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

With no annotations, the description carries the burden; it does disclose that the call is free and that it returns price-per-call plus return descriptions, which is meaningful behavioral context. It stays silent on catalog size, pagination or freshness, leaving gaps for a listing 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 sentence with zero waste; the free/cost signal is front-loaded followed immediately by the resource and payload.

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 listing tool with no output schema, the description explains what each entry contains (price per call, return values), which is enough for correct invocation. A brief note on catalog scope or freshness would complete 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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline of 4 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?

Specific verb (List) plus resource (DF Market Intelligence data tools), and it further specifies the payload — price per call and return values. This clearly distinguishes it from siblings like df_status and df_wallet, which serve different roles.

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 leading 'Free.' hints that this is a zero-cost discovery call, implicitly useful before invoking paid tools, but no explicit when-to-use or when-not-to-use guidance is given. The agent must infer that this is a catalog/bootstrap step.

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 burden. It helpfully discloses that the call is free (meaningful next to the x402_* siblings, which imply payment), but says nothing about cost/latency, caching, or whether results are stable snapshot values.

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 very short clauses, front-loaded with the cost fact and then the core purpose. Slightly telegraphic ('Free.' as a fragment) but 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, argument-free read tool this covers the essentials: it names the datasets covered and what value is returned per dataset. With no output schema, it could specify the response shape (timestamps, keys) a bit more, but an agent has enough to call 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?

The tool takes zero parameters, so the baseline is 4; there is nothing for the description to disambiguate and it correctly presents a no-argument status call.

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 concretely what it returns: the last-refresh time for each of four named datasets (insider trades, prediction markets, macro, x402 economy). That is a specific resource with scope, distinguishable from sibling query tools like insider_latest or macro_latest, though it never explicitly contrasts itself with df_catalog, which may sound adjacent.

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 – check freshness before relying on a dataset – and 'Free' signals there is no x402 payment cost. However, there is no explicit when-to-use versus df_catalog or any statement of what to do when data is stale.

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 whole burden and does disclose the key traits: the call is 'Free' (no charge against the wallet despite showing spend), it is a read/'Show' operation, and the response contents are enumerated. It omits auth requirements (e.g., whether a configured wallet is required) and any error behavior when no session exists.

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 short clauses, front-loaded with the cost qualifier ('Free.') that matters most before an agent spends a call budget. Every phrase maps to either a constraint or a returned field; 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?

With no output schema and no annotations, the description must convey return contents, and it lists all three. For a zero-parameter diagnostic read this is nearly complete; the remaining gap is failure/empty-wallet conditions rather than core behavior.

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?

Zero input parameters, so per baseline this scores 4; there is nothing for the description to disambiguate and it 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 concrete verb ('show') and enumerates exactly what is exposed: paying wallet address, spending caps, and session spend. It is specific enough to distinguish it from the sibling catalog/search/status tools, though it never names an alternative.

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 you call this to inspect the wallet behind paid x402 calls or to check remaining spend. There is no explicit when-to-use, no preconditions, and no named alternative, so the routing signal relies on 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?

With no annotations, the description does real work by disclosing the monetization behavior: $0.05 USDC per call via x402 on Base, auto-paid from a configured wallet, so the agent knows a cost and wallet dependency are involved. However it says nothing about return shape, result limits, or whether the read is safe/reversible, leaving gaps a no-annotation tool should close.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the definition and ranking, followed by the cost disclosure — every sentence earns its place. The em-dash aside is slightly dense but not wasteful.

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-required-param, two-optional-param tool with full schema coverage but no annotations and no output schema, the description covers what it returns conceptually (ranked stocks) and the cost model. It still omits the shape of the ranked results and any limits, which is a modest gap rather than a blocking one.

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 (days 1-90 default 14, min_insiders 2-10 default 2) are fully documented in the schema. The description alludes to 'same window' and 'several insiders' but adds no syntax, units, or defaults beyond what the schema already states, so 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?

