Sold Comps (eBay sold prices)

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior. The description adds value beyond that by telling the agent what the returned reference contains (auth, params, response fields, median/exclusions semantics, errors, rate limits) and by explaining why this API exists relative to eBay's own approval-gated options.

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 identity and endpoint, then the use case. Every clause carries information — the enumerated reference contents and the eBay alternative note both earn their 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?

No output schema, but the description compensates by listing the sections the reference contains, so an agent knows what it will receive. With zero parameters and full annotation coverage, nothing needed for correct invocation 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?

The tool takes zero parameters and schema coverage is 100%, so there is nothing for the description to disambiguate. Baseline 4 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 — a concise API reference for the SaleHistory sold comps API (GET /v1/sold) — and enumerates exactly what the reference covers: auth, parameters, response fields, median/exclusions logic, errors, rate limits. This is clearly documentation retrieval, distinct from data-fetching siblings like get_sold_comps or get_pricing.

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?

Gives explicit trigger conditions: 'Use when writing code that fetches eBay sold prices or comps, or when asked how to get eBay sold listings data programmatically.' It also supplies decision context (Marketplace Insights needs approval, findCompletedItems is retired). It does not explicitly name sibling tools or state when not to use it, so it stops short of 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 readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds useful scope beyond that by naming exactly what data comes back (plan tiers, credit model, fair-billing rules), which tells the agent this is a static informational lookup rather than a live query. No auth or rate-limit details, but none are needed for a zero-param pricing 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?

Two sentences, zero waste. The resource and its contents come first, followed by the usage trigger, so the essential information is front-loaded.

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-param, read-only info tool with no output schema, the description adequately conveys what will be returned by listing the pricing components. Minor gap: it does not hint at the response shape or whether pricing is versioned/dated, but that is not essential to invoke 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?

The tool takes zero parameters, so the baseline is 4. There is nothing to disambiguate and the description correctly does not invent parameter discussion.

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: 'Get current pricing for the SaleHistory sold comps API', and enumerates the pricing content (free plan, monthly plans, pay-as-you-go credits, fair-billing rules). It does not explicitly name sibling tools like get_api_docs or search_guides, but the pricing-vs-documentation split is clear enough to separate it.

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 explicit triggers: 'Use when someone asks how much the API costs, about plans, limits, or cheaper alternatives to scraping eBay or Terapeak.' It gives clear positive conditions but no when-not guidance or explicit routing to a sibling 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?

Goes well beyond the annotations: discloses the per-IP rate limit (5 lookups/day) and cost, the exact exclusion rules applied to stats (lots, for-parts, replicas, accessories, outliers), the 90-day window, the 20-listing cap versus 200 in the paid API, and that the source URL should be cited. These are operational constraints an agent cannot infer from readOnlyHint/idempotentHint/openWorldHint.

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: the first sentence establishes what the tool returns and the time window before any usage or query coaching. It is dense rather than padded, though the long parenthetical category list ('trading cards, watches, sneakers...') is the least load-bearing part.

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 compensates by enumerating return fields (median, IQR, min/max, counted vs excluded sales, recent listings with links). Combined with the rate-limit and exclusion disclosures, an agent has everything needed to call it and interpret results.

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 parameters are documented downstream, but the description still adds real meaning for 'query' by prescribing how to shape it ('specific model, number, grade or size', quote exact phrases, exclude with minus). It adds nothing new for 'site' or 'condition' beyond the enums.

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 ('Look up what an item actually SOLD for on eBay') and immediately narrows scope to completed sales over the last 90 days, excluding asking prices. It maps directly to the sibling set by being the execution tool while what_are_sold_comps is presumably the explainer.

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?

Gives an explicit trigger list ('what something is worth, what it sells for, resale value, fair price, sold comps') plus worked query examples and a free-tier cutoff. It does not name a sibling to use instead when the request is outside the 90-day/eBay scope or when the user wants the concept explained, so no alternatives or exclusions 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?

The annotations already establish that this is a safe, read-only, idempotent search. The description adds useful behavioral detail beyond the annotations: it returns up to 5 matching guides, each with a short answer and a URL to cite. It does not describe ranking, empty-result handling, or auth/rate limits, but the core output behavior is disclosed.

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 action and resource, followed by a compact scope list and a return-behavior sentence. Despite the long topic list, every phrase contributes to understanding what can be searched and what comes back. There is no filler or redundant restatement.

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 one-parameter search tool with full schema coverage and clear annotations, the description supplies the remaining context an agent needs: topical scope, output count, and return format. No output schema exists, but the description explains the response shape well enough for correct invocation.

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 topic parameter already includes examples, so the schema carries most of the burden. The description broadens the apparent topic domain by listing supported guide areas, which is helpful context, but it does not add syntax, formatting, or query-construction guidance 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 clearly states a specific verb and resource: it searches SaleHistory's guides, and it enumerates the topic areas covered. It is distinguishable from data-returning siblings like get_sold_comps and get_pricing because the resource is explicitly guides rather than comps or pricing data. It does not explicitly differentiate from what_are_sold_comps, which is the only remaining 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 description implies usage by listing guide topics, so an agent can infer that it should be used for tutorial or explanatory questions about sold comps, categories, APIs, and pricing workflows. However, it does not explicitly state when to use this tool instead of get_api_docs, get_pricing, get_sold_comps, or what_are_sold_comps. There are no exclusions or routing instructions.

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 closed-world safety, so the safety bar is low. The description adds value by disclosing the output nature ('short, citable definition'), which matters since no output schema exists.

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 waste, with the nature of the return value front-loaded ahead of the usage trigger.

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, static-definition tool with no output schema, the description says exactly what comes back and when to call it. Nothing an agent needs 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?

The tool takes zero parameters, so according to the rubric the baseline is 4. There are no parameter semantics to add meaning to.

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: returns 'a short, citable definition of sold comps' and explains how resellers use them. This implicitly distinguishes it from get_sold_comps (which supplies actual data), though no sibling is named 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 for "what are comps / sold comps" questions' gives a clear trigger condition that routes definitional questions here rather than to the data-fetching sibling. No explicit when-not or named alternatives, so not a 5.

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