GoNoGo

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

Annotations already declare readOnlyHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds one genuinely useful behavioral fact — the call may come back with a 'still running' status rather than a verdict — but says nothing about freshness, polling, or error behavior for an unknown/invalid project_id.

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 compact sentences, front-loaded with the verdict/score outcome before the edge case. The second sentence about the project page earns its place by scoping what is not returned, though it does not tell the agent where to source project_id.

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?

An output schema exists, so the return shape need not be described. However, for a one-parameter tool with zero schema descriptions, the definition omits the crucial link to list_my_projects as the source of project_id, leaving a gap an agent must guess at.

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 0% for the single required project_id, and the description never explains the parameter, its expected format, or where the agent obtains the ID. The phrase 'one of the user's GoNoGo projects' weakly implies an ownership constraint, but that is all the compensation offered for a fully undocumented parameter.

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: it returns the GO/NO-GO verdict and score for one GoNoGo project. It also names the alternate outcome (research still running), which is more precise than the title alone. It does not explicitly contrast itself with siblings like list_my_projects, so it stops 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?

Usage is only implied: the agent infers this is the call to make after learning a project exists, and the note that 'full reports are on the project page' scopes what this tool is not for. There is no explicit when-to-use vs. when-to-use list_my_projects or interview_with_alex.

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 set readOnlyHint=false and idempotentHint=false, and the description goes well beyond them: it discloses that the call creates a project on the user's account, that a live voice/video session follows, and gives an operational rule ('The user taps Start and talks; stay silent while the interview runs'). That interaction guidance is exactly the kind of behavior annotations cannot express.

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-loaded with the core action, then scope, then usage trigger, then operational caveat. Every sentence carries information, though the parenthetical 'a talking video avatar' is decorative and the flow/verdict detail could be trimmed.

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?

An output schema exists, so return values need not be explained, yet the description still tells the agent what the user ultimately receives (a researched GO / NO-GO verdict). Combined with the account-creation side effect and the silent-during-interview rule, an agent has everything needed to invoke 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 description coverage is 100% and both parameters are optional and self-documented ('idea in the user's words', ISO 639-1 'language'), so the schema already carries the meaning. The description adds no format or default detail for either parameter, which is the baseline-3 case.

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?

Names a specific action (opens a live voice interview with Alex, GoNoGo's AI mentor) plus the downstream outcome (market research and a GO / NO-GO verdict). It is clearly distinguishable from the read-oriented siblings (get_project_result, list_my_projects, whoami) because it is the only tool that initiates the interview flow.

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?

Explicitly states the trigger condition: 'Use it when the user wants to validate, test or pressure-test a startup or business idea.' It gives clear context but no exclusions or named alternative, so an agent cannot tell from the text what to do if the user instead wants to resume or inspect an existing interview.

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, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds useful substance by saying what each row conveys (verdict plus whether research is still running), which hints at non-final/in-progress states, but says nothing about pagination, ordering, or result size.

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 sentence that front-loads the verb and resource and then specifies the returned fields. Every clause earns its place with no 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 parameters, an output schema present to describe the return shape, and annotations covering the safety profile, the description does everything an agent needs before invoking it. Only the absence of any filtering/pagination expectations keeps it off a 5.

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 there is no parameter semantics burden; the baseline for a no-parameter tool is 4. Nothing in the description misleads about inputs.

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 (Lists) and resource (the user's GoNoGo projects), plus the salient return fields (GO/NO-GO verdict and running status). The purpose is unambiguous, though it never names or contrasts with siblings like get_project_result, which is the one thing missing for 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?

The possessive 'my' implies a personal-scope listing, and the purpose makes the use case self-evident, but there is no explicit statement of when to call this versus get_project_result for a single project's result. Usage is implied rather than guided.

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, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered and an output schema handles return values. The description's only added behavioral detail is that the account is the one 'connected to ChatGPT,' which clarifies the auth/session scope but nothing about failure modes when no account is linked.

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 sentence with no filler, and the resource ('GoNoGo account') is front-loaded immediately after the verb. Every word 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-parameter identity tool with an output schema and full annotation coverage, the description is essentially sufficient. It could add one clause on what happens when no GoNoGo account is connected, which is the only realistic edge case an agent would need.

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 there is nothing for the description to disambiguate and the baseline of 4 applies. The description correctly implies no input is required.

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 and resource: 'Returns the GoNoGo account.' This is clearly distinguishable from list_my_projects and get_project_result, which operate on projects rather than identity. It stops short of 5 because it doesn't explicitly contrast itself with the siblings that also return account-scoped data.

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 or when-not-to-use guidance and no alternatives are named. However, 'whoami' plus 'account connected to ChatGPT' makes the intended invocation context (establishing caller identity) strongly implied, which lands at minimum-viable rather than absent.

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