Quotalis

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 well: it discloses the precise checks run and the shape of the result (0-100 score with per-check findings and fixes), which conveys that this is a read-only diagnostic rather than a mutation. It omits rate limits, whether results are cached, and any auth/host restrictions, so it is not fully transparent.

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 front-loaded sentence that packs in the action, the checks, and the return shape, plus a short reference link. Dense but not padded; the enumerated checks are the one slightly list-like element that could be trimmed.

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 usefully compensates by describing the return value (score plus per-check findings and fixes). Combined with the full schema coverage on the lone parameter, an agent has enough to invoke and interpret the tool; only rate-limit/auth behavior is left unstated.

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 there is a single parameter, so the schema already documents the accepted 'domain or URL' format. The description adds only the implicit 'public website' constraint, which is meaningful but marginal; 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 ('Run Quotalis's AI-readiness audit on a public website') and enumerates the exact checks performed (llms.txt, AI bot rules, sitemap.xml, JSON-LD, title/meta/canonical). This is clearly distinguishable from the sibling benchmark tools, which report historical/latest benchmark data rather than auditing a site.

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 scope constraint 'public website' implies usage, and the link to the equivalent free-audit page gives the agent a calibration point. However, it never states when to prefer this over siblings or what prerequisites/exclusions apply (e.g. no private/intranet hosts, no auth). Usage is implied rather than guided.

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 return ordering ('newest first') and content ('every tool named by each engine and every source cited'). However it says nothing about size, pagination, or cost of retrieving a 'full' history, which matters for a potentially large read.

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 sentence that front-loads the resource and folds ordering and payload contents in without waste. 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?

With no output schema and no annotations, the description correctly compensates by enumerating returned contents (per-engine tools, cited sources) and ordering. Only the absence of any guidance on volume/pagination keeps it from being fully complete.

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 there is nothing for the description to disambiguate; baseline 4 applies. The description correctly implies no filtering input is needed.

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 ('Get') and resource ('full dated history of weekly benchmark rounds') plus ordering ('newest first'). It implicitly contrasts with sibling get_benchmark_latest via 'history', but never names the alternative explicitly, so it stops 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?

There is no statement of when to use this tool versus get_benchmark_latest; the distinction (full history vs. most recent round) is left entirely to inference from the names. No prerequisites or context are given.

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 adds useful context: data provenance ('live free-tier tests by Quotalis') and refresh cadence ('updated weekly'). It stops short of describing latency, caching, or stability of the payload, so it is solid but not complete.

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 front-loaded sentence that names the resource and then enumerates the returned contents and source. Every clause earns its place 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?

For a zero-parameter, read-only tool with no output schema, the description does the heavy lifting by enumerating the return contents (recommended tools per engine plus consensus ranking) and the update cadence. It is complete enough to call correctly, though a bit more on freshness timing would fully close the loop.

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 nothing needs explaining beyond the schema. Baseline of 4 applies; there is no parameter-level gap to compensate for.

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 (Get) and resource (latest weekly benchmark round) and details exactly what the payload contains (tool recommendations from ChatGPT, Gemini, Perplexity plus a consensus ranking). It does not explicitly name the sibling get_benchmark_history, though 'latest' vs. 'history' is inferable from the names.

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 word 'latest' implies the current round as opposed to historical ones, so a competent agent can infer this is the tool for the most recent data. However, there is no explicit when-to-use statement or reference to get_benchmark_history as the alternative for past rounds.

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