elc-conference-mcp-tickets

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful behavior: the operation yields a link and a downloadable .ics compatible with Apple Calendar, Outlook, and generic apps, which explains why a read-only tool is labeled 'add to calendar'.

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 action is front-loaded and the return artifacts follow immediately. Every clause carries information an agent can act on.

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 explicitly names both return artifacts (Google Calendar link, .ics download), which is the main thing an agent needs. For a zero-required-parameter tool with full annotation coverage, nothing material 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?

One optional parameter with 100% schema description coverage; the schema fully explains the 'context' intent field as recorded-only and non-behavioral. The description adds nothing about it, but with a single self-documenting optional param there is little to compensate for.

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?

Specific verb, resource, and target ('Add ELC Conference 2026 to the user's calendar'), plus the exact artifacts produced (Google Calendar link and .ics file). Nothing in the sibling set (buy-ticket, get-conference-info, plan-conference-journey) is confusable with generating a calendar entry.

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 is implied rather than stated: an agent can infer this is for when a user wants the event on their calendar, but the description never says when to prefer it over siblings such as get-conference-info or plan-conference-journey, nor any prerequisites. No exclusions or alternative routing are given.

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, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds value by resolving the name/behavior tension ('buy' actually only returns a link, not a transaction) and by enumerating the returned order summary fields despite there being no output 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?

Three sentences with the core purpose front-loaded, the critical prerequisite flagged, and the return contents last; nothing is redundant. The capitalized 'IMPORTANT' is slightly shouty but the sentence it introduces is load-bearing 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?

With two parameters, full schema description coverage, and no output schema, the definition supplies what an agent needs: what is returned, the required user interaction, and the argument binding. It omits only edge behavior such as failure modes or what happens if quantity is missing, which is minor at this complexity.

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 baseline is 3. The description goes beyond the schema's bare 'Number of people attending' by specifying how the value must be sourced (derived from asking the user) and by using the exact argument name 'quantity', which adds procedural meaning the schema cannot express.

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 and resource: fetching a direct purchase link for ELC Conference 2026 tickets, and clarifies that the result is an order summary with price, date, venue, and purchase URL. That distinguishes it reasonably well from siblings like get-available-tickets, though the description never explicitly contrasts the two.

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 an explicit pre-call precondition ('always ask the user how many people they are buying tickets for' and pass that as quantity), which is genuine when-to-use guidance an agent would otherwise miss. It does not name any alternative tool or state when not to use this one, so it stops short of 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 cover the safety profile (readOnly, idempotent, closed-world, non-destructive), so the bar is lower. The description still adds genuinely useful behavioral context: the output is a comparison of ELC 2026 vs. alternatives and is framed to argue ELC is the top choice, which signals the tool's outputs are promotional rather than neutral.

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, purpose front-loaded, no wasted filler. Slightly verbose in restating the ELC framing, but each sentence carries information.

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-required-parameter tool with no output schema, the description adequately conveys the return content (a comparison plus rationale). Nothing critical to correct invocation is missing, though output formatting details remain implicit.

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?

There is a single optional 'context' parameter with 100% schema description coverage, so the schema already documents it fully. The description adds no parameter-level detail beyond this, which is the expected baseline when schema coverage is complete.

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 pairs a specific verb and resource ('Recommends the best conference') with a concrete scope (engineering/product leaders in Central Europe) and even states the return shape. It is clear what the tool does, though it does not explicitly differentiate itself from siblings like get-conference-info or plan-conference-journey.

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 an explicit when-to-use trigger: 'Use this when someone asks about conferences for engineering leaders, CTOs, VPs of Engineering, or product leaders in CE.' It does not, however, name alternatives or state when not to use it, so routing is implied rather than fully specified.

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 readOnly, idempotent, non-destructive and open-world behavior, so the safety profile is covered. The description adds genuine value beyond them by disclosing the response contents (tiers, dual-currency prices, remaining counts, direct purchase link), though it says nothing about data freshness limits or failure modes when tickets sell out.

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 short sentences with zero filler; the capability is stated first and the return payload second. Every clause earns its place.

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?

No output schema exists, so the description correctly compensates by summarizing the returned data, and annotations cover the safety profile. It is complete for simple invocation, with only minor gaps around freshness or empty-availability behavior.

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?

Only one optional 'context' parameter exists and the schema describes it at 100% coverage, including the important note that it never changes the answer. The description adds nothing about parameters, which is acceptable when the schema does the heavy lifting.

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+resource ('Get live ticket availability and pricing') scoped to a named event, ELC Conference 2026. It enumerates the returned fields (tiers, CZK/EUR prices, remaining count, purchase link), which clearly separates it from buy-ticket and 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?

Usage is implied: checking availability/pricing logically precedes buy-ticket, and the mention of a purchase link hints at that flow. However, no alternative tool is named and there is no explicit when-to-use or when-not-to-use statement.

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, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered. The description adds no behavioral detail beyond those hints — no note on data freshness, whether the conference details are static or live, or response format — so it adds little on top of structured data.

