AITeamGuide AI agent prices

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 real behavioral value by disclosing the result-set rule: entries without a listed monthly price are excluded, so the agent knows results are a filtered subset. It does not mention pagination, the default for limit, or how ties are ordered.

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, front-loaded with the resource and ordering, and the exclusion rule follows as a clean caveat. Minor redundancy between 'sorted by lowest listed monthly price' and 'cheapest first', but nothing is padded.

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 2-parameter read tool with no output schema, the description covers the filtering and sort semantics adequately. It is still incomplete on the limit parameter and its default, which an agent needs to know to control result size or understand truncation.

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 only 50%: category is documented ('Category slug from list_categories') but limit has no description anywhere. The description does not mention limit, its default, or its maximum of 25, so it fails to compensate for the coverage gap on a parameter that directly shapes the result size.

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 the specific resource (AI agents), the scope (one category), and the ordering (monthly price ascending in USD), which lets an agent tell it apart from a generic search. It does not name or contrast with the siblings get_agent_pricing and search_ai_agents, which likely overlap in purpose.

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 says what the tool returns but never states when to choose it over get_agent_pricing or search_ai_agents. The only hint at alternatives is the schema note pointing to list_categories for slugs, which covers input discovery, not tool 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 cover safety (readOnlyHint=true, openWorldHint=false), and the description adds real value by characterizing the payload: vendor pricing source and the date the price was checked, signaling point-in-time data with provenance. It stops short of describing behavior for an unknown id or whether all tiers are included.

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 with no filler; the key clause (what is returned) comes before the lookup-method clause. Every phrase 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 one-parameter read tool with annotations and no output schema, the description covers input form and the highlights of the returned payload. Missing are the not-found case and whether the tiers include currency/billing period detail, which matter for a pricing lookup with 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 coverage is 100% and the description's 'by id (e.g. 'cursor') or name' essentially restates the agent parameter's own documented description without adding matching rules. With one fully documented parameter, the schema carries the semantic load, so 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?

The description names a specific verb and resource: fetching full pricing tiers for one AI agent or product, keyed by id or name, from AITeamGuide. It is clearly distinct from a bulk/cheapest listing, but it never names the sibling tools (search_ai_agents, cheapest_ai_agents) to make the boundary explicit.

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 only implied: it is the tool for a known single agent, and the parenthetical id example suggests how to call it. There is no statement of when to prefer this over search_ai_agents (unknown id) or cheapest_ai_agents (comparison shopping).

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 establish this as a safe, closed-world read, so the description only needs to add context. It does add one useful semantic detail — counts reflect only 'fully listed' products, not all products — but says nothing about ordering, completeness, or how to consume the result. Adequate but thin.

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 fragment that front-loads the returned field and qualifies the count semantics; every word carries information and nothing is padded.

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 is the only source for return shape, and it does identify the two fields (slug, count). A short note on ordering or typical next step would make it fully complete for a zero-argument enumeration 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 zero parameters, so the baseline is 4 and there is nothing for the description 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?

The description names the exact resource (category slugs) and the payload returned with each (count of fully listed products), which is specific enough for an agent to know what data it gets. It lacks an explicit verb and never contrasts itself with the agent-search/pricing siblings, but the resource is distinct enough that confusion is unlikely.

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 when-to-use guidance, no statement of what the categories are for, and no pointer to which sibling to call after obtaining a slug. Usage is implied only by the title 'List AI agent categories'.

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 safety is covered. The description adds useful context beyond that: prices are public and checked by AITeamGuide, and it enumerates the returned fields including the checked date and source page, which helps the agent understand data freshness.

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 what is searched and followed by filters and return fields. There is minor redundancy, such as the parenthetical notice about checked prices, but no significant waste.

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 five optional parameters, no required inputs, full schema coverage, and no output schema, the description is complete enough to call correctly. It also describes return fields, which compensates for the absent 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%, so all five parameters are already documented in the schema with examples and defaults. The description restates the filter concepts but adds no syntax, format, or edge-case detail beyond what the schema provides, 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?

The description states a specific verb (Search) and resource (AI agents and receptionist products) plus the filter dimensions, so the tool's function is clear. It does not explicitly name how it differs from siblings such as cheapest_ai_agents or get_agent_pricing, leaving that differentiation to inference.

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 lists the available filter mechanisms (free text, job category, free plan, max monthly price), which implies when to use this tool. However, it gives no explicit guidance on when to prefer it over cheapest_ai_agents or get_agent_pricing, nor any exclusions.

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