PlugMyAI

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 return-content context ('the plan required and official source'), which is genuinely useful, but says nothing about behavior when no steps exist or about rate/source 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?

A single compact sentence with the key content (steps, required plan, official source) front-loaded. The sentence is a noun fragment rather than a verb-led statement, 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?

With only two required, fully documented parameters and no output schema, the description covers the essentials including what the response contains. It is still thin on when to call it and what happens on a miss, which matters for a lookup tool an agent must choose deliberately.

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 both 'app' and 'ai' are already documented in the schema (including the AI assistant examples). The description adds no syntax, casing, or matching guidance 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?

States a specific resource ('steps to connect an app to an AI assistant') and implies retrieval of that content. It contrasts implicitly with discovery-oriented siblings (list_connectors, what_can_i_connect) but never names them, so differentiation requires 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?

There is no when-to-use guidance, no prerequisites, and no reference to alternatives such as what_can_i_connect. An agent must guess that this is the follow-up call after discovering a connector.

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 (readOnlyHint=true) and dataset scope (openWorldHint=false). The description adds genuinely new behavioral context by enumerating the possible status values ('works / not available / not confirmed yet') and noting that each result carries an official source, which an agent cannot learn from the schema or 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?

Three short sentences, each carrying distinct information: what is listed, how to filter, and what comes back. The core purpose is front-loaded with zero 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 no output schema, the description usefully compensates by summarizing result contents (status values plus official source), and the readOnly annotation plus zero required parameters make invocation unambiguous. The only gap is sibling differentiation against 'what_can_i_connect'.

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 are already documented as 'ChatGPT, Claude, Gemini or Grok' and 'App name, e.g. Gmail'. The description only restates that they can be combined with 'and/or', adding marginal value over 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 ('List which apps connect to ChatGPT, Claude, Gemini and Grok'), which is far more informative than the name alone. It scopes the resource to AI-to-app connectors, though it does not explicitly distinguish itself from the sibling 'what_can_i_connect', which sounds like an overlapping query.

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 through 'Filter by AI and/or app name', telling the agent that filters are optional and combinable. However, it never states when to prefer this tool over 'what_can_i_connect' or 'get_connection_steps', so routing among siblings 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 readOnlyHint=true and openWorldHint=false. The description adds the sorting behavior ('newest first') and that entries are 'verified', which is useful context, but it omits default result count, pagination, and what 'verified' means. With annotations covering the safety profile, this is a moderate addition.

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 scope (recently verified, newest first) is stated immediately.

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 list tool with annotations and no output schema, the description is adequate in stating what is returned and the sort order. However, it leaves the limit parameter undocumented and does not clarify how this tool relates to list_connectors or what happens if limit is omitted.

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 (limit) has 0% schema description coverage and is not mentioned in the description. The schema does provide type and min/max constraints, so an agent can infer it controls count, but the description adds no semantic meaning such as default value or behavior when omitted.

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 resource (connector entries) and the scope (most recently verified, newest first), which distinguishes it from a generic connector list. However, it does not explicitly name or contrast with sibling tools like list_connectors, so sibling differentiation is inferred rather than stated.

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 explicit when-to-use guidance, no conditions, and no mention of alternatives such as list_connectors. The only hint is the implied use case of retrieving recently verified connectors, which is not enough to route an agent among siblings.

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 only the 'verified to work' trust qualifier, but says nothing about return format, ordering, or how the assistant argument affects results.

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?

It is a single short sentence with no waste, appropriately sized for a simple one-parameter tool. It reads as a noun phrase rather than a full sentence, which is slightly less front-loaded than it could be.

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 lookup with one fully documented parameter and no output schema, the description conveys enough to call the tool correctly. It could note what the returned app list looks like, but that is a minor gap.

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 single 'ai' parameter already documented as 'ChatGPT, Claude, Gemini or Grok'. The description adds no further semantics, 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 names the resource (apps verified to work with an AI assistant), making it clear this returns a list of connectable apps. However, it is a noun fragment with no explicit verb and gives no differentiation from the sibling list_connectors, which sounds like it does something similar.

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 explicit when-to-use statement, no prerequisites, and no mention of alternatives among siblings (get_connection_steps, list_connectors, recently_updated). Usage is only loosely implied by the title.

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