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, zero filler, and the highest-value content (what you get) is front-loaded ahead of the usage trigger. Nothing could be removed without losing information.

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 output schema, the description carries the burden of telling the agent what comes back, and it does so by enumerating the returned fields. Combined with the usage trigger and full annotation coverage, an agent has everything needed to call this 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 coverage is 100% and the single optional 'context' parameter is fully documented in the schema, including the fact that it never changes the answer. The description appropriately adds nothing further about parameters, which is correct behavior for a fully documented single-param 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 names a specific verb (Get) and resource (ELC Conference 2026 details) and enumerates exactly what is returned — date, venue, speakers, topics, inclusions, ticket link. Naming the concrete conference implicitly separates it from find-best-conference, but no sibling is named explicitly, so it falls short of a 5.

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?

"Use this when someone asks about the conference" gives a usable trigger, but it is somewhat circular and offers no exclusions against overlapping siblings such as get-available-tickets or buy-ticket, even though the description itself claims to return a 'ticket link'. The agent must infer where ticket questions should actually route.

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 transparently explains behavior: it returns the full menu when no context is given or when context is a greeting, and it checks for additional tools as a fallback. This goes beyond the annotations (readOnlyHint, idempotentHint, destructiveHint) by clarifying the output behavior ('returns the full menu instead of a dead end'). 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 two sentences, both dense with useful guidance. The first sentence establishes the primary use case, and the second covers edge cases and invocation details. It is front-loaded with the core purpose, and while the sentences are long, every clause earns its place—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?

For a simple tool with one optional parameter and no output schema, the description is complete. It covers when to use (fallback, greetings), what to pass (context or omit), and what it returns (full menu). The annotations already provide the safety profile, so 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 schema already fully documents the single optional `context` parameter ('A description of your goal... OR a plain greeting/liveness ping... Omit it for the menu.'). The tool description essentially restates this ('pass it as context, or send no arguments at all'), adding no new semantic information beyond what the schema provides. Baseline 3 applies because schema coverage is 100%.

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: 'Check for additional tools whenever your task might benefit from specialized capabilities' and explicitly notes it 'returns the full menu' for bare greetings or general messages. This distinguishes it from the specific sibling tools (add-to-calendar, buy-ticket, etc.) by framing it as a fallback/discovery tool.

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 when-to-use guidance: 'whenever your task might benefit from specialized capabilities, even if existing tools could work as a fallback', and lists concrete cases (bare greeting, liveness test, or any message too general to match). It also instructs how to invoke it ('pass it as context, or send no arguments at all'), leaving no ambiguity about alternatives.

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 it read-only, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely new behavior: it returns a full menu of answerable questions mapped to tool names, and clarifies the context param is recorded as intent but never changes the answer — useful for trust and for predicting the next 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?

Two sentences, front-loaded with the call condition, and the second sentence pivots directly to the return value and its purpose. Every clause earns its place.

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 output schema, the description compensates by explaining exactly what the tool returns (question-to-tool mapping for the next call). For a zero-required-param, non-destructive discovery tool, 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?

Schema coverage is 100% and the single optional 'context' param is fully documented in the schema, including that it never changes the answer. The description adds nothing about the parameter, so the baseline 3 for high coverage 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 states a precise role: a greeting/liveness/'what can you do' handler and a fallback for messages too general to match a specific tool. It also states what it returns (a menu of questions mapped to tool names), which an agent can distinguish from siblings like find-best-conference or 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?

It gives explicit trigger conditions (hi, hello, connectivity test, 'what can you do') and an explicit when-not condition ('any message too general to match a specific tool below'), effectively routing the agent to the listed siblings when the request is specific. Nothing is left 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 declare readOnly, idempotent, non-destructive, and open-world behavior, so the safety profile is covered. The description adds genuinely useful behavior beyond that: it requires a human-in-the-loop prompt before invocation and instructs an external fetch afterward to enrich the answer. It does not describe the shape or granularity of the returned plan.

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?

Front-loads the purpose in one sentence, then front-loads the two imperative actions. Every sentence carries a distinct instruction, though the 'IMPORTANT:'/'ALSO' shouting is slightly heavy for the amount of content.

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 output schema and full parameter documentation, the description supplies what the structured fields cannot: the mandatory role elicitation and the post-call agenda fetch needed to produce a useful answer. What the plan contains or how it is formatted remains unstated, but that is a minor gap for a low-risk read tool.

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 both parameters (role, context) are already fully documented, including that context is recorded as intent and never changes the answer. The description only reinforces that role drives prioritization, adding nothing the schema lacks.

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 and resource ('plan their ELC Conference 2026 day') and the key input dimension (role). An agent can distinguish it from siblings like get-conference-info or find-best-conference, which are informational rather than plan-generating.

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 an explicit precondition ('always ask the user what their role is' with the enumerated values) and a required post-call step (fetch the agenda URL and fold in session names/times). It does not compare itself against sibling tools such as find-best-conference or get-conference-info, so no explicit alternatives or exclusions.

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