The description gives a specific resource (insider cluster buying) and defines it precisely: stocks where several distinct insiders bought on the open market in the same window, ranked by insider count and dollar value. It is clearly distinguishable from insider_latest or insider_ticker in substance, though it never names those siblings to route the agent 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?

The phrase 'one of the strongest public insider signals' hints at when this is preferable to a raw insider feed, but there is no explicit when-to-use/when-not statement and no named alternative among the insider_* siblings. Use is implied rather than prescribed.

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 burden and does well: it discloses the paid model ($0.01 USDC per call via x402 on Base, auto-charged from the wallet), the freshness window (parsed within minutes of filing), and the return format (clean JSON). It omits error/failure behavior and what happens if the wallet lacks funds, which is notable for a paid endpoint.

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 dense sentences with zero filler: data source and freshness first, then filtering, then cost. Every clause carries information an agent needs before invoking.

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 three-param, no-output-schema read tool, the description covers source, freshness, filters, and payment model — the essentials. It would be complete with a note on sibling differentiation and empty-result or payment-failure behavior.

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 all three parameters are already documented in the schema, establishing a baseline of 3. The description restates the type codes (P=buy, S=sale) and min_value filter without adding new syntax or format detail beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Names a specific verb and resource — most recent SEC Form 4 insider transactions for US stocks — with concrete detail about parsing latency. It does not, however, distinguish itself from the sibling tools insider_ticker and insider_clusters, which an agent must choose between.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by describing filter options ('filter by type... and minimum dollar value'), but never states when to pick this over insider_ticker or insider_clusters. No explicit when/when-not guidance is given.

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 must carry behavioral disclosure. It usefully discloses the $0.02 USDC per-call cost and automatic wallet payment, and it summarizes return metrics, but it omits read-only status, rate limits, failure/charge behavior, and data freshness.

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 two sentences, front-loads the tool's purpose, and then adds the critical cost/payment detail. The summary metrics are compact and no sentence 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?

There is no output schema, but the description summarizes what is returned: buy vs sell dollar value, distinct buyers/sellers, and a net_buying/net_selling signal. It also discloses the per-call cost, though it could mention data freshness or error behavior for fuller completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the symbol and days parameters are already documented in the schema. The description's 'over a window' phrasing adds only marginal context and does not explain defaults, ranges, or formats beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific resource and scope: insider buys and sells for one ticker over a look-back window, plus summary metrics. It is clear but does not explicitly differentiate itself from sibling tools such as insider_latest or insider_clusters.

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 'for a stock' and 'over a window,' giving enough context to infer when this tool applies. However, it does not state when to use it instead of sibling insider tools, nor does it mention exclusions or prerequisites beyond wallet payment.

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 present, so the description carries the disclosure burden. It helpfully surfaces the payment model ($0.005 USDC per call, x402 on Base, auto-paid from wallet), which is genuine behavioral context. But it omits return shape, whether releases include dates/times/importance, and any timezone or coverage caveats.

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 efficient sentences with the purpose front-loaded before the cost note. Every clause carries information; the cost sentence is justified since no annotation conveys it.

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-param read tool this is mostly adequate, and the cost is disclosed. With no output schema and no annotations, though, the agent still cannot anticipate what a calendar entry contains or the format of returned dates/events.

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 single 'days' parameter is 100% covered by the schema ('1-45, default 14'). The description echoes 'next N days' but adds no constraint or format meaning beyond the schema, so 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?

The description gives a specific verb+resource: an 'economic release calendar' for 'upcoming US economic data releases' over 'the next N days', with concrete examples (CPI, jobs report, GDP). It's clearly distinct from a series/latest tool, though it never names the sibling (macro_latest/macro_series) to reinforce the distinction.

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 'Upcoming ... for the next N days', which tells an agent this is the forward-looking view. However, no explicit when-to-use vs when-not, and the obvious alternatives (macro_latest, macro_series) are never referenced.

