Pulltrader Seller Economics

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

With no annotations, the description fully bears the burden. It discloses that calculations are deterministic and use dated fee schedules, that results are estimates for eBay and competitors, and that if acquisition_cost is supplied the target is net profit. It also notes per-order fixed fees are applied once, covering important behavioral traits.

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 paragraph that front-loads the core purpose and then covers usage, exclusions, and caveats. Every sentence adds value, with no redundancy or filler. It is optimally concise for the complexity.

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?

Given 11 parameters and no output schema, the description covers input interpretation, fee methodology, and estimation disclaimers thoroughly. A minor gap is that it doesn't describe the return format (e.g., what values are returned), but the tool is a straightforward computation so this is acceptable.

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 baseline is 3. The description adds meaning beyond the schema, e.g., explaining that quantity affects per-order fixed fees, that shipping_amount affects eBay's fee base, and that acquisition_cost changes the interpretation of target_net. This extra context justifies a score above baseline.

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 specifies a clear verb ('compute the per-item sale price') and resource (trading-card selling methods), and it distinguishes itself from siblings by explicitly saying 'Do NOT use this to look up a card's market value or recent sales', which differentiates it from tools like get_card_price_history.

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 provides explicit usage scenarios ('when a seller asks what do I need to list this at to walk away with $X') and clear exclusions ('do NOT use it for non-trading-card categories'). It also names an alternative tool indirectly by stating what not to use it for.

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?

No annotations provided, so description covers behavioral traits: deterministic calculations using dated fee schedules, only fixed-price seller fees modeled, and eBay/competitor figures as estimates. Could add note about non-destructive nature but sufficient.

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?

Description is well-structured with front-loaded purpose, usage scenarios, and limitations. Slightly long but no fluff; 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?

Given 11 parameters and no output schema, description adequately explains tool scope, inputs, and limitations. Covers major usage scenarios and exceptions like auction formats not modeled.

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 baseline is 3. Description adds value by explaining default methods, that competitor methods are off by default, and how seller_plan affects payout tiers.

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 the tool compares estimated fees and net proceeds across various trading-card selling methods. It distinguishes from siblings by focusing on selling method comparison, not pricing or identification.

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?

Explicitly specifies when to use (e.g., seller asks what they keep/net, how fees compare) and when not to use (not for market value, not for non-trading cards). Also clarifies that competitor methods are off by default.

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?

No annotations are provided, so the description carries the full burden. It explains the tool returns a 'plain, structured explanation' and lists the aspects covered (who owns, fulfills, fees, caveats), making it clear this is a read-only informational operation. However, it does not explicitly state that no data is modified or that it does not call external APIs, which would improve transparency. The description is still strong overall.

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 yet informative: two paragraphs with no wasted sentences. It front-loads the purpose and includes necessary details about what is explained and what is excluded. Every sentence serves a purpose, making it easy to parse quickly.

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?

Without an output schema, the description must explain the return value. It states the explanation is 'plain, structured' and covers specific aspects (ownership, fulfillment, fees, caveats), which is fairly complete. However, it does not describe the exact structure (e.g., whether it's a list or paragraphs) or mention any edge cases, leaving a minor 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?

Schema coverage is 100% with a clear description of the 'methods' parameter. The tool description adds value by naming each method and indicating which are 'estimated' (eBay, competitor marketplaces), providing context beyond the schema's enum list. This extra detail helps the agent understand the parameter's 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?

The description clearly states the tool returns a 'plain, structured explanation' of selling methods, specifying what aspects it covers (ownership, fulfillment, fees, caveats) and lists all supported methods. It distinguishes itself by explicitly stating what the tool is not for, contrasting with siblings like 'compare_selling_costs' and 'calculate_required_sale_price'.

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 provides explicit guidance on when to use the tool ('when a seller asks how a method works, what fees a platform charges, or how Pulltrader selling options differ') and exactly when not to use it, including alternative tools for specific tasks. This clear differentiation helps an agent decide correctly.

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 fully discloses behavioral traits: it aggregates sold-sale samples and vendor history, provides estimates not financial advice, and is limited to trading cards. It does not mention rate limits or auth needs, but the tool is read-only and simple.

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?

Four sentences with no fluff. The first sentence states the core function, followed by usage hints, parameter clarification, and a caveat. Every sentence 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?

