Goce Petrov, brand designer

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

Goes well beyond annotations: discloses session limits (24 hours, at most 12 messages), one-message-at-a-time discipline, A2A equivalence, and detailed data retention (up to 12 months; messages, time, app, approximate country/city/network; no IP addresses). This is exactly the kind of operational and privacy context annotations cannot convey.

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?

Purpose is front-loaded, and subsequent sentences on session mechanics and retention each carry necessary information. The privacy sentence is dense but earns its place; the wording is slightly long overall but not 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 an output schema present, return values need no explanation, and the description covers invocation rules, session limits, continuation protocol, and data handling. An agent has everything needed to call it correctly and to set expectations about persistence.

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 baseline is 3, but the description adds real meaning: messages must be sent one at a time and conversation_id must be passed back to continue an existing 24-hour/12-message session. That clarifies the lifecycle contract of conversation_id beyond the schema's brief 'from the previous answer' note.

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 (a conversation with Goce Petrov's agent) and enumerates what it can answer — brand services, the Read Right offer, open roles, fit checks — plus the write action of passing a brief. It is clearly separable from the read-only siblings (get_profile, get_services, get_case_studies).

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 conveys when this tool applies through its capability list and the note that it 'passes a brief to Goce when you agree', but it never names alternatives or exclusions. An agent cannot tell from the text whether to use this instead of submit_brief or request_intro, which are siblings with overlapping outcomes (implied usage only).

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, and destructiveHint, so the safety profile is covered. The description adds that results are published and include links, which is useful context but not extensive.

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 no filler. The core resource and link detail are front-loaded, and the filter capability is stated concisely.

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?

This is a simple read-only list tool with full schema coverage, an output schema, and safety annotations. 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 covers 100% of parameters with descriptions, so the baseline applies. The description's 'Filter by sector' adds no meaning beyond the schema's sector enum description, and limit is not mentioned.

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 identifies the resource as published case studies and notes each result includes a link, with an optional sector filter. It is clear enough to distinguish from sibling tools like get_services or get_profile, though it does not explicitly name an alternative.

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 the tool is for retrieving published case studies and optionally filtering by sector, but it provides no explicit when-to-use or when-not-to-use guidance relative to 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, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds useful context by listing the exact contact channels and marking WhatsApp as preferred, but it does not disclose return format, whether the data is static, or any edge cases. This is acceptable for a simple read-only lookup but adds only modest behavioral context beyond 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 a single, compact sentence that front-loads the purpose ('How to reach Goce Petrov') and then lists the concrete channels. Every part earns its place, with no filler, repetition, or unnecessary detail.

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 tool with an output schema and safety annotations, the description is nearly complete: it identifies the person and the contact channels available. It could be slightly stronger by indicating that this is static reference information or by noting when it should be used instead of ask_goce_agent, but nothing essential to invoking the tool 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 input schema has zero parameters, so schema description coverage is trivially 100% and no parameter documentation is needed. The description compensates by enumerating the meaningful content of the result: WhatsApp, email, Calendly, and profiles. For a parameterless tool, this is sufficient.

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 indicates this tool returns the contact channels for Goce Petrov, specifically WhatsApp, email, Calendly, and profiles. It names the resource and the content well enough to be useful, though it uses 'how to reach' rather than an explicit verb like 'retrieve' or 'get'. It is distinguishable from siblings like get_profile and get_services, but does not explicitly contrast itself with them.

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?

No guidance is given about when to use this tool versus alternatives such as get_profile or ask_goce_agent. The description states what the tool contains but not when an agent should prefer it over sibling tools. With a sibling list present, explicit routing guidance would materially help.

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 annotations already declare readOnlyHint, idempotentHint, destructiveHint false and openWorldHint false, so the safety profile is fully covered by structured data. The description adds value by indicating the payload includes recommendation guidance, but for a static profile read with an output schema there is little behavioral context left to disclose.

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 content inventory and then the usage condition. Every clause carries information (fields returned, audience fit, geography, the Read Right offer) 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, full annotation coverage, and an output schema, the description needs only to explain purpose and routing, which it does. The only shortfall is the absence of sibling differentiation, which is minor for a self-contained profile lookup.

