PawLine Pet Guides

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

Annotations already declare read-only, idempotent, non-destructive behavior, so the safety profile is covered. The description adds useful context about what information is returned (description, trial terms, store links), though it does not discuss freshness or source authority.

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 are front-loaded with the primary payload and then the usage condition. Every phrase carries useful information with no redundancy.

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 informational tool with no output schema, the description fully explains what the tool returns and when to call it. An agent can invoke it correctly without needing additional context.

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?

There are zero parameters, so parameter semantics are not a concern. The baseline for a parameterless tool is 4, and nothing in the description creates 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 uses a specific verb ('Get') and names concrete resources: app description, trial terms, and store links. It clearly distinguishes itself from sibling tools like list_pawline_sites by focusing on official PawLine app metadata.

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 trigger: 'Use when someone asks what PawLine is or where to get it.' It does not name exclusions or alternatives, but the use case is narrow enough that guidance is effectively complete.

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 this as read-only, idempotent, non-destructive, and closed-world. The description adds useful behavioral context beyond annotations: it cites reference gestation ranges and warns that 'a calendar cannot confirm pregnancy,' clarifying the tool's limits. It does not describe the exact return format, but the simple calculator nature makes that less critical.

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 short sentences, front-loaded with the core calculation, followed by usage guidance and a limitation caveat. Every sentence adds value with no redundancy.

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 two-parameter calculator with annotations covering safety and no output schema, the description gives enough context to invoke it correctly. The only minor gap is that it does not explicitly state the shape of the returned planning window, though 'planning window' implies a date range.

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 50%, so the description needs to add meaning, and it does: it identifies both inputs (species and breeding date) and maps species to the relevant gestation ranges. The date format is already documented in the schema, so 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 states a specific verb and resource: calculate a planning window from a known goat or sheep breeding date. It names the species and gives the Penn State gestation ranges, making it clearly distinct from sibling tools like dog_years_calculator or horse_weight_estimate.

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 explicitly says when to use the tool: 'Use when someone asks when a goat or sheep might kid or lamb.' That is clear contextual guidance. It does not name alternatives or exclusions, but the use case is distinct enough that this is a minor gap.

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 this is a read-only, idempotent, closed-world, non-destructive computation, so the safety profile is fully covered. The description adds the actual algorithm used, which is genuine transparency about how the result is derived. It stops short of saying whether the result is rounded or how it is formatted.

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, front-loaded with the action and method, followed by the usage condition. Nothing redundant or 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?

There is no output schema, and the description never indicates what is returned (a number, a formatted sentence, a table?). For a trivial read-only calculator that is a modest gap, but the combination of an unexplained return value and an unmentioned months parameter leaves the definition only adequate.

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 both parameters are documented in the schema itself; the description adds the useful framing that age is fed into a log formula. However it never mentions the months parameter or how months and years are combined (presumably as a fractional year), so it does not add meaning 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?

States a specific verb and resource (convert a dog's age to human years) and pins down the exact method (UC Davis log formula), which no sibling tool offers. An agent can distinguish it from horse_weight_estimate or pet_cost_calculator immediately.

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?

"Use when someone asks how old their dog is in human years" gives an explicit trigger condition. It names no exclusions or alternatives, but none of the listed siblings is close enough to require disambiguation.

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 readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds genuinely new context beyond that: the deterministic formula and the accuracy limitation implied by the medication-dosing prohibition.

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 dense sentence that front-loads the action, units, and formula, then immediately qualifies with the safety exclusion. 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?

For a two-input pure calculation with no output schema, the description supplies method, units, and the output unit (pounds), and flags the one dangerous misuse case. 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 description coverage is 0%, so the description must carry units — and it does, specifying heart girth and body length are in inches, which is the critical ambiguity for both parameters. It stops short of describing measurement technique or plausible ranges, so not a full 5.

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 ('Estimate a horse's weight in pounds') and even gives the exact formula, so the computation is unambiguous. It is clearly distinguishable from the sibling pet calculators by species and method.

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 names the intended contexts ('records and nutrition discussions') and a hard exclusion ('never for medication dosing'), which is exactly the routing guidance an agent needs. It does not name a sibling alternative (e.g., a vet scale or a different tool), which keeps it just below a 5.

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 readOnly, idempotent, non-destructive and closed-world, so safety needs no restating. The description adds one useful trait beyond the schema — that the catalog is finite and fixed at 11 sites — but says nothing about ordering, stability or output shape.

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, front-loaded with what is returned and followed by when to call it. Nothing repeated from the schema or annotations.

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 and no output schema, the agent needs to know what comes back and why — the description covers both (site names plus coverage, used for routing). A hint about how results relate to search_pet_guides would close the remaining gap.

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 there is no parameter semantics to get wrong; baseline 4 applies. The description correctly signals a zero-argument call by describing a fixed catalog.

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 (List) and a specific resource (the 11 PawLine guide sites) plus the content of each entry, which no sibling tool provides. It doesn't name a sibling directly, but the phrase 'before searching' implicitly points at search_pet_guides.

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?

'Use this to pick the right site before searching' gives a concrete usage context and ordering relative to the search tool. It stops short of explicitly naming search_pet_guides or read_pet_guide as the follow-up, so the routing is implied rather than stated.

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 readOnly, idempotent, non-destructive and openWorld=false, so the safety profile is covered. The description adds useful provenance (ASPCA 2021 national averages) that signals these are rough US national estimates, but it says nothing about the shape of the result, and the 'per month' trigger is not backed by any stated monthly 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 sentences, no filler, with the purpose and the data source front-loaded and the usage trigger second. Every sentence earns its place.

