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 burden of behavioral disclosure. It clearly indicates this is a fast cached read, explains data freshness (refreshed every 30 minutes), and specifies inclusion criteria. It doesn't describe output shape or pagination, but the core behavior is 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 a single dense sentence that front-loads the purpose and includes only meaningful details: coverage lanes, qualification thresholds, refresh interval, and cache behavior. No 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 simple one-optional-parameter cached list tool, the description covers scope, data source, freshness, and performance characteristics. Exact lane slug values and output format are not given, but these are minor given the schema and list semantics.

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 describes the lane parameter at 100% coverage, so the baseline is 3. The description adds value by enumerating the tracked lane categories and confirming the parameter filters within those lanes, which goes 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 specific resource ('pre-scored steal list') and the exact criteria that qualify items, making the tool's purpose clear. It doesn't explicitly differentiate from scan_deals, but the curated 'hot list' concept is distinct 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?

The description implies usage for fast cached deal lookups and notes the 30-minute refresh cadence, which suggests when it is appropriate. However, it never names sibling alternatives like scan_deals or states when not to use this 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?

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.