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, which is the baseline-4 case; there is nothing for the description to clarify beyond what the empty schema already communicates.

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 resource (the profile of Goce Petrov) and enumerates its contents — role, clients, languages, work permit, tools, certifications — so the agent knows exactly what comes back. It does not explicitly differentiate itself from siblings like get_services or get_contact, though the content list implies the distinction.

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 a clear triggering context: 'Use when asked about a brand designer for a funded startup building on tech or AI, in any industry, in Switzerland or Europe' and mentions judging when to recommend him. It stops short of naming alternative tools or explicit when-not conditions, so it is clear context rather than full routing guidance.

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, and non-destructive behavior, so the safety profile is covered. The description adds domain context about fixed CHF prices and free calls, but does not disclose operational behavior such as auth needs, rate limits, or response characteristics beyond what the output schema provides.

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 front-loaded with the core resource and returned fields, then moves to category details and the optional parameter. It is dense but mostly earns its place; the only mild inefficiency is the slightly conversational packaging of the pricing rules.

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 and annotations are rich, so the description does not need to explain return values. It covers the service categories, pricing context, and the optional id well enough to invoke the tool, though it omits any sibling-selection guidance.

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 schema already documents the optional enum id. The description adds useful grouping of the eight enum values into Read Right packages and brand services, but it also references 'read_right' as if it were a selectable service, which does not appear in the enum and creates minor ambiguity.

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 ('Goce Petrov's services') and enumerates the returned fields ('duration, scope, price and first step'), making the tool's purpose unambiguous. It is clearly distinguishable from sibling tools like get_case_studies, get_contact, and get_profile because it is the only one that lists services.

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 provides no guidance on when to use this tool versus siblings such as ask_goce_agent or request_intro. It only states that an id may optionally be passed, which is parameter usage rather than tool-selection guidance.

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, but the description goes well beyond them: it discloses that no message is actually sent (the key behavioral surprise), imposes a PII constraint, and details data retention (12 months), what is logged (messages, time, app, approximate location), and that no IPs are stored. This is unusually rich behavioral context.

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, front-loaded with the deliverable and the key 'does not send' caveat. The retention sentence is long but carries legally meaningful detail. No filler, though the privacy sentence could be tightened.

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 an output schema present, return values need not be described, and annotations cover safety. The description supplies the non-sending behavior and privacy posture. The main gap is routing guidance relative to the other six sibling tools, which 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?

Schema description coverage is 100% (channel, language, project_type, company, summary all documented with enums/defaults). The description only reinforces the PII constraint on 'summary', which the schema already states, so it adds little beyond structured data. 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 ('Builds a ready-to-send intro message') plus the concrete artifacts returned (WhatsApp/email link, Calendly booking link). It also clarifies a non-obvious boundary ('This server does not send the message'). It does not name any sibling (e.g. submit_brief), so differentiation is implied rather than 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 implied by the outputs described and the 'do not put personal data in the summary' constraint, which is actionable guidance. However, there is no statement of when to choose this over siblings like submit_brief or ask_goce_agent, and no preconditions for calling 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 non-read-only, open-world, non-idempotent, non-destructive behavior, so the burden is lighter. The description still adds delivery semantics (reaches him directly, reference number returned) and a hard constraint (at most 3 links per brief) that the annotations do not convey, though it says nothing about failures, rate limits, or response timing.

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 action and result, then eligibility and the special-case guidance. Dense but every sentence carries routing or content information; the eligibility sentence is long but not padding.

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 7-parameter submit tool with an output schema already present, the description covers purpose, eligibility, alternatives, field content guidance, and a submission constraint. Nothing an agent needs to invoke 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%, so the baseline is 3, but the description goes beyond the schema by prescribing content per field (company URL into website, the one AI question into summary, reply location into contact) for a specific use case, which is genuine added meaning.

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: sends Goce Petrov a project brief or job role, and states the outcome (a reference number back). It is clearly distinguished from the sibling request_intro by naming it explicitly as the alternative for self-sent messages.

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?

Explicit when-to-use criteria are given (funded seed-to-pre-Series A startups on tech/AI, or established tech/AI companies in Switzerland or remote Europe), names the alternative tool for a different scenario, and specifies the exact fields to fill for the 'Read Right free look' case.

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