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 burden, and it does disclose the most consequential behavior: a $0.01 USDC charge per call via x402 on Base, auto-paid from a configured wallet. That is exactly the kind of cost and prerequisite information an agent needs before invoking. It stops short of stating data freshness/cadence, rate limits, or what happens if the wallet is unfunded.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the payload scope and ending with the payment model, with no filler. The 24-indicator list is long but functional, since it defines the coverage the agent is paying for.

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 read tool with no output schema, the description covers scope and cost but omits the return structure (units, direction of 'change', comparison period for YoY) and the freshness of the data. It also fails to position the tool against macro_series, which is the main remaining gap given a fairly crowded sibling set.

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 baseline of 4 applies. The description correctly implies no input is needed and spends its words on scope and cost instead.

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?

It states a specific verb-and-resource combination ('Latest value, change and year-over-year % for 24 key US indicators') and enumerates the indicators covered, so an agent knows exactly what data comes back. It does not differentiate itself from the sibling macro_series, which sounds like a closely related per-indicator lookup, leaving ambiguity about which to call.

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 no mention of the alternatives macro_series and macro_calendar despite them being obvious siblings. An agent must infer from the name alone that this is the snapshot tool rather than the time-series or calendar tool.

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

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

With no annotations, the description carries the behavioral burden and does a good job disclosing the return content, observation limit, per-call cost, payment rail, and wallet behavior. It still does not state whether the operation is read-only, error behavior for invalid ids, or rate limits, but the key operational traits are disclosed.

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 two dense sentences with no wasted words. It front-loads what the tool returns before covering cost and payment mechanics.

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-style series retrieval tool with no output schema, the description covers the essential return shape and cost context. More detail on the exact summary-stat fields or response format would make it fully complete, but an agent has enough 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?

Schema description coverage is 100%, and the single parameter is fully documented in the schema with FRED id examples. The description only repeats 'by FRED id' and adds no further semantics beyond the schema, so the baseline of 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?

The description states a specific resource and scope: one US macro time series by FRED id, returning history (up to ~260 observations) plus summary stats. It is clear what the tool does, but it does not explicitly distinguish itself from siblings such as macro_latest or macro_calendar.

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 phrase 'History ... for one US macro series by FRED id,' suggesting it is for historical series retrieval. However, it gives no explicit when-to-use guidance, exclusions, or alternative tools for related macro queries.

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 load, and it does disclose the important behavioral trait: a paid call at $0.01 USDC per invocation via x402 on Base, auto-deducted from the configured wallet. That cost/payment disclosure is exactly the kind of context an agent needs before calling. It omits response shape, pagination, and error/insufficient-balance behavior, keeping it short of a 5.

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?

Purpose and scope are front-loaded, and the cost sentence is a separate, earned line given the payment model. The framing clause is slightly decorative but short enough not to hurt.

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-optional-parameter list tool with no output schema and no annotations, the description covers what it returns conceptually (markets with largest probability moves), the filter dimension, and the payment model. Missing only return format and pagination, which are minor here.

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 (limit, min_volume) are already fully documented with ranges and defaults. The description's 'filtered by minimum volume' merely restates min_volume, adding no syntax or semantics beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific metric — the markets whose implied probability moved the most over the last 24h — which is a distinct concept from the sibling predictions_top and predictions_search. The verb/resource framing plus the plain-language gloss ('what the crowd suddenly changed its mind about') makes it unambiguous.

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 24h-mover scope and the min_volume filter imply when this tool is useful relative to a generic top-markets list, but no sibling is named and no exclusion is stated. The agent must infer that predictions_top is the alternative for volume-ranked rather than movement-ranked data.

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 does well by disclosing the cost ($0.01 USDC per call), payment rail (x402 on Base), and automatic wallet deduction. It does not describe rate limits, failure modes, or result ordering, which keeps it from a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core purpose and followed by the critical payment detail. Every clause earns its place, and no filler is present.

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 search tool with no output schema and no annotations, the description supplies purpose, sources, and payment behavior. It could say more about the shape of returned probabilities, but the essential call-time context is present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both q and limit with examples. The description reinforces that q is keyword-based but adds no format, syntax, or usage constraints beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Uses a specific verb ('Search') and resource ('prediction markets'), and explicitly scopes it to keyword lookup of market-implied probabilities across Polymarket and Kalshi. This distinguishes it from siblings like predictions_top and predictions_movers, which do not take a keyword.

