Magpie — USDA Agricultural Data for AI Agents

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

With no annotations, the description carries the full burden, and it does disclose that the result is a derived comparison metric ('unshipped balance') rather than raw contract or shipment rows. However, it says nothing about permissions, data freshness, whether both ESR and GATS must be available, or the result's granularity beyond that single aggregate.

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 sentence that front-loads the comparison semantics and ends with the payoff metric. Every clause earns its place with 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?

Adequate but thin for a tool with no output schema and no annotations: the agent knows what is compared and one output field, but not the time window, aggregation level, or units of the 'unshipped balance'. Those gaps matter because nothing else in the definition fills them.

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 both parameters (commodity enum, partner country code) are documented in the schema, so the baseline is 3. The description adds no additional meaning about how commodity or partner affect the comparison.

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 (compare) and two named resources (ESR sales contracts, GATS actual shipments) plus the derived output (unshipped balance). It is clearly distinguishable from data-retrieval siblings like get_export_sales or get_trade_flows, though it never names an alternative 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?

No guidance on when to reach for this comparison versus get_export_sales, get_trade_flows, or list_esr_commodities / list_gats_commodities. No prerequisites, no exclusions, no indication of the time scope of the comparison.

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, and it discloses little beyond a bare read. It does not say whether the data is latest-only vs historical, how frequently NASS updates it, or whether any auth/rate constraints apply. 'current' is the only behavioral hint.

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?

One front-loaded sentence with zero filler that names the source, the metric, and the value categories. Nothing could be trimmed without losing information.

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 read tool with fully documented schema and no output schema, the description says what the tool returns well enough to call it. Only minor gaps remain, such as the lack of any note on freshness or comparison against sibling condition/progress tools.

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% — both optional parameters (commodity, geography) with their allowed values and defaults are fully documented in the schema. The description adds no additional meaning about the parameters, so the 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?

States a specific verb (Get) and resource (NASS crop condition ratings) and even specifies the data shape (% excellent/good/fair/poor/very poor), which helps distinguish it from nearby siblings like get_crop_stats and get_crop_progress. It does not explicitly name a sibling to route against, so it falls just short of a 5.

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 when-to-use guidance, no prerequisites, and no mention of the alternatives (get_crop_stats, get_crop_progress) that an agent might confuse this with. Usage must be inferred entirely from the name.

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 hints that data is 'current'. It does not disclose that this is a read-only lookup, the reporting cadence/source (weekly NASS), whether history is excluded, or how defaults (CORN/US) are applied.

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 filler; the resource and the returned metrics are stated immediately and 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-optional-parameter read tool with full schema coverage and no output schema, the description is nearly sufficient. The remaining gap is the absence of any note on recency/cadence or how to choose between this and the condition/stats siblings.

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 both parameters are already documented with defaults and accepted values in the schema. The description adds no parameter-level detail (e.g., accepted commodity/state codes) beyond that, so the baseline 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?

States a specific verb (Get) and resource (NASS crop progress) and clarifies the payload with metric examples ('% planted, emerged, harvested, etc.'). It is distinguishable from get_crop_condition (ratings) and get_crop_stats (aggregate stats), but it never names or contrasts those siblings 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?

No when-to-use guidance and no alternatives named, despite several adjacent siblings (get_crop_condition, get_crop_stats, and the *_history tools). The word 'current' implicitly scopes it to the latest report, but the agent gets no explicit 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?

No annotations are provided, so the description carries the full behavioral burden. It implies a read ('Get') and names the data source (NASS survey statistics), but says nothing about data recency (weekly/monthly/annual), units of measure, or what a caller receives back.

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 filler, naming the source, the statistic types, and the scoping key. It is appropriately sized, though the statistic types listed partially duplicate the schema's stat description.

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 an all-optional, fully documented read tool there is no output schema, so the description should ideally signal return shape or data frequency. As written it is adequate but leaves the agent guessing about what a 'stat' value represents and over what time period.

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%, with each of stat, commodity, and geography documented and defaulted in the schema. The description only restates that results are tied to a commodity and adds no format, unit, or valid-value guidance beyond the schema, so the baseline 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?

