Lomen

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered; the description adds substantive context beyond that — the fixed 30-day lookback, that it draws on real account traffic (not synthetic data), and that the output is short and factual rather than a full report. It does not mention generation latency, cost, or non-determinism, which would be the remaining useful disclosures.

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 action, the output character (short, factual), the data source and window, and the three topics covered. Nothing is wasted and nothing relevant is buried.

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 no-parameter, read-only tool this covers source, scope, and content of the insight. With no output schema present, a brief note on the return shape (e.g., a prose string vs. structured fields) would have closed the last 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 zero parameters, so the baseline is 4. The description usefully explains why there are none: the window is fixed at 30 days and the account is implicit ("signed-in account"), pre-empting an agent from hunting for filter arguments.

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 artifact ("Generate a short, factual AI insight") plus the exact data basis: the signed-in account's real website traffic over the last 30 days, listing the three things covered (pageview trend, top source, unique visitors). It is clearly distinguishable from siblings like get_website_overview or investigate_traffic_day, though it never names a sibling explicitly to sharpen that contrast.

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 implied usage is clear enough — call this when you want a narrative summary rather than raw traffic data — and the 30-day window is stated. But there is no explicit "use this instead of get_website_overview when..." routing, and no note about whether it should be called repeatedly or cached.

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 the operation as read-only, idempotent, and closed-world, so the safety profile is covered. The description adds scope by specifying the signed-in user's plan and the returned fields, but does not describe authentication requirements, error behavior, or response structure beyond the listed values.

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?

It is a single, front-loaded sentence with no redundant clauses. Every element names a useful part of the response.

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 lookup with no output schema, the description is complete enough: it names the resource, scopes it to the signed-in user, and lists the key returned fields.

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 has zero parameters, so the baseline is 4. The description correctly focuses on what the parameterless call returns rather than implying any hidden filters or options.

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: get the signed-in user's subscription plan, status, and billing interval. It does not explicitly differentiate from sibling tools, but the purpose is unambiguous and distinct from the listed alternatives.

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?

Usage is implied by 'signed-in user's,' making clear this is for the current user's subscription rather than another user's. However, there is no explicit when-to-use guidance or mention of when not to use it versus alternatives.

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, openWorldHint=false, and idempotentHint=true. The description adds useful behavioral context beyond that: account scoping, the fixed 30-day window, 'real' traffic metrics, and the inclusion of current visitors, though it omits auth, rate-limit, or multi-site behavior details.

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 definition is front-loaded with the core purpose and contains no filler, but the metric enumeration is a single very long sentence. The length is mostly justified because there is no output schema to document return fields.

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 description does a good job enumerating what the overview returns and the time window. It is slightly incomplete about how the 'tracked website' is chosen when an account has multiple sites, which is relevant given the list_sites sibling.

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?

This tool has zero parameters, so parameter semantics are not a meaningful differentiator and the baseline is 4. The long list of metrics describes return values rather than input parameters, which is appropriate given the empty 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 specific verb and resource, 'get' and 'website traffic overview,' and scopes it to the signed-in account's tracked website over the last 30 days. It clearly distinguishes itself as a broad overview rather than a day-level investigation, though it does not explicitly name 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?

Usage is implied by 'overview' and the 30-day window, but the description does not explicitly say when to use this instead of investigate_traffic_day, generate_ai_insight, or list_sites. No exclusions or prerequisites are 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 only declare readOnly/idempotent/closed-world; the description adds substantive behavior the agent could not otherwise know: same-weekday multi-week baseline, drivers split into visitors vs pages-per-visitor, per-source/URL/landing-page/UTM attribution with shares, and explicit reporting of unattributable traffic. It also sets an interpretive contract — correlation is labelled correlation, never causation.

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?

Front-loaded with the core purpose and then builds the methodology in one coherent block; every clause (baseline week, unusualness, driver split, attribution breakdown, attribution limits, correlation caveat) carries distinct information. It is somewhat dense and could be tightened, but nothing is padding.

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?

No output schema exists, so the description must convey what comes back — and it does: comparison against prior same weekdays, a measure of unusualness, driver decomposition, per-dimension share attribution, and explicit no-attribution cases. Combined with annotations covering the safety profile, an agent has everything needed to call and interpret it.

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 single 'date' parameter already documents the YYYY-MM-DD format and the site-time-zone default. The description adds only the implicit site-time-zone framing, which the schema states more precisely, so 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 ('Explain why traffic on one day differed from usual') scoped to the signed-in account's tracked website. It is clearly distinguishable from siblings like get_website_overview (summary metrics) or generate_ai_insight (generic AI narrative) because it names the comparison baseline and decomposition dimensions.

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 trigger condition is clear: use it when you need to explain a single day's deviation from normal traffic. It does not name specific alternatives or state when-not-to-use (e.g. for multi-day or aggregate analysis), leaving that inference to the agent.

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 and openWorldHint=false, so safety behavior is covered. The description adds real scope context — the returned fields and the "one site per account in this version" limitation — but says nothing about ordering, latency, or auth requirements.

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 resource and return payload, with no filler. The trailing "One site per account in this version" is slightly ambiguous in wording but earns its place as a scope caveat.

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 with no output schema, the description supplies the key information an agent needs: what is listed and the fields returned. The missing piece is routing guidance versus the sibling overview tools, which matters given four siblings.

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 does not misleadingly suggest any filtering options, which is consistent with the empty 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 ("List the websites tracked in this Lomen account") and enumerates the returned fields (domain, id, added date), so the agent knows exactly what it retrieves. It does not, however, distinguish itself from the sibling get_website_overview, which an agent may reasonably confuse with per-site 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?

Usage is implied by the name and scope (enumerate sites in the account), but there is no explicit when-to-use or when-not clause and no sibling is named as an alternative. The

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