Universal Agents

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is known. The description adds no further behavioral detail (e.g., whether the content is static, whether it changes over time), but for a zero-param informational lookup the remaining burden is small.

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?

One compact sentence that front-loads the topic list, awkwardly phrased as 'What X sells ... and who it is for' but free of filler. It could be tightened, yet nothing is wasted.

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 enumerating the three things the result covers (offering, engagement start, audience), which is enough for an agent to decide if this answers the user's question. It stops short of describing the response format, but that is a minor gap for a simple info 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?

The tool takes no parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. No parameter text is needed or missing.

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 gives a specific topic: what the company sells (naming Interplay, the playbook, Living Blocks, the universal agent), how an engagement starts, and who it targets. That is far more than a restatement of the name. It is not explicitly differentiated from the sibling tools, but the content scope is clear.

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 guidance on when to call this versus answer_faq, get_pricing, or request_intro. The agent must infer that this is the general overview tool for capability/company questions, and nothing states when not to use it.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds one real behavioral trait not in structured data: omitting the question returns the full set of answers. It says nothing about response shape or matching behavior for partial keywords.

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 purpose, with the default behavior appended. The topic list is long but earns its place by signaling what the agent can ask, so waste is minimal.

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 single-parameter, read-only lookup tool with no output schema and annotations covering safety, the description supplies what is needed: subject matter, valid topics, and the omit-question default. Only the sibling differentiation is left 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?

Schema coverage is 100%, so the schema fully documents the single 'question' parameter including an example keyword. The topic enumeration in the description hints at valid keyword domains, but adds little beyond the schema. 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 and resource ('Answers common questions about Universal Agents') and enumerates the covered topics, so the agent knows exactly what knowledge base backs it. It does not explicitly distinguish itself from the overlapping sibling about_universal_agents, which is the one real gap.

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 sentence 'Omit the question to get all of them' is genuine usage guidance for the optional parameter. However, there is no guidance on when to prefer this over about_universal_agents or get_pricing, which are plausible alternatives for overlapping informational needs.

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 and openWorldHint=false, so the safety profile is covered. The description adds useful scope context by enumerating the pricing topics returned, but says nothing about freshness, currency, or what happens on unknown pricing questions — fine given annotations, but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence naming the topic and its sub-areas, with zero filler or redundancy. Nothing could be cut without losing meaning.

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 informational tool with no output schema, the description gives enough to know the subject matter retrieved. It could be marginally stronger by saying it should be used specifically for cost/licensing questions, but it is essentially complete for 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?

The tool takes zero parameters, so the baseline of 4 applies. Schema coverage is 100% and there is nothing for the description to compensate for on the input side.

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 resource (Universal Agents pricing) and enumerates the coverage areas — paid pilot, rollout continuation cost, licensing and support. It is clearly distinguishable from siblings like about_universal_agents or answer_faq, though it lists content nouns rather than a verb+resource phrase.

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 statement of when to call this versus answer_faq or request_intro, and no conditions, prerequisites, or exclusions. The agent must infer that this is the pricing-specific lookup, which is only weakly implied.

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 and openWorldHint=false, and the description reinforces this with 'Sends nothing itself,' which is the key behavioral fact an agent needs before invoking. It also discloses the output artifact (a mailto link). It stops short of stating auth requirements or whether the draft is persisted.

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 tight sentences, zero waste, with the core action and the no-side-effect guarantee front-loaded.

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, and the description steps in to explain what is produced (a mailto link the user can send), which is the essential return-value information. Slightly incomplete in that it doesn't say what happens if no parameters are supplied, though none are required.

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 all four parameters (goal, name, size, agency) are already documented in the schema. The description adds no parameter-level detail, 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 (drafts) and resource (intro email to Universal Agents), and immediately scopes the behavior with 'Sends nothing itself.' This is clearly distinguishable from the siblings about_universal_agents, answer_faq, and get_pricing.

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?

'For the person you are helping' implies the context in which this is used, but there is no explicit when-to-use, no exclusions, and no reference to the sibling tools that handle informational requests (pricing, FAQ, about). Usage is inferable rather than stated.

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