States a specific verb and resource: NASS survey statistics covering yield, production, and acreage for a commodity. It distinguishes itself from data-source siblings like get_weather or get_export_sales, but it does not differentiate itself from adjacent NASS tools such as get_crop_condition or get_crop_progress.

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 indication of when to use this tool rather than get_crop_condition, get_crop_progress, or get_grain_price, and no prerequisites or exclusions are stated. Usage must be inferred purely from the name and the word 'survey statistics'.

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 at all, the description carries the full behavioral burden and mostly fails: 'latest' hints at recency but nothing states units/currency, data source, latency, or whether the default geography applies silently. It also does not confirm the operation is read-only, which the agent must infer.

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 filler or redundancy. It is appropriately terse for a simple lookup, though the brevity is partly under-specification rather than disciplined concision.

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 no annotations, so the description must set expectations on its own, and it does not. Return shape (single price, series, timestamp), price units, and the meaning/scope of the geography parameter are all unaddressed, leaving real gaps for a pricing tool with a 2-param schema.

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%: the product enum is documented in the schema, while 'geography' has only a default and no description anywhere. The description's phrase 'for a dairy product' merely restates the required param and adds nothing about geography semantics (region codes, default behavior).

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 ('Get') and resource ('latest price for a dairy product'), which is unambiguous on its own. It does not explicitly contrast itself with sibling price tools like get_grain_price or get_livestock_price, but the resource noun 'dairy product' does the differentiation implicitly.

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 when-to-use guidance, no mention of prerequisites, and no reference to alternatives (e.g., list_dairy_products for discovery). The single sentence leaves the agent to infer that this is the price lookup for the dairy commodity family purely from the tool name.

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. It discloses the returned metrics, but says nothing about data freshness/lag, auth requirements, or pagination for what is a recurring weekly dataset. A read operation is implied but not confirmed.

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 tight sentence that front-loads the verb and resource and parenthetically enumerates the payload. No wasted words, though the parenthetical is the only content beyond the core statement.

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 2-parameter read tool with no output schema or annotations, the metric enumeration partly compensates for the missing return documentation. The unresolved overlap with get_export_sales_history and absent freshness/auth details leave it only adequate.

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%, with both parameters documented (country as a GENC code or omitted, commodity as an enum slug). The description adds no parameter detail beyond the schema, so the baseline 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?

States a specific verb (Get) and resource (USDA weekly export sales) and names the returned metrics (net sales, outstanding, commitments), which is more than a restated name. However, it does not distinguish itself from the very similar sibling get_export_sales_history, leaving the agent to guess which one it wants.

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 when-to-use or when-not-to-use guidance, and the near-identical sibling get_export_sales_history is never mentioned. The agent gets no signal about which of the two to select.

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. It conveys only the weekly cadence; it says nothing about the data source, units, whether a missing country means aggregate/total, or how the series is bounded (the default/max window only appears in the schema).

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 efficient sentence that front-loads the resource and cadence with no filler. It is appropriately sized, though the terseness is part of why usage and distinctions go unaddressed.

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 and no annotations, the description is the sole source of context, and it omits the differentiator versus get_export_sales, the default country behavior, and the units/return shape. Adequate to invoke, but thin for a time-series retrieval 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?

The 67% schema coverage is effectively higher than it looks, since the undocumented 'commodity' parameter is fully enumerated and the other two carry schema descriptions. The description restates commodity and country but adds no format or interpretation detail (e.g., what omitting country returns), so it neither compensates nor detracts.

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 a specific verb ('Get'), resource ('weekly export sales time series'), and scope ('for a commodity and country'), so an agent knows exactly what data comes back. It does not, however, distinguish itself from the sibling get_export_sales, which an agent would have to disambiguate on its own.

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 by the phrase 'time series'; there is no explicit statement of when to pick this tool over get_export_sales or get_trade_flows, and no prerequisites or exclusions are given. For a sibling set crowded with export/trade tools, this leaves the routing decision to guesswork.

