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

Beyond the annotations (readOnlyHint=false, openWorldHint=true), the description discloses the return artifact (a signed decision receipt), the escalation rule for over-policy actions, and the cost/payment mechanism ($0.02 USDC on Base via x402). It does not state exactly what state is written or whether the decision is auditable, so it stops short of full disclosure.

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

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

Three compact sentences, front-loaded with the core action and its escalation behavior, followed by the input hint and price. The query-string-style input listing is mildly redundant with the schema but costs little space.

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 correctly compensates by stating the return value (signed decision receipt). It also covers pricing and escalation, which an agent calling a paid, open-world authorization service needs. Missing only details on side effects/permissions, which are minor given the annotations.

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 action, amount, and counterparty, including the required flag. The description's 'Input: ?action=&counterparty=&amount= (counterparty required)' merely restates the schema and adds no syntax, format, or constraint detail beyond it.

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 pair (approve or deny), the resource (an agent action), and the governing context (a human-set policy), plus the escalation outcome. It is clearly distinguished functionally from generic siblings like dyoe_verify or dyoe_review, though it never names an alternative tool 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?

Usage is implied: you call this when an agent action needs instant authorization against a policy, and anything over the policy line escalates rather than being handled here. There is no explicit when-not guidance or named alternative, so the agent must infer the boundary.

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?

Annotations already declare readOnlyHint and openWorldHint, so safety is covered. The description adds genuinely useful behavior beyond annotations: the operation costs $0.05 USDC on Base per call and is paid via x402, and it returns both a verdict and prioritized fixes. It does not detail response structure or failure modes, but the cost/auth disclosure is valuable context.

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

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

Front-loaded purpose with the em-dash clause, followed by return info and pricing in two compact sentences. Slightly redundant with the title, which also states the $0.05 price, and the Input fragment is borderline noise, but overall 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 single-parameter tool with no output schema, the description covers purpose, output character (verdict + prioritized fixes), and payment mechanics. An agent has enough to call it and set expectations, though no output schema means return details could be richer.

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?

Only one parameter exists and schema coverage is 100%, so the schema already documents url with an example. The description's "Input: ?url=domain" adds negligible meaning beyond the schema (a query-string style that conflicts slightly with the schema's https://stripe.com example). 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 (Score) and resource (any website) with a clear scope: 0-100 for legitimacy, trust, SEO and contactability, framed as company due diligence. It distinguishes itself functionally from siblings like dyoe_verify or dyoe_reputation through the website-scoring angle, though it never names an alternative to route against.

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?

"due diligence on a company in one call" implies the use context, and the tool's nature suggests pre-deal research. But there is no explicit when-to-use vs when-not guidance, and despite many overlapping siblings (verify, intel, reputation, merchant) none are referenced as alternatives.

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?

Annotations cover the safety profile (readOnlyHint, openWorldHint), so the description correctly spends its words elsewhere: it discloses the paid model ($0.01 USDC on Base, x402), that calls are batch-safe, and that output is structured JSON. Cost and payment mechanism are material traits an agent cannot get from annotations or schema. It stops short of 5 because it says nothing about rate limits or failure behavior on unreachable sites.

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

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

Four short sentences, front-loaded with what is extracted, then the batch/agent framing, the input/return contract, and the price. Little waste; 'Returns structured JSON' earns its place given there is no output schema, though the sentence could be trimmed further.

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 single-parameter, annotation-covered tool with no output schema, the description covers what is extracted, input shape, return format, and the paid-call model — enough for an agent to invoke it correctly. It is not fully complete because it omits any note on partial results or what happens when a site yields no contacts.

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 schema's url field already carries a concrete example (https://stripe.com). The description only restates 'Input: website URL', adding no format or constraint detail, 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?

Names a specific verb (extract) and concrete resources (public business emails, phone numbers, social profiles) scoped to a website, so an agent knows exactly what comes back. It does not differentiate itself from the sibling dyoe_extract or dyoe_metadata, which could plausibly overlap, so it stops 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?