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, zero-required-parameter, purely computational tool with no output schema, the description gives enough to call it correctly: what it computes, on what basis, and when to reach for it. Only the return structure and the all-defaults (0 pets) edge case are 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 100% and every parameter carries its own description and default, so the schema does the heavy lifting. The description only loosely gestures at the parameters ('first-year costs' hints at include_one_time) without adding format or behavior detail 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?

States a specific verb ('Estimate') and resource ('yearly and first-year costs of dogs and cats') plus the data provenance (ASPCA 2021 national averages). It is implicitly distinct from siblings like dog_years_calculator, though it doesn't name any sibling 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?

'Use when someone asks what a pet costs per year or month' gives a clear triggering context, which is more than most tools offer. It stops short of exclusions or naming an alternative tool when the question is about something else (e.g. lifespan or weight).

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, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds that each domain is rated 0-10 on a published scale, but says nothing about what the tool returns (total, per-domain output, verdict) or any interpretation threshold.

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: the identity/scale first, the usage trigger second. Nothing is repeated and 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 7-parameter scoring tool with no output schema, the description covers the inputs but not the result — an agent cannot tell whether it gets a single aggregate score, an itemized breakdown, or an interpretation of 'more good days than bad'. That missing return-value statement is the main completeness gap.

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%, so the schema gives only bare names and type 'number'. The description compensates well: it expands the acronym and assigns each of the seven required fields to a named domain, and specifies the 0-10 range that the schema omits. It leaves the polarity of 'hurt' (whether 10 means no pain) unstated.

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 (score) and resource (an older pet's quality of life) and names the exact instrument (the published HHHHHMM scale) with its seven domains spelled out. No sibling tool does anything similar, so an agent can select this without ambiguity.

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 second sentence gives a concrete trigger: 'Use when someone is tracking whether a senior pet still has more good days than bad.' That is a clear usage context, but there are no exclusions or pointers to alternatives (e.g., for general cost or lifespan questions where cost_calculator or dog_years_calculator would be right).

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 readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description still adds real context beyond them: the response is plain-text Markdown that embeds the guide's sources, which matters for accurate quoting. It does not say what happens on an invalid/short id or missing URL, but that is a minor gap against annotated behavior.

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: the first front-loads what is returned and in what format, the second gives invocation triggers. No filler, and the most decision-relevant detail (full text, Markdown, sources included) comes first.

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 two-parameter, no-output-schema read tool, the description covers purpose, format of the return, and when to reach for it. The main omission is failure/empty behavior for a bad id or URL, which an agent calling by URL could plausibly hit.

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 both parameters are documented in-schema, including the '.md version' URL variant. The description only faintly touches the params via 'when given a guide URL'; it adds no selector guidance such as whether id and url are interchangeable or which wins if both are supplied. Baseline 3 is appropriate.

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 (read) and resource (one full guide/blog post) with scope ('one full guide', not a list), and names the PawLine network. The return format (clean plain text Markdown, including sources) further separates it from search_pet_guides, which only finds guides.

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?

'Use after search_pet_guides, or when given a guide URL' gives two concrete trigger conditions and names the sibling that precedes it. It lacks an explicit exclusion (e.g. what to do if you only need a snippet or already have the content), so it stops short of a full when/when-not map.

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, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered. The description usefully adds that results are sourced guides with shareable links across a multi-site network, but says nothing about ranking, result shape, or pagination behavior beyond the limit param.

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, zero filler, with the resource scope and topic coverage front-loaded before the usage cue. Every phrase earns its place.

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 search tool with full schema coverage and rich annotations, the definition gives an agent enough to call it correctly. Minor gap: it doesn't clarify when discovery should escalate to read_pet_guide for the full guide content.

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%, including examples for query, site domain, and limit range, so the schema does the heavy lifting and baseline is 3. The description's topic list adds flavor about searchable subject matter but no syntax or format meaning 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?

States a specific verb and resource ('Search plain-language pet and animal care guides') plus concrete scope (PawLine's 11-site network) with an enumerated topic list. It implies discovery-versus-reading distinction but never names the sibling read_pet_guide as the alternative, so it stops just short of full sibling differentiation.

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?

"Use this when someone asks a pet care question" gives a clear triggering condition and adds the intent of finding shareable, sourced guides. It offers no explicit when-not-to-use or named alternatives, keeping it below a 5.

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 read-only, idempotent, non-destructive, closed-world behavior, so the description's added value is the AVMA grounding and the fact that scenario selection only layers extra items onto a base kit. It does not say what the returned checklist looks like (grouped list, sections), but that gap is minor given annotations cover the safety profile.

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, zero filler, with the capability front-loaded before the usage cue. Every clause earns its place.

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 one-optional-param, non-mutating content generator with no output schema, the description covers what it produces, the basis (AVMA), and when to call it. Only the shape of the returned checklist is left implicit, which is a small gap.

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 enum is already documented with 'omit for the base kit only'. The description's enumeration of blizzard/ice/hurricane/summer outage largely restates the enum values, adding only slight semantic color, 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?

Specific verb+resource: 'Build a pet evacuation kit checklist (AVMA-based)' with the exact scope of extras. It is clearly distinct from the surrounding calculators and guide readers, so an agent can tell it apart from every sibling without opening the schema.

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?

'Use when someone prepares for a storm or evacuation with pets' gives a clear triggering context and the scenario enumeration implies the four supported situations. There are no explicit exclusions or sibling alternatives named, but none of the siblings plausibly compete with a checklist builder.

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