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, yet it discloses nothing beyond the name: no granularity (weekly/monthly), no units, no time-span semantics, and no note that the enum oddly includes non-fertilizer products like farm_diesel and biodiesel. The only behavioral detail (max 52 periods) lives in the schema, not the description.

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 zero filler; the verb and resource lead. It is efficient, though the extreme brevity shades into under-specification rather than tightness.

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 time-series tool with no annotations and no output schema, the description should at least convey period granularity, units, and what the returned series looks like. None of that is present, so an agent cannot anticipate the shape or meaning of the result.

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 50% – 'periods' is documented in the schema, while the 'product' enum has no description anywhere. The description adds no format, unit, or range meaning for either parameter, and does nothing to explain that the enum spans fuels as well as fertilizers.

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 price history for a fertilizer product'), which cleanly separates it from the sibling get_fertilizer_price (current price) and list_fertilizer_products. It stops short of naming those alternatives explicitly, so differentiation is implied 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?

No guidance on when to choose this over get_fertilizer_price or the other history tools. There are no exclusions, prerequisites, or trigger conditions of any kind.

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 implies a read-only lookup but says nothing about data source, freshness/lag, geographic scope, currency, or units (e.g. $/ton vs $/gallon, which matters for the diesel/biodiesel entries in the enum). For a market-data tool with zero annotation coverage, this is a substantial gap.

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 tight sentence with the resource and scope front-loaded and zero wasted words. Nothing is padded or repeated from the 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?

There is no output schema and no annotations, so the description is the only place return semantics could be described. It omits units, currency, geography, and as-of date, all of which an agent needs to use a price value correctly. Adequate for identification, incomplete for interpretation.

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 enum parameter is fully documented with examples, so the schema does the heavy lifting. The description adds no meaning beyond it (no guidance on picking a slug or what each product covers). Baseline 3 is correct.

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 clear verb+resource+scope: fetching the latest price for a fertilizer product. An agent immediately knows what it returns. However, it does nothing to distinguish itself from the sibling get_fertilizer_history, and 'latest' is the only differentiator, which is left implicit.

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 when-to-use guidance and no mention of alternatives. The sibling get_fertilizer_history is the obvious complement (current vs. historical), but the description never routes the agent between them. The word 'latest' hints at a distinction but never states 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 burden. It does disclose the forecast horizon (7 days), which is genuinely useful behavior context, but says nothing about units, update cadence, geographic resolution, or what happens when the location is omitted and the default applies.

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?

One front-loaded sentence with zero filler; nothing is wordy or redundant. It is efficient, though the brevity is partly the cause of the missing behavioral detail.

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 tool with a fully documented optional parameter and no annotations or output schema, the description is minimally complete. The key missing element is any signal separating it from get_weather, which leaves the agent to guess between the two.

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 location parameter is documented with a default, so the schema does the heavy lifting. The description adds no meaning beyond the schema, such as what a valid location key looks like. Baseline 3 applies for full-coverage single-parameter tools.

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 a specific verb (Get), resource (weather forecast), and scope (7-day, agricultural region), so the purpose is unambiguous. However, it never distinguishes itself from the sibling get_weather, which an agent would have to disambiguate on its own.

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 when-to-use guidance and no exclusion or alternative named. With a sibling tool literally called get_weather sitting next to it, the absence of any routing rule is a real gap.

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, yet it says nothing about data source, granularity (daily/weekly), units, currency, or return shape. Only the terse 'price history' phrase hints at a time-series result.

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 short sentence with the resource front-loaded and zero filler. It is efficient, though it borders on under-specification for a three-parameter tool with an output format the agent must discover.

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 annotations, no output schema, and only a third of parameters documented means the description should do far more. It omits what the history series looks like, what geography codes are valid, and how 'periods' interacts with the returned data.

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 only 33% — 'periods' is documented inline, but 'product' (enum, self-evident) and 'geography' (default 'IL', an unexplained abbreviation) have no descriptions. The one-line description adds no parameter meaning at all, so it fails to compensate for the coverage gap.

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 price history for a grain commodity'), and the word 'history' implicitly separates it from the sibling get_grain_price. However, it does not explicitly call out the current-price sibling, leaving the distinction to the agent's inference.