The description is thorough for a simple tool with no required parameters and no output schema. It explains the output format (chart-ready series, median per bucket, trend) and domain limitations. Minor omissions (e.g., pagination) are acceptable given low complexity.

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 well-documented. The description adds contextual value (e.g., natural-language query vs structured item, interval defaults to week) but does not significantly augment parameter semantics beyond 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 the purpose: returning a chart-ready price-history series aggregated into day/week/month buckets with median and trend. It distinguishes from siblings like search_card_sales and summarize_card_market by focusing on historical price changes over time.

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 explicitly tells when to use the tool (e.g., 'how has the price changed', 'price over time', trend queries, chart requests). It lacks explicit when-not-to-use or alternatives, but the sibling list and context provide indirect 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?

No annotations provided, so description carries full burden. It discloses behavior: returns confidence and resolved fields, does not price or return sales, and scope is 'trading cards only'. However, could mention whether multiple results are possible or if it's deterministic.

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?

Four sentences: first declares core function, second gives usage context, third clarifies non-behaviors, fourth limits scope. Every sentence earns its place with no waste.

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?

Given low complexity (1 param, no output schema, no nested objects), the description is fully adequate. Covers purpose, usage, behavior, and boundaries completely for an AI agent.

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% with the single 'query' parameter already described. Description adds an example but no additional semantic detail beyond the schema. Baseline 3 is appropriate.

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?

Description clearly states it resolves natural-language trading-card descriptions into structured fields, and explicitly distinguishes from pricing/sales tools by stating what it does not do.

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?

Explicitly says to use first when needing canonical fields before sales lookup, and directs to specific siblings for pricing/sales, providing clear when-to-use and when-not-to-use 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?

No annotations are provided, so the description carries the full burden. It transparently states that figures are 'estimates from recent sales', 'exclude fees/taxes/shipping', 'not financial advice', and 'does not place orders'. This effectively sets expectations. It could mention data source freshness, but overall it's good.

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 highly concise: four sentences covering purpose, usage, caveats, and domain. It front-loads the core function and provides necessary details without padding. Every sentence 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?

Despite having no output schema, the description specifies the return: 'price + sale date' and 'market snapshot (median, range, sample size)'. It covers all three parameters, domain restrictions, and limitations. For a tool of this complexity, the description is complete.

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 baseline is 3. The description adds value by explaining that 'query' is natural-language and 'item' is structured, and that either is required. It also clarifies the 'limit' parameter's purpose. This extra context helps the agent choose between 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 clearly states it returns recent comparable sold listings and a market snapshot for a trading card. The verb 'Return' and specific resource 'recent comparable SOLD listings' make the purpose unmistakable. It distinguishes itself from siblings like 'get_card_price_history' or 'summarize_card_market' by focusing on recent comps.

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 explicitly tells when to use it: 'when a user asks 'what is this card selling for', 'recent sales', or 'comps''. It also limits usage to 'Trading cards only.' While it doesn't discuss alternatives, the context signals provide sibling tools, and the description gives clear usage scenarios.

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 discloses key behaviors: estimates are from recent sales, excludes fees/taxes/shipping, and disclaims as not financial advice. It also restricts to trading cards. Does not cover rate limits or error handling, but the disclosed traits are relevant and sufficient for an agent.

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?

Four sentences; front-loaded with purpose and outputs. Each sentence adds necessary detail. Minor redundancy in saying 'not financial advice', but overall efficient without unnecessary verbiage.

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 lists all output components. Input options are well explained. Limitations (trading cards only, excludes fees) are stated. For a non-destructive query tool, the description is sufficiently complete to guide 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 coverage is 100% with descriptions for both parameters. The description adds value by clarifying the mutually exclusive nature of query vs item, and enumerating the fields expected in the structured item object, which goes beyond the schema description alone.

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 specifies a clear verb ('Return a canonical market summary') and resource ('for a trading card'), listing specific outputs and domain. It effectively distinguishes from siblings like search_card_sales and get_card_price_history by focusing on synthesized market summary rather than raw sales or price history.

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?

Explicitly states when to use: when user asks 'what's it worth', 'market value', or 'how volatile'. Provides domain constraint ('Trading cards only'). Does not mention when not to use or compare with sibling tools, but the guidance is clear and actionable.

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