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 keyword-based lookup and names example domains, but it does not explicitly state when to use this versus predictions_top, predictions_movers, or macro_series. No exclusions or alternative-routing guidance are 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, the description carries the full behavioral burden and does well on key traits: it discloses freshness ('Refreshed every 15 minutes') and billing ('Costs $0.005 USDC per call ... paid automatically from your configured wallet'). It does not cover rate limits or error behavior, but the cost and staleness disclosures are substantial for a read-only data 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?

The description is two tightly written sentences. The core scope is front-loaded, and the remaining sentences add essential context about refresh cadence and cost without any 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?

No output schema exists, but the description lists the returned fields (implied probabilities, 24h change, volume, close time), which is important. Combined with the freshness and payment notes, it is nearly complete for this tool, though it could say more about result ordering or coverage 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%, and both parameters (limit and source) are fully documented in the schema, including the source enum. The description adds no parameter-specific syntax or constraints beyond what the schema already provides, so the baseline of 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?

The description uses a specific verb and resource ('Top prediction markets') and immediately scopes it to 'Highest-volume live prediction markets across Polymarket and Kalshi.' This distinguishes it clearly from sibling tools like predictions_search and predictions_movers, which imply keyword search and movement-based ranking respectively.

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 scope ('top ... highest-volume live'), so an agent can infer this is for browsing leading markets. However, the description never explicitly says when to use this versus predictions_search or predictions_movers, nor does it state any exclusions or prerequisites beyond the payment note.

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

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

With no annotations provided, the description carries the behavioral burden and discloses important traits: it costs $0.01 USDC per call on Base, payment is automatic from the configured wallet, and data is refreshed every cycle. It still lacks details on rate limits, payment failure behavior, and explicit read-only safety, but the cost and freshness disclosures are substantial.

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 purpose is front-loaded, followed by a dense but useful enumeration of included metrics and then two short sentences on refresh and cost. The long metric list is information-rich but slightly dense; nothing is wasted, though the structure could be sharper.

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 aggregate overview with no output schema, the description covers what data is returned, the data source, freshness, and payment cost. It is largely complete, though it does not describe the response shape or units beyond estimated USDC volume.

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 appropriately does not waste space on nonexistent parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb and resource — an overview of the x402 agent economy drawn from the full Bazaar catalogue — and enumerates the aggregate metrics it covers. It is clearly an aggregate summary rather than a service-level search or listing tool, though it does not explicitly name the sibling alternatives it replaces.

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 word "overview" and the list of aggregate metrics, suggesting it should be used when a broad state-of-the-economy summary is needed. It does not explicitly state when to prefer x402_services, x402_search, x402_trending, or x402_pricing, nor does it provide exclusions.

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 burden and does disclose the most important non-obvious trait: a $0.01 USDC charge per call via x402 on Base, deducted automatically from a configured wallet. It stops short of stating rate limits, caching, or whether failures are still billed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the resource and the payload of metrics, followed by audience and payment terms. Dense but every clause carries information; the parenthetical payment method is useful rather than 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?

No output schema exists, and the description does compensate by enumerating the returned metrics. Missing pieces are the shape of the response (per-category list?), whether it covers all categories or a fixed set, and how it differs from the sibling x402_overview.

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 nothing for the description to clarify beyond confirming the call requires no inputs.

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 and what it returns: per-category price benchmarks with 25th/50th/75th percentile, free share, and median paid price. It does not distinguish itself from siblings like x402_overview or x402_services, so an agent cannot tell from this text alone which to call.

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 audience framing ('For sellers setting prices and buyers checking value') implies when the tool is useful, but there is no explicit when-to-use versus alternatives, no mention of x402_overview/x402_services, and no note on whether data is cached or how often to refresh.

