PokeInvest Pokemon card prices

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

With no annotations, the description carries the full behavioral burden, and it does disclose a lot about what comes back: medians for ungraded and each grader, sale counts, window, low/high, newest sale, population totals, card page, buy link, and a live eBay copy when one exists. However, it says nothing about authentication needs, rate limits, cost, or what happens on a bad or ambiguous card identifier. The output-content detail is strong but operational behavior is absent.

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?

It is a single very long run-on sentence with a comma-spliced list of a dozen return fields. The key idea is front-loaded, which helps, but the enumeration of graders and fields is dense and could be trimmed or split. Nothing is truly wasted, yet the structure makes it harder to scan than necessary.

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 exists, so the description must describe returns, and it does so thoroughly, covering grade coverage, statistics, population, links, and the optional eBay copy. What remains missing is usage/routing context against four closely related siblings and any error or ambiguity behavior for the name-based lookup.

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 `card` parameter is richly documented in the schema itself (PokeInvest ID, numeric URL ID, or name with best-match resolution). The description adds no additional meaning about the identifier, only about the response. Baseline 3 applies since the schema does all the parameter work.

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 opening clause "What a card sells for" plus the enumeration of grades and providers makes clear this retrieves pricing data for a single card. It is distinguishable from get_price_history and get_sales in emphasis (current median sold prices across graders), though it never explicitly names those siblings. The verb is implicit ("what X sells for") rather than a crisp "get current card prices".

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?

There is no statement of when to call this versus get_price_history, get_sales, get_population, or get_population_history, even though the description mentions population totals and sales that overlap those siblings. No prerequisites or exclusions are given. The agent must infer routing from the return-field list alone.

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 supplied, so the description carries the full behavioral burden. It does disclose real behavior: listings are live, verification covers title, photo and price, and the response includes the saving amount and a buy link. It says nothing about how many results come back, whether results are cached daily, or whether calls are rate limited, leaving the mutation-free read nature and result freshness only partially covered.

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 front-loaded sentence with a colon that separates the claim from the verification detail; every clause ('live listings', 'at that grade', 'title, photo and price all checked') adds real meaning. It is dense but not padded.

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 two-parameter read tool with no output schema and no annotations, the description covers the return shape reasonably (saving plus buy link) but leaves both input parameters unexplained. The 'across every card' phrasing also leaves unclear whether this is a global feed or scoped in some way the parameters control.

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 0%, and the description never mentions limit or min_total_usd. The agent gets no explanation of the $25 default floor or the 1-30 cap on results, so both parameters are documented nowhere.

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 and resource: it returns 'today's best verified eBay deals' and defines a deal precisely as a live listing priced under what the card sells for at that grade. That definition implicitly separates it from get_card_prices and get_sales, but no sibling is named, so the agent must infer the boundary rather than read 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?

The description conveys what the tool returns but never says when to reach for it over get_card_prices, get_sales or search_cards, nor any when-not condition. The only usage signal is the word 'today's', which hints at a daily-discovery use case without stating it.

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 behavioral burden. It lists returned report fields but does not state whether the tool is read-only, what data source it uses, whether results are cached or live, or any rate-limit or authentication considerations.

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 enumerates the report contents without redundant wording. Every phrase contributes useful information about what the tool returns.

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 tool with no annotations, no output schema, and an undocumented required parameter, the description is missing critical invocation details. It explains the report contents but not how to identify the card correctly or how this tool relates to get_population_history.

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 0%, and the description only says the report is 'for a card' without explaining what format the required 'card' parameter accepts. It does not clarify whether this should be a card name, PSA identifier, cert number, or another key.

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 resource and report contents: PSA population data for a card, including grade counts, total, gem rate, and last-updated time. It does not explicitly distinguish this current report from the sibling tool get_population_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?

There is no guidance on when to use this tool versus alternatives such as get_population_history or get_card_prices. An agent must infer the intended use from the name and description alone.

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 supplied, so the description carries the full behavioral burden, and it only discloses the output dimensions (total, PSA 10, PSA 9 by date). It says nothing about data source, time granularity, date range limits, how gaps in grading history are handled, or whether the call is read-only/cached. For an unannotated tool this leaves significant 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?

A single front-loaded sentence with no wasted words; the parenthetical breakdown is an efficient way to convey the returned metrics. It is telegraphic to the point that it omits key facts, but nothing is padded or redundant.

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 at least sketch the return values (total, PSA 10, PSA 9 by date), which is its main contribution. However, it omits the identifier format for the sole required parameter and the time granularity of the series, both of which an agent needs before calling.

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 0% and there is one required parameter, 'card', whose accepted format is never specified — card ID, slug, or name is left ambiguous. The description only repeats 'for a card' rather than compensating for the undocumented parameter.

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 resource (PSA population) with a temporal scope ('over time') and names the breakdown (total, PSA 10, PSA 9 by date), which implicitly separates it from the snapshot-oriented get_population and get_price_history siblings. It stops short of naming those siblings explicitly, so the differentiation is inferable rather than stated.

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?

'Over time' and 'by date' imply this is the trend/history query versus the point-in-time get_population, but the description never says when to prefer it or when not to. No prerequisites, no exclusions, no explicit pointer to an alternative.

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 full behavioral burden, and it only partially does so. It usefully discloses the aggregation cadence (weekly), the coverage window (back to 2022), and the returned measures (date, median, sale count, window). It says nothing about how 'grade' is determined or whether the caller can select one, how results are ordered or bounded, or what happens for a card with no sales.