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 guidance on when to use history versus get_grain_price, no prerequisites, and no mention of the sibling tools. The agent must guess that 'history' means time-series retrieval rather than a snapshot.

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 of behavioral disclosure, and it says almost nothing: no statement of read-only safety, no permissions, no rate limits, no indication of how fresh the 'latest' price is or whether it is delayed. 'Latest cash price' hints at recency but leaves the freshness contract undefined.

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 zero filler; the verb and resource come first and nothing is wasted.

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 lookup with a fully documented schema and no output schema, the description is minimally adequate. But with no annotations it omits currency/units, timestamp semantics, and read-only confirmation, leaving real gaps for an agent deciding whether to call it.

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 schema itself documents the product enum with examples and the geography default (IL). The description adds no parameter meaning at all, so the baseline 3 applies where the schema does all the 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?

States a specific verb and resource ('get the latest cash price for a grain commodity') that is clearly distinct from sibling tools like get_dairy_price, get_livestock_price, and get_fertilizer_price. It does not, however, explicitly differentiate itself from get_grain_history, which shares the same resource domain.

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 when-to-use guidance is given, and the obvious alternative (get_grain_history) is never mentioned. An agent must infer that this tool returns a single current snapshot while the history sibling returns a time 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?

No annotations are provided, so the description carries the entire behavioral burden, and it discloses almost nothing: not the granularity (daily/weekly), units, whether the series is nominal or real, nor whether geography changes the series. For a data-retrieval tool with zero annotation coverage this leaves significant 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, which is structurally fine. It is concise to the point of under-specification rather than genuinely efficient, so it earns only a middling score.

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 three parameters, no annotations, no output schema, and a 33% schema coverage, the description should clarify what is returned (granularity, units) and how geography and periods interact. It does none of this, leaving an agent unable to predict the response shape.

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 only 33%: only 'periods' is documented ('Days (max 365)'), while 'geography' has no description and only a default of 'IA'. The description's phrase 'livestock category' loosely maps to the product enum but adds no format or meaning the schema lacks, and it does not compensate for the undocumented geography 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 verb (get) and resource (price history for a livestock category), which is enough to distinguish it from non-livestock siblings like get_grain_history. However, it never names its closest sibling get_livestock_price, so the agent must infer that 'history' means time series rather than a current quote.

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 when-to-use guidance, no prerequisite, and no mention of alternatives such as get_livestock_price for a spot value or list_livestock_products for valid categories. Usage is only weakly implied by the word 'history'.

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 says almost nothing: no auth requirements, no rate limits, no update frequency, no units/currency, and no indication of whether the returned price is a snapshot or a range. 'Latest' hints at recency but is not elaborated.

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 filler or redundancy. It is appropriately sized, though its brevity is partly a symptom of the missing behavioral detail rather than disciplined compression.

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, so the description should explain the return shape (price value, units, as-of date), and it does not. For a data-retrieval tool with zero annotations, the definition is under-specified about what the agent actually receives.

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 both the product enum and the geography default are fully documented in the schema itself. The description adds no syntax, format, or constraint detail beyond that, so the baseline 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?

States a specific verb ('Get') and resource ('latest price for a livestock category'), which is clearer than a tautology. However, it does nothing to distinguish itself from siblings like get_livestock_history or list_livestock_products, so an agent must infer the boundary from names alone.

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 when-to-use guidance, no prerequisites, and no mention of alternatives such as get_livestock_history for past prices or list_livestock_products for the valid slugs. The word 'latest' weakly implies a current-snapshot use case but never states it as a selection rule.

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 discloses almost nothing: no data source, no units or ratio definitions, no freshness, no rate limits, and no statement of what happens when a spread component is unavailable. It only clarifies what spread categories exist, which is minimal disclosure for a data-fetch tool.

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 dense sentence with the resource stated first and the three spread types listed immediately; there is no filler. It is terse but appropriately sized for the amount of information conveyed.

