Developh

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 that only *published* projects are returned and that each entry includes a link, which is useful beyond the annotations, but says nothing about ordering, result size, or how locale affects output.

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 with the resource statement front-loaded and the filtering behavior second. It slightly restates enum values already present in the schema, which is minor waste but aids scanning.

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-required-parameter read-only listing tool with no output schema, the description covers what is returned (published case studies with links) and how filters behave. Only interaction between the two filters and the locale effect are 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% and all three parameters are enums with their own descriptions, so the schema carries the weight. The description echoes the sector and service enum values (slightly differing in spelling: 'online stores' vs 'online-stores') but adds no semantics about combining filters or the purpose of `locale`.

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 and scope ('Published client work by Developh with links to each case study'), so an agent knows exactly what is returned. It does not need to differentiate from siblings (contact, audit, studio info) since they are unrelated, but the sentence itself is unambiguous.

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 describes both modes: filter by sector or service to narrow results, and 'with no filter, lists every published project' for the unfiltered case. No when-not or alternative-tool routing is offered, but for a small three-sibling toolset there is little to route to.

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 declare openWorld and non-destructive but not the human consequences; the description adds them — a confirmation email goes to the person and the team replies in 2 to 8 business hours. It does not warn about duplicate submissions or what happens on failure, which matters given idempotentHint=false.

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 dense sentences, front-loaded with purpose followed by guardrails and expected outcome. No filler or repetition of schema details.

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 an 8-parameter, non-idempotent, open-world send tool with no output schema, the description covers intent, consent, and expected follow-up well. It stops short of describing the immediate return value or error behavior (invalid email, rate limits), which an agent would need to recover from failures.

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 baseline is 3, but the description adds meaning the schema lacks: the 'confirmed' flag is tied to showing the person the message first, and the message should be 'in their words'. That clarifies the semantic contract rather than restating field types.

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: sends a project inquiry or question to the Developh team on behalf of the person being helped. None of the siblings (list_case_studies, run_website_audit, studio_info) do this, so the routing is unambiguous.

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?

Gives an explicit precondition ('only when the person explicitly asked to contact Developh and gave you their own name and email'), an explicit prohibition ('never invent or guess contact details'), and a procedural rule ('show them the message before sending'). An agent knows exactly when this applies and when it does not.

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, openWorldHint=true and destructiveHint=false, so the safety profile is covered elsewhere. The description adds genuinely new behavioral context: expected latency of 20-90 seconds and the public-URL-only constraint, which explains why a call may be slow or rejected. It doesn't describe failure behavior beyond the address restriction, which keeps it short of a 5.

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, each load-bearing: what it does, how long it takes, and what it will refuse. The capability and its return surface are front-loaded before the operational caveats, 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?

There is no output schema, and the description compensates by enumerating the audit's returned dimensions in reasonable detail, so an agent knows what comes back. The remaining gap is minor: nothing is said about how failures or low-score results are surfaced, but the latency and eligibility constraints cover the practical essentials.

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 the url and locale parameters are already documented in the schema. The description reinforces "public website" and pins the audit to mobile (a fixed, non-parameter choice worth knowing), but adds nothing about the locale parameter's effect on output language. Baseline 3 applies when the schema does the heavy lifting.

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 ("Runs a Google PageSpeed Insights audit of a public website on mobile") and then enumerates the exact dimensions returned: performance, accessibility, best-practices, SEO, Core Web Vitals, weighted issues, security headers and page weight. Nothing in the sibling set overlaps, and an agent knows precisely what capability it is invoking.

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?

Gives concrete runtime ("20 to 90 seconds") and a hard scope constraint ("Only public http(s) addresses"), which functions as an exclusion. There is no explicit when-not guidance, but the sibling tools (list_case_studies, request_contact, studio_info) are unrelated so no alternative routing is needed.

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 the useful content disclosure (what facts are included) but nothing about response shape, size, or whether sections are conditionally present. With annotations carrying the safety burden, this is 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?

One front-loaded sentence with no filler; every listed item helps an agent judge relevance. The long enumeration is dense but each clause earns its place, though a short lead-in naming the tool as the general entry point would improve structure.

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 read-only, single-optional-parameter info tool with no output schema and full annotation coverage, the description is nearly sufficient: it tells the agent what domains of information exist. What remains unstated is whether all sections are always returned and how large the response is.

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 the single locale parameter is fully documented in the schema with an enum and default. The description adds nothing about the locale (e.g., that Portuguese answers draw on the same underlying data), 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 resource (the Developh studio profile) and enumerates the facts it contains: address, team, services, sectors with case studies, pricing, contact. It is clear what the tool returns. However, it does not differentiate itself from siblings like list_case_studies or request_contact, whose subject matter it explicitly overlaps with.

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 routing to alternatives. An agent could infer this is the general-purpose profile call versus the more targeted siblings, but the description never says so, leaving the choice between studio_info, list_case_studies, and request_contact to guesswork.

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