Mini Split Reef

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

With no annotations, the description carries the full burden. It hints at the payload ('local housing facts when available') but never states that this is a read-only lookup, what happens if both zip and city are supplied, whether the check can fail for malformed input, or what an out-of-area result looks like.

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 well-formed sentence with the resource and the returned value both front-loaded. Nothing is padded, though the terseness comes at the cost of leaving core semantics unstated.

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?

A zero-required-parameter lookup with no output schema and no annotations needs more than one sentence; the description omits which of zip/city is mandatory or sufficient, and only vaguely gestures at return content. An agent cannot reliably construct a valid call from this alone.

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% and both parameters are undocumented in the schema. The description names 'ZIP code or city', which maps loosely to the two fields, but supplies no format, precedence, or mutual-exclusivity semantics. Note the 'or' hints at alternatives while the schema permits both simultaneously without resolution.

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 check against a named resource (service area) keyed by ZIP code or city, which an agent can distinguish from the quote/pricing siblings. The verb is implicit ('whether ... is in') but the outcome 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?

No when-to-use guidance, no prerequisites, and no mention of the sibling tools it naturally precedes (estimate_job, get_pricing). An agent must infer that this is a qualification/gate step rather than an action tool.

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?

No annotations are provided, so the description carries the full behavioral burden. It implies a computation returning an installed price but does not state whether this is read-only, whether it creates or persists anything, or how it relates to the separate request_quote action. For a tool with zero annotation coverage this is a notable gap.

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 short sentence with the key concept front-loaded and no padding. It is a grammatical fragment rather than a full clause, but nothing is wasted.

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 one-parameter tool this is close to adequate, but the description promises 'with the financing option' while the schema exposes only 'zones' and no financing parameter, leaving ambiguity about what the estimate includes. It also never hints at the shape of the returned price (single number, range, breakdown).

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?

With a single parameter at 100% schema coverage, the schema already documents 'zones' including its range. The description's '(indoor units)' gloss matches the schema description and adds no new format or constraint information, 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 states a specific output (installed price) driven by a specific input (number of zones / indoor units), and the title supplies the verb 'Estimate' for a job. It is reasonably distinct from get_pricing and request_quote, though the mention of 'financing option' blurs the line with get_financing.

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 use estimate_job versus the sibling tools get_pricing, get_financing, or request_quote, nor any stated prerequisites. The agent must infer the routing entirely from tool names.

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?

No annotations are provided, so the description carries the full behavior burden. It discloses key assumptions ($2,000 down, 10% APR fixed, 40-50 months, on approved credit), but does not state read-only status, side effects, or whether the result is an estimate versus a firm offer.

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 front-loaded sentence that states the output and the exact financing terms without any wasted words.

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 calculator with no output schema and no annotations, it communicates the return value and core assumptions. It still lacks parameter boundary details and safety/read-only context that would make it fully self-contained.

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%, so the description must compensate. It relates price_usd to a 'system price' and mentions the 40-50 month range, but omits the price range, optionality of months, and explicit parameter naming.

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 the specific resource and output: a monthly payment calculated from a system price under fixed financing assumptions. It does not, however, distinguish this from sibling tools such as get_pricing or request_quote.

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. The agent must infer that this tool is for financing estimates rather than pricing or quoting.

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?

No annotations exist, so the description carries the full burden. It does disclose that prices are 'posted' and 'installed' and that inclusions are covered, but says nothing about currency, regional variation, freshness, or whether the read requires any prerequisites. Adequate but thin for a tool with zero annotation coverage.

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 short sentence with no filler and the key qualifier ('installed') front-loaded. It is efficient, though the brand prefix occupies space that could carry more useful scope 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 tool this is close to sufficient, but with no output schema the description should at least sketch the return shape. Saying only 'what they include' leaves the structure of the pricing data unspecified.

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 per the rubric the baseline is 4. There is nothing for the description to clarify beyond what an empty schema already conveys.

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 (Mini Split Reef's posted installed prices) and adds scope detail about inclusions. It implicitly distinguishes itself from estimate_job and request_quote by framing these as posted/fixed prices, but never names those siblings explicitly.

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 when-to-use guidance and no mention of the alternatives (estimate_job, request_quote, get_financing) that an agent must choose between. Usage is only weakly implied by the word 'pricing'.

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?

With no annotations, the description carries the full burden, and it does disclose the key behavioral fact: this dispatches a request to humans ('the crew') rather than computing a result, and it is consent-gated. It stops short of describing what happens after submission, whether repeat calls are deduplicated, or how the request is stored.

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 tight sentences with the action front-loaded and the constraint second. No filler, no restated title.

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 side-effecting, six-parameter tool with no annotations and no output schema, the description covers the trigger condition well but leaves the post-submission behavior, the meaning of the quote fields, and the lack of a documented return unaddressed.

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 0% across six parameters, and the description only gives semantics for phone/email by tying them to user consent. zip, rooms, and zones are undocumented in both schema and description, so it only partially compensates for the gap.

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 — sending a mini split quote request to the crew — which is distinguishable from the informational siblings (get_pricing, estimate_job, check_coverage). It does not name a sibling directly, but the dispatch-oriented framing is clear enough to separate it.

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?

Provides an explicit gating condition: only when the user explicitly asks to be contacted and supplies their own phone or email. This is a real when-to-use rule with an implicit exclusion (do not fire it unprompted), though it never names an alternative tool.

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