SentientData Market Scan

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

With no annotations provided, the description carries the full transparency burden. It discloses that the output is an estimate, not financial advice, and that the calculation accounts for marketplace fees and optional shipping costs. It does not describe edge cases like missing market data, but the provided disclaimers add meaningful behavioral context.

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 three concise sentences: it states the core purpose, lists what the tool accounts for, summarizes the return values, and adds a disclaimer. No filler or redundant restatement of the tool name.

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 non-destructive estimation tool with fully described parameters and no output schema, the description gives enough context to call it correctly: required inputs are implied, optional inputs are mentioned, and the return content is summarized as profit and ROI. It lacks detail on output format or edge cases, but that is not critical for basic 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%, so the schema already documents all four parameters. The description adds a little semantic context by tying buy_price to the acquisition cost and fee_pct/shipping_cost to marketplace fees and shipping, but it does not need to carry the parameter documentation burden.

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: estimate resale margin using buy price and the current eBay market median. It names what the tool computes (profit and ROI) and distinguishes it from a generic price check. However, it does not explicitly differentiate from sibling tools like price_check or scan_deals.

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 context is implied: the tool is for evaluating a flip opportunity at a given purchase price. It does not explicitly state when to use this tool over siblings, nor does it mention exclusions or prerequisites. The guidance is present but not made explicit.

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 burden. It explicitly states this is a cached read refreshed every 20 minutes, and explains the scoring criteria, so an agent can reasonably infer that this is a non-mutating operation that may serve slightly stale data. It does not discuss rate limits or auth, but for a simple read tool this is strong disclosure.

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 concise and front-loaded with the core resource, then adds selection criteria, refresh frequency, and read behavior. The lane list is long but informative, and every clause contributes useful details.

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 read-only list with one optional filter, the description explains what is returned, how it is pre-scored, how fresh it is, and that it is cached. It does not cover output ordering or empty-result behavior, but these are minor gaps for this 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 description coverage is 100%: the only parameter, 'lane', is documented in the schema as 'Optional lane slug to filter'. The tool description adds no extra parameter-level meaning, but none is needed, so the baseline score 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 clearly identifies a specific resource: the current pre-scored steal list across tracked lanes. It further defines what qualifies (auctions ≥45% under market and mispriced Buy It Now listings), making the tool's function unambiguous. It does not explicitly differentiate from siblings like scan_deals, but the resource and criteria are specific enough.

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?

No explicit guidance is given about when to use hot_list instead of sibling tools such as scan_deals, price_check, or flip_margin. 'Fast cached read' and 'current' imply it is for quick snapshots, but there are no clear when-to/when-not-to conditions or 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?

With no annotations, the description carries the behavioral disclosure burden. It states that the data is live, sourced from current eBay Buy It Now listings, and includes sample size, which is useful context. It does not mention rate limits, failure modes, or whether network calls are made, but for a simple read-only price lookup the disclosed behavior is adequate.

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 with no fluff. The first sentence front-loads the core output and data source, and the second gives the practical usage context. 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?

For a simple two-parameter tool, the description explains the return value composition despite lacking an output schema, and the schema covers parameters fully. It omits edge-case behavior like empty results or errors, but those are minor for this use case.

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 schema already documents both parameters. The description adds little beyond naming the product and implying a price floor; it does not enrich the parameter semantics beyond what the schema provides.

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 a specific verb-resource pair: it computes a live market price distribution from current eBay Buy It Now listings. It lists concrete outputs (median, p25, p75, min, max, sample size) and a usage phrase, but it does not explicitly differentiate itself from sibling tools like flip_margin or scan_deals.

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 an explicit use case: 'Use to answer what is this worth right now.' This provides clear context for when to invoke the tool, though it does not state when not to use it or name alternatives among the siblings.

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 full burden of behavioral disclosure. It explains the scanning behavior, default mode, output contents, and the difference between auction and fixed-price results. It does not mention rate limits, failure modes, or whether the tool only returns links versus executing purchases, but the core behavior is reasonably 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?

The description is three concise sentences with no filler. The purpose is front-loaded in the first sentence, followed by mode behavior and output contents. Every sentence adds value.

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?

The tool has 6 parameters and no output schema, but the description covers the return contents (market median, percent under market, buy link) and explains the two operational modes. It is complete enough for an agent to understand what results to expect, though it could specify sorting behavior or edge cases like empty 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 description coverage is 100%, so the baseline is 3. The description adds meaningful context for buying_option by explaining what AUCTION and FIXED_PRICE modes do, but it does not add significant semantics beyond the schema for the other parameters.

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 ('Scan'), resource ('live eBay listings'), and outcome ('return the ones priced furthest under the current market median'). It clearly identifies the tool's core function and distinguishes its auction vs fixed-price modes, though it does not explicitly differentiate from sibling tools like price_check or flip_margin.

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 clear guidance on when to use AUCTION vs FIXED_PRICE mode, which is useful context. However, it never mentions alternatives or explicitly states when NOT to use this tool over siblings like hot_list or price_check, leaving that differentiation to inference.

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