KooLink URL Shortener

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

No annotations are provided, so the description carries the disclosure burden. It adds useful behavioral context: the link must be the user's own, and views are fraud-filtered. However, it does not disclose authentication requirements, error behavior for invalid codes, or whether the operation requires any special permissions.

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 compact and information-dense: purpose, scope, included metrics, and the intended user question are all covered in two sentences. Key facts are front-loaded and no words are 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 single-param, read-only analytics tool without an output schema, the description adequately explains what data will be returned and what the param means. It could be more complete by noting what happens for invalid/unknown codes or if authorization is required, but those are secondary for selecting and invoking the 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 coverage is 100% and the schema already documents 'code' as the short code. The description adds practical meaning beyond the schema by specifying 'the part after kool.ink/', making the expected value format concrete and unambiguous.

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 the specific verb 'Get view analytics' and the resource (the user's own KooLink short links). Names the concrete data returned: total/valid views, device/country/referrer breakdowns, and a 7-day trend, which clearly distinguishes it from the sibling tools list_links and shorten_url.

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 use case: 'Use this to answer how is my link performing.' This gives clear context for when to invoke. It does not explicitly name alternatives or exclusions, but the intended scenario is obvious against the sibling tools.

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 behavioral disclosure burden. It reveals the returned data includes valid view counts, that results are scoped to the user's links, and that they are ordered most recent first. This is sufficient for a simple read-only listing tool, though it does not describe edge cases like empty results or pagination.

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. The first sentence states the core behavior and ordering; the second provides the use case and sibling linkage. The most important information is front-loaded and 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 low-complexity tool with one optional parameter and no output schema, the description is nearly complete: it covers scope, content, ordering, and intended use. A minor gap is that it does not describe the exact response shape, but the listing nature of the tool makes that less critical.

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 schema already fully documents the single limit parameter with range and default, so the description adds no parameter-level meaning. Baseline 3 applies because the schema coverage is 100% and the description doesn't need to compensate.

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 and resource: 'List the user's short links with their valid view counts, most recent first.' It clearly states what is returned and the ordering, and it distinguishes itself from sibling link_stats by framing list_links as the survey-level tool and link_stats as the per-code deep-dive tool.

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 actionable guidance: use this tool 'to survey overall link performance or to find a code to dig into with link_stats.' This implies the when-to-use and points to a sibling alternative. It does not explicitly mention shorten_url or exclusions, but the context is clear enough.

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 provided, the description carries the burden of behavioral disclosure. It clearly states the core behavior (shorten and return a link) and mentions the service (KooLink). However, it does not disclose side effects like whether the link is stored, authentication requirements, or error behavior if the supplied handle is already taken. This is adequate but has clear gaps.

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 zero fluff. The core action and result are front-loaded in the first sentence, and the second sentence gives practical usage signals. Every word 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 3-parameter tool, the description covers what it does, when to use it, and what it returns. The lack of an output schema is mitigated by explicitly stating the result is a compact kool.ink short link. It could note error cases or handle conflicts, but those are secondary for typical invocation and are reasonably inferred from the schema.

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 the baseline is 3. The description's phrase 'long URL' adds slight context beyond the schema's 'destination URL,' and 'tidy link to share' hints at the use case, but no significant parameter-level meaning is added 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 description states a clear verb and resource: 'Shorten a long URL using KooLink' and explicitly names the outcome 'return a compact kool.ink short link.' It is instantly distinguishable from sibling tools link_stats and list_links, which imply different operations (statistics and listing).

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 gives explicit usage context: 'Use this whenever the user wants a shortened URL, a tidy link to share, or a redirect for a long destination.' It does not name alternatives or exclusions, but the sibling tools are so clearly different in purpose that little ambiguity remains.

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