PanelCompare

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description adds genuine behavioral detail beyond that: results are ordered cheapest first, the response includes a market index with median/quartiles/quotable extremes, and quotes are per 1,000 units.

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 dense sentence that front-loads the core answer and then appends ordering, index contents, and slug discovery. Every clause carries information, though the sentence is long enough that the guidance clause risks being skimmed.

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, the description does a fair job of sketching the return (sellers, price per 1,000, index statistics). It leaves the max-result behavior (limit up to 50), the trust-score filter, and any pagination unaddressed, which an agent would need to infer from the schema 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 coverage is 60%, and the description clarifies the two slug parameters (via list_services) and the price-unit normalization, plus the implied sort order. But limit and minTrust have no schema description and no mention in the description, so the gap is only partly compensated.

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+resource: it returns sellers of one service with price per 1,000, sorted cheapest first, plus a market price index. This is concrete enough that an agent can distinguish it from the more aggregate-sounding get_price_index and market_stats 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?

It gives one explicit prerequisite route: "Use list_services for valid platform and service slugs." However, it never says when to prefer this over the closely related get_price_index or search_panels siblings, so the primary when-to-use decision is left implicit.

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 establish read-only, idempotent, non-destructive, closed-world behavior. The description adds valuable return-content context—trust scores with evidence, uptime, features, payment methods, supply chain, cheapest listings and medians—though it does not cover error or pagination 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, front-loaded with the core purpose and tightly enumerating relevant return fields; the second sentence gives the input-source instruction without 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 small read-only lookup with rich annotations and complete parameter schema, the description adequately explains what the response contains. Minor gaps remain around error handling and how the services count affects pagination, but no output schema exists to carry that burden.

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 the schema documents both parameters. The description adds meaning by specifying that the slug should come from search_panels and that the service listings are cheapest listings with market medians.

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 identifies a single panel's full profile and enumerates the returned data categories, making the resource and scope clear. It references search_panels for the slug but does not explicitly contrast with all siblings such as compare_service_prices or list_services.

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 sentence 'Use the slug from search_panels' gives clear context: this is a detail lookup following search. It does not state when not to use it or name alternatives like compare_service_prices, so it lacks exclusions but provides usable workflow guidance.

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, so the safety profile is covered. The description adds genuine context the annotations cannot: it enumerates the returned statistics, states freshness ('latest daily'), the normalization basis (per 1,000), and the panel-count inclusion — all without an output schema to lean on.

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 resource and freshness, then lists the metrics and the optional filter. No filler; every clause carries information.

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, the description competently explains return contents (median, quartiles, extremes, panel counts) and recency. Minor gaps remain — currency/unit normalization for 'per 1,000' and whether aggregation is per service — but an agent can call it correctly.

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 parameter's description already says 'Platform slug, e.g. "youtube". Omit for all.' The description only echoes this with 'Optionally one platform only', adding no format or scope detail beyond the schema. Baseline 3 for a fully documented 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+resource and enumerates the returned metrics (median, quartiles, cheapest/dearest per 1,000, panel count) plus 'latest daily', so an agent knows exactly what this returns. It does not, however, distinguish itself from siblings like compare_service_prices or market_stats, which likely overlap.

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?

'Optionally one platform only' implies the filtering use case, but there is no explicit when-to-use, when-not-to-use, or routing to compare_service_prices / market_stats for cross-service comparison. Usage is only inferable.

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, openWorldHint=false and destructiveHint=false, so safety is covered. The description still adds value by specifying that this is the canonical/full catalog and by listing the return fields in the absence of an output schema. It does not mention pagination or ordering, which keeps it below 5.

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 with the resource and its returned fields front-loaded; no filler. The parenthetical field list makes the sentence long but every clause carries information.

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-parameter, read-only list tool with no output schema, the description supplies the return shape and the scope, which is the main thing an agent needs. Missing only ordering/pagination details, which are minor here.

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 single parameter is documented as "Platform slug, e.g. 'tiktok'. Omit for all." The description's "optionally for one platform" merely restates that behavior, so the baseline of 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 the resource (the canonical set of services PanelCompare tracks) and enumerates the fields returned (platform/service slugs, unit, reference price range), which lets an agent tell it apart from compare_service_prices or get_price_index. The verb is only implied by the name, but the scope 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?

"Optionally for one platform" implies the filtering behavior but there is no explicit when-to-use guidance and no sibling is named as an alternative. An agent can infer this is a catalog lookup that should precede compare_service_prices, but that routing is left to inference 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 readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is clear. The description adds value by naming the aggregate metrics returned, but it does not mention data freshness, cache behavior, or response shape, which leaves some behavioral 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?

The description is a single, front-loaded sentence that lists the key metrics without filler. Every phrase contributes to explaining what totals are available.

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, no output schema, and strong annotations covering safety, the description carries the main burden of explaining return values. It does this by enumerating the included metrics, though it stops short of describing the response structure or freshness.

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, which is the baseline 4 case. There are no parameter semantics for the description to clarify, and the schema has 100% coverage for the empty object.

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 clearly identifies the resource as market totals and enumerates the metrics returned: panels tracked, platforms, canonical services, listings, and the cheapest quotable rate. It is more specific than the title alone, though it does not explicitly differentiate itself from siblings like get_price_index.

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 offers no explicit guidance on when to use this tool versus alternatives such as get_price_index or compare_service_prices. Usage is only implied by the word 'Totals', leaving the agent to infer that this is an aggregate overview 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?

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds useful behavioral context by specifying what comes back per result (trust score 0-100, overall score 0-10, 30-day uptime, PanelCompare page link), which matters since there is no output schema. It omits result-count/pagination behavior and any rate-limit or cost notes.

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, front-loaded with the verb and resource, then the filter/ranking options and return fields. No filler and no repetition of the 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?

With no output schema, describing the returned fields is exactly the right compensating detail, and the filter/ranking coverage is broad. Remaining gaps are modest: default and maximum result count, and what the sort modes actually mean, would let an agent call it correctly on the first try.

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 a high 71%, so the documented filter params (query, feature, payment, minTrust, platform) already carry their own examples. The description restates the filter dimensions but does not explain the sort enum values ('best', 'services', 'rating', 'newest' are not mapped to the described ranking by score/price/trust/uptime) nor the limit cap of 25, so it adds only marginal meaning.

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 ('Find SMM panels ... tracked by PanelCompare') and even glosses the domain term for agents unfamiliar with it, plus the ranking and filtering capabilities. It never names a sibling tool, so the agent gets no explicit contrast with get_panel or list_services, which keeps it short of a 5.

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?

'optionally filtered by platform, payment method, feature or minimum trust score' implies how to use the filters but gives no when-to-use guidance. There is no statement about when to prefer this over get_panel (single-panel lookup) or market_stats, and no note that all filters are combinable.

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