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 burden and does so well: it discloses result ranking (by real usage), a filtering rule (decoy/honeypot endpoints ≥$1000 excluded), the fields returned (price, method, network, recent activity), and — critically — that each call costs $0.005 USDC on Base paid automatically from the configured wallet. Cost and payment mechanics are non-obvious traits an agent must know before invoking.

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?

Front-loads the core action, then layers in scope, filtering, and cost. Every sentence carries information, though the single long middle sentence packs return fields and the honeypot rule tightly enough to be slightly dense.

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, and the description partially compensates by enumerating returned fields and the ranking basis. It still leaves the response envelope (count, pagination, failure behavior when payment fails or no match is found) unspecified, which matters for a paid, agent-invoked call.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3, but the description adds genuine meaning by giving semantic examples of the required `q` intent strings and confirming results are ranked/filtered. The `limit`, `category`, and `max_price` parameters are left entirely to the schema, which handles them adequately.

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+resource ("Find a paid API for a task") and immediately clarifies the mechanism: describe a need in natural language and get matching x402 endpoints. The concrete query examples ('weather forecast', 'token price', 'transcribe audio') and the returned fields make the purpose unmistakable and distinct from listing-oriented siblings like x402_services.

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?

Clearly tells the agent the input style (describe what you need) and frames it as intent-based discovery, which implicitly positions it against listing tools. However, it never names an alternative or an exclusion (e.g., use x402_services to browse, x402_trending for popularity), so the agent must infer sibling routing.

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 real weight and does so: it discloses a per-call cost of $0.01 USDC on Base paid automatically from a configured wallet, and it discloses a non-obvious default filter that drops services whose volume comes from fewer than 5 wallets. It stops short of describing pagination, result ordering limits, or error behavior when a wallet is unconfigured.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the resource and its metrics, followed by the cost disclosure. The first sentence is dense but every clause (metrics, returned fields, concentration flag, category filter) adds information an agent needs; nothing is padding.

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 still enumerates the returned shape (endpoint count, median price, networks, concentration flag), covers all four parameters, and discloses the payment model. Nothing an agent needs to call this correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds meaning the schema lacks: the ranking metrics are defined as 30-day calls, unique payers, and estimated revenue, and the <5-wallet concentration exclusion is stated as a default rather than only as an opt-in flag. That clarifies the behavior of include_concentrated beyond the enum's own text.

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 and resource ('Ranked x402 services') plus the three ranking metrics, so an agent can tell it is a rankings/list tool rather than a lookup. It does not explicitly name the sibling alternatives (x402_search, x402_trending, x402_pricing), 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?

Usage is only implied: the agent can guess this is the tool for browsing ranked services by calls/payers/revenue, and filtering by category is mentioned. There is no explicit when-to-use guidance, no stated conditions for picking this over x402_trending or x402_search, and no exclusions.

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 burden, and it does disclose two behaviors beyond the name: the $0.02 USDC per-call cost on Base with automatic wallet payment, and the data provenance from daily whole-catalogue snapshots. It stops short of covering failure modes such as insufficient wallet balance or how ties and services with zero calls are handled.

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 one tight paragraph that leads with the concept before the cost note, and every clause carries information. The provenance clause is useful, but the cost and payment details would be easier to scan as their own sentence.

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-optional-parameter, output-schema-less tool with no annotations, the description covers what the tool ranks, the data source, and the payment model, which is enough to call it correctly. It omits how many services are represented, how the ordering is presented, or how results behave when a service is new, which would be useful for interpreting the response.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so both parameters are already fully documented with ranges and defaults, making 3 the baseline. The description reinforces the meaning of days ('versus N days ago') and new entrants, but adds no format or edge-case detail beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific resource and operation: ranking x402 services by gain or loss in paid calls over an N-day window, plus new entrants. This is clearly distinct from catalogue-listing siblings such as x402_services or x402_search, and an agent can tell them apart without opening schemas.

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 when to use it by describing trending and movers analysis, but it never explicitly says when this tool is preferable to x402_services or x402_pricing, nor does it state what to use instead. An agent must infer the split from sibling names alone.

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