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 compact line with the payload description front-loaded and no filler. The telegraphic field list is efficient, though the trailing term 'window' is unexplained jargon that costs a little clarity.

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 tool with no annotations and no output schema, the description usefully stands in for the missing output schema by listing the return fields and time coverage. However, it leaves the required parameter's format and the grade dimension unspecified, which are real gaps 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 0% for the single required parameter 'card', and the description never mentions it or explains the accepted identifier form (card name, set code, or internal ID). It also introduces 'per grade' without explaining whether grade is a fixed dimension of the output or something the caller controls, which leaves the parameter contract ambiguous.

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 names the resource and its shape concretely: weekly price per grade, from 2022 onward, with the returned fields enumerated. That distinguishes it from the point-in-time sibling get_card_prices by implication (weekly, historical), but the distinction is never stated explicitly, so an agent must infer it from the word '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?

There is no explicit when-to-use, when-not-to-use, or sibling routing guidance. The closest siblings, get_card_prices and get_sales, are never mentioned, so the agent must decide on its own whether it wants the current price snapshot or the weekly series.

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 full behavioral burden but only partly meets it. It usefully discloses the result cap and ordering ('Up to 500 newest') and the shape of each record, but says nothing about currency, what happens if the card is not found, or how 'newest' interacts with the days filter.

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 tight sentences with zero waste: the first front-loads what the records contain, the second front-loads the limits and filters. Nothing is repeated from the schema and no filler appears.

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 tool with no annotations, no output schema, and 0% schema description coverage, the description should resolve more. It handles the return record shape and result cap well, but leaves the required 'card' identifier and the semantics of days (default window, max 1095) undocumented anywhere.

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 0%, so the description must compensate and it does so only partly. It meaningfully clarifies grade with concrete examples ('PSA 10', 'RAW') and explains days as a lookback filter, but the sole required parameter, 'card', is never explained — an agent cannot tell whether it expects an ID, a name, or a slug.

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 resource (completed sales for a card) and enumerates the fields returned (date, price, grader/grade, platform, listing title), which is much more informative than the bare name. It implies a distinction from aggregated siblings like get_price_history by framing these as individual completed transactions, but never names an alternative outright.

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 is only implied: 'the completed sales behind a price' suggests an agent should reach for this when it wants raw comps rather than an aggregate. There is no explicit when-not guidance and no mention of the sibling tools (get_price_history, get_deals) that an agent must choose between.

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 exist, so the description carries the full behavioral burden. It does well on confidence and limits — quoting 91% top-1 and 95% top-3 accuracy on 1,000 real eBay photos and explicitly disclaiming same-art variant discrimination, which is exactly the kind of honesty an agent needs. It is silent on failure modes, though: no mention of what happens with a non-card photo, a blocked/private URL, rate limits, or latency.

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?

Three sentences, each load-bearing and front-loaded: capability first, then accuracy evidence, then the limitation plus the action to take. Nothing is repeated from the title or schema, and the most actionable instruction ('show the top 3') is not buried.

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 naming the return contents (candidates with IDs, prices, population). For a one-parameter tool with no annotations, it supplies capability, accuracy, input constraints, and a known failure class, which is everything needed 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?

With 100% schema coverage on a single parameter, the baseline is 3. The description earns above that by adding image-content requirements the schema does not: the photo may be a raw card or a slab and may be taken from any angle. That tells the agent which images are acceptable inputs, which the schema's 'public https URL of the photo' does not.

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 opens with a specific verb and resource ('Identify a Pokemon card from a photo URL') and immediately bounds the input domain ('raw card or slab, any angle'). It also states what comes back (top candidates with PokeInvest IDs, prices, population), which cleanly separates it from all sibling lookup tools like search_cards and get_card_prices.

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 clear operating context: use it when you only have a photo, and 'show the top 3' because same-art variants (1st Edition, reverse holo) cannot be distinguished. That is real guidance on how to act on results. What is missing is an explicit routing statement such as 'if you already know the card name, use search_cards instead', so the alternative 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?

No annotations are supplied, so the description carries the full behavioral burden. It does disclose useful output context ('ungraded and PSA 10 price when known'), which signals prices may be missing, but it says nothing about result ranking, result-count defaulting to 8 with a max of 25, or truncation behavior when a query is broad.

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?

Three short sentences, front-loaded with purpose, then return value, then illustrating examples. Every sentence adds something, though the examples slightly restate the query format already stated in sentence one.

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 annotations and no output schema, the description should say more about what comes back and how the search behaves. It covers purpose and return IDs reasonably but leaves the limit parameter and result-set behavior undocumented, which matters for an agent deciding how many candidates to request.

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 only 50% (limit has no description), so the description should compensate, and it does for query by giving concrete example strings ('Charizard base set 4', 'Umbreon VMAX 215') that show the expected format beyond 'name, optionally with set and/or number'. The limit parameter is left entirely unexplained in both schema and description, which keeps this from a 5.

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 Pokemon cards by name, set or number') with the retrieval dimensions named. It also clarifies its position in the workflow by noting it returns PokeInvest IDs to pass to other tools, which distinguishes it from get_card_prices, get_sales and the other siblings that consume those IDs.

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 the entry-point workflow: search here first, then pass the returned IDs to 'the other tools'. That is clear contextual routing, but it never states exclusions (e.g., when to use identify_card_photo instead when only an image is available) or what happens when a query is ambiguous.

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