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, no annotations, and an undocumented parameter, the description should explain what a spread value represents and how geography affects results. It does not, so an agent cannot reliably predict the return shape or the effect of its only argument.

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% and the sole parameter, geography (default 'IL'), is never mentioned in the description. The phrase 'by product' implies a product breakdown that does not correspond to any actual parameter, leaving the geography dimension entirely unexplained (state? region? country?).

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 ('Get input-to-output price spreads') and enumerates the three concrete spread types (corn-to-nitrogen, soybean-to-corn, feeder-to-fed cattle), which differentiates it from the many price/history siblings. It falls short of 5 because 'by product' is ambiguous and 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?

There is no guidance on when to choose this tool over get_grain_price, get_fertilizer_price, get_livestock_price, or get_forecast, all of which could plausibly answer related questions. No prerequisites, no exclusions, no context is provided.

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 present, the description carries the full behavioral burden, and it delivers almost nothing beyond the source name. It never states that this is a read-only lookup, describes the shape or units of the returned flow values (volume? value?), or mentions any rate limit or data-lag caveat typical of monthly GATS releases.

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 zero filler; the subject and qualifier both land immediately. Nothing could be trimmed without losing meaning.

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 no annotations, so the description is the only place to explain what comes back. It omits units/measure (metric tons vs value), time granularity confirmation, and whether partner is broken out per row — meaningful gaps for a trade-flow data 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%, so the schema already documents months, partner and commodity, including the default and max on months. The description adds no semantics beyond what the schema supplies, which is the expected baseline of 3.

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 (Get), a named source (USDA GATS), a resource (monthly trade flows) and a scope qualifier (actual shipments) for a given commodity. The parenthetical 'actual shipments' usefully distinguishes it from sales-commitment tools like get_export_sales or compare_contracts_vs_shipments, 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?

No when-to-use guidance, no conditions, and no routing to alternatives. An agent cannot tell from the text why it would pick this over get_export_sales or compare_contracts_vs_shipments, both of which appear to touch the same domain.

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 implies a revision-history read but says nothing about time range, revision granularity, ordering, pagination, or response shape for a tool whose whole value is historical depth.

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?

One sentence, front-loaded with the verb and resource, with no filler. It is efficient, though its brevity contributes to the completeness gaps noted elsewhere.

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, no output schema, and low parameter coverage, the description should do more work. It leaves the agent without return format, historical range, or revision semantics for a tool that is fundamentally about revision 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 only 33% (just 'Projection attribute' on attribute). The description mentions 'commodity attribute' but adds no meaning for country, the WORLD default, or the enum semantics, so it fails to compensate for the coverage gap.

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 ('Get') and resource ('historical WASDE projection revisions') scoped to a commodity attribute. This is clearly distinguishable in spirit from get_wasde_projection, but the description never names that sibling or explicitly contrasts current vs. historical.

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 when-to-use guidance and no exclusions. The word 'historical' weakly implies this is for revision history rather than the current projection, but the agent gets no explicit direction on when to prefer this over get_wasde_projection.

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 and mostly fails it. It does not say whether this returns only the latest report, how the WORLD default affects results, or whether market_year omission yields a default season.

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 filler or redundancy. It is efficient, though its brevity is partly the source of the missing guidance noted elsewhere.

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 is simple and its parameters are fully documented in the schema, but with no output schema and no annotations the description should at least sketch what a projection result contains (e.g., per-market-year balance sheets). It is adequate but leaves real gaps.

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%, with the enum and the market_year example (2026 = 2025/26) fully documented in the schema, so baseline 3 applies. The description's phrase 'for a commodity' adds nothing beyond what the schema already states.

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?

Names a specific verb (Get) and resource (USDA WASDE supply/demand projections) scoped to a commodity, which is clear enough for selection. However it never distinguishes itself from sibling get_wasde_history, which an agent could easily confuse with this tool.

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 when-to-use guidance and no mention of alternatives such as get_wasde_history for prior releases or list_wasde_commodities for valid slugs. The agent must infer the selection criteria entirely from the name.

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 discloses the temporal scope ('current') but says nothing about data source, update cadence, units, or whether a missing/invalid location falls back to the default region — all relevant for a weather lookup.

