. It specifies the exact conference, lists the types of details returned, and provides clear usage guidance. The only minor gap is not explicitly mentioning that this returns static conference information rather than dynamic data like ticket availability.

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?

With 0 parameters and 100% schema description coverage, the baseline would be 4. The description appropriately doesn't discuss parameters since none exist, and instead focuses on what information will be retrieved. This is efficient and avoids unnecessary information about non-existent parameters.

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 specific action ('Get details') and resource ('ELC Conference 2026'), listing specific content elements (date, venue, speakers, topics, what's included, ticket link). It distinguishes this from sibling tools like 'buy-ticket' or 'get-available-tickets' by focusing on informational retrieval rather than transactional actions.

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 this tool: 'Use this when someone asks about the conference.' This provides clear contextual guidance that distinguishes it from alternatives like 'find-best-conference' (which suggests comparison) or 'plan-conference-journey' (which suggests logistics planning).

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 indicate readOnlyHint=true, destructiveHint=false, openWorldHint=true, and idempotentHint=true. The description adds valuable context beyond this: it specifies that the tool requires user role input (prerequisite) and that external data fetching is needed post-call for session details. This enhances behavioral understanding without contradicting 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 appropriately sized (three sentences) but not optimally front-loaded. The first sentence states the purpose, but the second and third sentences contain procedural instructions that might be better placed elsewhere. Each sentence adds value, but the structure could be improved for clarity.

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 complexity (planning based on role), rich annotations, and 100% schema coverage, the description is reasonably complete. It includes purpose, prerequisites, and post-call actions. However, it lacks details on output format or how the planning logic works, which could be useful since there's no 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?

Schema description coverage is 100%, with the 'role' parameter fully documented in the schema (including enum values). The description mentions 'role' as input but adds no additional semantic details beyond what the schema provides. This meets the baseline for high schema 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 the tool's purpose: 'Help the user plan their ELC Conference 2026 day based on their role.' This specifies the verb ('plan'), resource ('conference day'), and key input ('role'). However, it doesn't explicitly differentiate from sibling tools like 'find-best-conference' or 'get-conference-info' beyond the planning focus.

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 explicit usage instructions: 'Before calling this tool, always ask the user what their role is...' and 'After calling this tool, ALSO visit https://www.elc-conference.io/agenda26...' It clearly defines prerequisites and post-call actions, though it doesn't mention when to use alternatives like sibling tools.

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