Acoustic Sound Panels

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds value beyond that by disclosing the computation basis (plain rectangular room), that results are planning estimates, and that a human-reviewed layout exists separately — exactly the kind of expectation-setting an agent needs before quoting numbers to a user.

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 purpose and inputs are front-loaded in the first two sentences, then outputs, then caveats in a logical order. It is a bit conversational ("Find out how much echo...") and could tighten phrasing, but no sentence is 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, so the description carries the return-value burden — and it does, naming the echo time in seconds, a plain-language speech rating, and the suggested coverage share. Combined with the estimate caveat and the escalation path to a Free Room Analysis, an agent has everything needed to call and interpret this 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?

Schema description coverage is 100% and every parameter carries units, ranges and the enum of room uses, so the description's restatement of length, width, ceiling height in feet and room use adds little. The one genuinely additive semantic is the implicit rectangular-room constraint on the dimensions. Baseline 3 is appropriate when the schema already does the parameter work.

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 estimation task: predicting echo (reverberation) time and the share of wall/ceiling that should be covered. It names the outputs and the rectangular-room assumption, so an agent knows exactly what comes back. It stops short of explicitly contrasting itself with asp_recommend_panels, which also deals with panel coverage, so the sibling boundary is only partly drawn.

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?

"These are estimates for planning" sets the appropriate context, and the closing line points to asp_start_free_room_analysis as the path when a vetted layout is needed. That gives a real use/don't-rely-on-this-for distinction. It does not say when to prefer this over asp_recommend_panels or what to do if dimensions fall outside a rectangular room, leaving some routing 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, idempotentHint, openWorldHint=false and destructiveHint=false, so safety is covered. The description adds the useful context that a link is tied to a Free Room Analysis request, but it omits whether the link expires, is single-use, or is reusable, which matters for a link-generating tool.

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 with no clear front-loading: the opening sentence leads with vague framing ('a way to capture a room') instead of the concrete action (returns a scan/upload link). The second sentence mixes in promotional information about a Free Room Analysis request.

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 and no parameters, the description carries the full burden of explaining the returned link and its lifecycle, and it does not. An agent cannot tell from the description what to do with the result or how the link relates to asp_start_free_room_analysis.

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 no parameters, so the baseline is 4. There is nothing for the description to disambiguate beyond the schema's empty object.

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 says it will 'Get a way to capture a room' and mentions an app plus a personal link, but it never states plainly what the tool returns (a URL? a token? instructions?). It is distinguishable from the compute/recommend siblings only by implication, not by an explicit statement of the deliverable.

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 guidance on when to call this versus asp_start_free_room_analysis or the other siblings, no prerequisites, and no exclusions. The mention of LiDAR/Pro-device requirement comes across as marketing copy rather than an explicit usage condition.

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 read-only, idempotent, non-destructive and closed-world behavior, but the description adds real behavioral context beyond them: the panel count is a 'starting' plan, echo is estimated before and after, prices are exact only 'when they are available', and panels are priced as Burch Fabrics Prime Time while other fabrics are priced elsewhere. That pricing caveat is exactly the kind of disclosure annotations cannot carry.

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 outcome and followed by inputs then outputs, so the agent learns what it gets before what it needs. The final fabric-pricing sentence is a useful caveat, though it is slightly dense and could be tighter.

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 carries the return-value burden and does so: it enumerates panel size and count, echo before/after, exact prices, shipping statement and product link. Combined with 100% parameter coverage and a full annotation set, the only soft spot is that it doesn't clarify how authoritative or approximate the recommendation is beyond the word 'starting'.

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 units, ranges and an enum already documented, so the baseline is 3. The description reinforces units (feet) and the room-use input but adds no format, precision, or edge-case guidance beyond the schema.

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 first sentence states a specific outcome — planning panel count and current cost for a room — with a clear verb-plus-resource framing that an agent can map to a task. It is distinguishable from asp_calculate_room_acoustics in spirit (panels + pricing vs. raw acoustics), but it never names the sibling, so the 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?

The description tells the agent what inputs to supply ('length, width and ceiling height in feet and what the room is used for'), which implies the calling context. It gives no explicit when-to-use versus asp_calculate_room_acoustics or asp_start_free_room_analysis, and no when-not conditions, leaving routing 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 mark this as a write (readOnlyHint=false, non-idempotent), and the description adds genuinely useful context beyond them: PII is shared with a named third party, nothing is charged, and a new request returns a personal upload link while repeat requests may not. It stops short of stating rate limits or what an existing/duplicate request returns exactly.

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 tight sentences: what it requests, what to gather first, what it does not do, and what comes back. Front-loaded with the action and deliverable, 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 ten required-ish parameters, no output schema, and a third-party data handoff, the description covers both the intake requirements and the return shape. Minor gaps: it doesn't explain what happens if the person later adds photos/dimensions, or how the personal link expires.

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 ten parameters (including units, ranges, and the consent constraint) are already documented. The description only re-mentions name, email, ZIP and consent in conversational terms, adding little format or semantic detail the schema lacks; 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 ('Ask ... for a Free Room Analysis') and defines the deliverable precisely: a recommended layout plus one written quote. The output description ('a personal link for adding photos, room dimensions or a short video') further separates it from the calculation/recommendation siblings.

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 explicit preconditions — collect first name, email, ZIP, and a clear yes to third-party sharing before calling — plus reassurance that nothing is ordered or charged. It does not name the sibling tools (e.g. asp_calculate_room_acoustics) or say when a public analysis request is the wrong path versus those alternatives.

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