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?

One sentence, front-loaded with the verb and resource, with zero filler. It is efficient, though its brevity is partly the source of the missing usage and behavioral detail.

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 read with no output schema and no annotations, the description is minimally adequate but leaves the return shape (units, which conditions, spatial granularity of a 'region') unaddressed. An agent can call it, but cannot anticipate what it will receive.

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%: the single 'location' parameter is documented with its default and its five accepted region keys. The description's phrase 'agricultural region' aligns with but adds nothing beyond the schema, so the 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?

States a specific verb and resource ('Get current weather conditions') and scopes it to agricultural regions, so the agent knows exactly what data comes back. It does not, however, distinguish itself from the sibling get_forecast, leaving the temporal-boundary decision to inference.

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 no when-to-use guidance and never mentions the obvious alternative, get_forecast, nor any prerequisite for the location key. 'Current' hints at a use case but nothing explicitly routes the agent between this and the forecast sibling.

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 disclosure burden. "List" implies a read-only, non-destructive operation, but the description says nothing about the return shape, whether the set is static or date-dependent, or pagination — meaningful gaps for a tool with zero annotation coverage.

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 short sentence that is front-loaded and wastes no words. It is appropriately sized for the operation, though it is arguably under-specified rather than maximally efficient.

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 no-param enumeration tool with no output schema, the description should hint at what the returned list contains, since those values likely feed get_dairy_price. It states scope (all available products) but leaves the return content entirely unspecified.

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 there is nothing to disambiguate and the schema is trivially complete. Baseline of 4 applies for a parameterless tool.

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 (list) and resource (dairy products), so the agent knows exactly what it retrieves. It does not explicitly differentiate itself from sibling listers like list_grain_products or list_livestock_products, relying on the resource noun to do that work.

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 when-to-use guidance, no mention of a prerequisite (e.g. selecting a product before calling get_dairy_price), and no reference to alternatives. Usage is only inferable from the tool name and the surrounding list_* family.

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 disclosure burden. "List all" usefully signals a non-mutating, unfiltered enumeration, but it says nothing about ordering, result size, or whether the set is static or refreshed with each ESR report.

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 seven-word sentence with the verb and scope front-loaded and zero filler. Nothing in it is redundant with 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?

With no parameters, no output schema, and no annotations, this is a simple enumerator, and the description is minimally sufficient to call it. It stops short of telling the agent what a returned commodity identifier looks like or what to do with it next.

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 of 4 applies. There is no parameter syntax or meaning the description could add and none is missing.

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 pairs a specific verb ("List") with a specific resource ("commodities tracked in export sales"), which is more precise than the bare tool name and separates it from generic siblings like list_grain_products. It does not, however, explicitly name or contrast itself with the many sibling list_* tools, so differentiation is left implicit.

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 stated when-to-use, when-not-to-use, or alternative sibling. An agent must infer from the phrase "export sales" that this feeds get_export_sales/get_export_sales_history, but nothing in the text says so.

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. 'List' suggests read-only behavior, but the description does not explicitly confirm safety, mention pagination, rate limits, or what data is returned. It adds little beyond the tool name.

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 with no wasted words. It is appropriately sized for a simple list tool.

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 the simplicity (no parameters, no output schema, no annotations), the description is minimally adequate. However, it does not specify the return format (e.g., names, IDs) which would help an agent understand what to expect.

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?

There are zero parameters, so the baseline score is 4 per the rules. The description does not need to explain any parameter semantics.

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 clear verb ('List') and resource ('fertilizer products') with scope ('all available'). It distinguishes from siblings like get_fertilizer_price or get_fertilizer_history, but does not explicitly name or contrast them, so it falls short of 5.

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 implied by the name and description—this is a straightforward listing tool—but there is no explicit guidance on when to use it versus alternatives or any prerequisites. No exclusions or conditions 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?

No annotations are provided, so the description carries the burden alone. It does convey that the operation is a full enumeration with no filtering, but it says nothing about the shape of the result (names vs. codes vs. identifiers reusable in get_trade_flows) or whether the list is static. For a zero-parameter read this is a modest gap rather than a serious one.

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 filler and no redundancy. It is efficient, though its brevity is also the source of the missing return-shape context.

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 zero parameters and no annotations, the only real unknown is what the list contains (commodity names, codes, or IDs usable elsewhere) and there is no output schema to cover it. The description could have closed that gap in a few words but doesn't.

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 no parameters, so the schema has nothing to document and there is no parameter semantics to compensate for. Baseline 4 applies; no penalty is warranted.

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 gives a specific verb ('List') plus a bounded resource ('all commodities tracked in GATS trade flows'), which cleanly separates it from the sibling enumerators like list_esr_commodities and list_wasde_commodities by domain. It does not explicitly name those siblings, but the GATS qualifier is sufficient for an agent to distinguish them.

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: an agent can infer this is a discovery/enumeration step preceding get_trade_flows, but the description never says so, nor does it state any when-not condition versus the other list_* tools. Adequate but leaves the routing to inference.

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 burden, but the tool is trivially simple: no parameters, no side effects implied, and 'List all available' at least signals full enumeration rather than filtering. It does not mention read-only nature, pagination, or the identifier format returned for downstream calls.

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 short sentence with the resource and scope front-loaded and zero filler. Nothing could be cut without losing meaning.

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 and no annotations, the description is the only source of truth, yet it never says what a returned commodity looks like (name, code, ID) or how that value is consumed by siblings. Adequate for a trivial enumerator but incomplete as a discovery tool an agent must chain from.

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, which is the baseline-4 case. There is nothing parameter-related for the description to clarify or omit.

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?

Specific verb 'List' plus resource 'grain commodities' with explicit scope 'all available'. It is clearly distinguishable from data-fetching siblings like get_grain_price and get_grain_history, though it never names those siblings or states how the output relates to them.

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 when-to-use guidance, no mention that this is a discovery step whose output feeds get_grain_price/get_grain_history, and no exclusions. The intent is only weakly implied by the 'list_' prefix and the sibling naming pattern.

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 disclosure burden. 'List all available' usefully signals a complete, read-only enumeration with no pagination or filtering, but it says nothing about return shape, item identifiers, or payload size. Minimum viable for a trivial zero-param read, not more.

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 clause with zero filler; the scope word 'all available' is the only qualification and it earns its place. Nothing is buried or 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 zero-param listing tool with no output schema and no annotations this is roughly adequate, but the agent still cannot tell what an item looks like (category name, code, id) or whether those values are the accepted inputs to get_livestock_price. Given no output schema exists, that gap is the description's to close.

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 there is no parameter semantics to explain and the baseline is 4. 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 clear verb (List) and resource (livestock categories), and the 'livestock' qualifier distinguishes it from sibling listers like list_dairy_products and list_grain_products. Minor friction: the name says 'products' while the description says 'categories', so it's slightly unclear whether the same set is returned.

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 — an agent can infer this is the discovery/enumeration call for the livestock family, and the sibling 'get_livestock_price'/'get_livestock_history' names suggest the relationship. But the description never states when to use this versus those tools, nor that its output is intended to feed them.

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 of behavioral disclosure. Apart from the verb 'List' implying a read operation, it says nothing about return format, permissions, limitations, or what the output contains.

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 one-sentence description is front-loaded, contains no filler, and is appropriately sized for a simple zero-parameter list tool.

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 list tool, the description communicates the core purpose adequately. However, with no output schema and no annotations, it leaves the exact return shape (names, codes, objects) unspecified, which is a clear though 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?

This tool has zero parameters, so the baseline for parameter semantics is 4. The description correctly adds no parameter details because there are none to explain.

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?

Specific verb 'List' plus resource 'commodities' and scope 'tracked in WASDE projections' clearly states what the tool does. It distinguishes this tool from sibling list_* tools that cover other datasets such as grain, dairy, or fertilizer.

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 no when-to-use guidance, no prerequisites, and no alternatives. It does not tell an agent whether to call this before get_wasde_projection or how it differs from other commodity-listing tools in practical use.

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