'Batch-safe contact enrichment for autonomous agents' implies a high-volume enrichment context, and the URL-only input implies one site per call. However, it never states when to prefer this over dyoe_extract or any other sibling, nor any exclusions (e.g. pages behind auth), so usage is only implied.

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?

Annotations already declare readOnlyHint=true and openWorldHint=true, so the description only needs to add beyond that — and it does: it discloses the price ($0.10 USDC), the payment rail (Base via x402), and the fact that the output is a signed, independently verifiable credential. It does not note failure modes or rate limits, but for a single-call tool the pricing/payment disclosure is substantive.

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 compact paragraph that front-loads the purpose, then the input, then the price. Every element earns its place, though the '?domain=' fragment is slightly cryptic without 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?

For a single-parameter tool with no output schema, the description usefully enumerates the returned fields (verdict, trust_score, domain_age) and discloses cost and payment method. It omits what happens on a failed trust check or the credential's format, but the essentials for calling it correctly are 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 coverage is 100% and the single domain parameter is fully documented in the schema with an example (stripe.com). The description's 'Input: ?domain=' adds only marginal value over the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

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 — issuing a signed, independently verifiable credential that a domain passed a trust check — and names the return fields (verdict, trust_score, domain_age). It does not, however, differentiate itself from nearby siblings such as dyoe_verify, dyoe_reputation, or dyoe_audit, which an agent might confuse with it.

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

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

There is no explicit when-to-use guidance and no mention of the alternative tools (dyoe_verify, dyoe_reputation) that overlap in the trust-check space. The intended usage is only implied by the verb 'issue a credential'.

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?

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds important behavioral context beyond the annotations: the call costs $0.01 USDC on Base and is paid via x402. It does not discuss rate limits or latency, but for a paid read-only price tool the payment disclosure is the key extra detail.

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 short, front-loads the returned fields, and includes the essential payment detail without unnecessary prose. The phrase 'for trading agents' is mild filler, keeping it from a perfect 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 one required parameter and no output schema, the description adequately explains what is returned: price, 24h change, market cap and volume. It also discloses the payment model, which an agent needs before calling. It does not describe the exact response structure, but the field list is sufficient for this simple 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%, and the single parameter 'symbol' is already documented as a coin symbol with an example. The description restates the query format (?symbol=btc) but adds no semantic detail beyond what the schema provides. A 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?

The description names a specific resource and verb-equivalent: it returns live crypto price, 24h change, market cap and volume for any coin. The purpose is immediately clear. It does not explicitly differentiate itself from siblings such as dyoe_market, dyoe_token or dyoe_movers, so it falls 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?

The phrase 'for trading agents' hints at intended usage, but the description gives no explicit when-to-use, when-not-to-use, or alternative-tool guidance. It does not tell an agent when to choose this over dyoe_market, dyoe_token or dyoe_movers.

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?

Annotations already declare readOnlyHint and openWorldHint; the description adds key behavioral context: it costs $0.05 USDC on Base and is paid via x402. It also frames the booking check as a pre-payment safety step, though it doesn't describe errors, rate limits, or return behavior.

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 compact and front-loads the purpose before giving an invocation example and price. The inline query-string example is useful but somewhat redundant with the schema, and the price is repeated from the title.

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 composite tool with no output schema, the description names the data categories returned but does not explain the response structure or how budget and date affect results. It covers payment and purpose, but leaves output expectations underspecified.

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 five parameters are already documented in the schema. The example query string shows how the parameters compose, but it does not add meaning beyond the schema, such as how budget influences results.

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 composite purpose: weather/forecast, local currency with FX, and booking-site scam check in one call. The enumerated outputs make it clear what the tool does, though it does not explicitly name sibling alternatives like dyoe_weather or dyoe_fx.

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?

Provides clear timing guidance: use before the agent books or pays, and the 'one call' phrasing implies bundling those checks. It does not state when not to use it or compare it directly against sibling tools.

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?

Annotations cover the safety profile (readOnlyHint, openWorldHint), and the description adds non-obvious behavior the schema cannot convey: a $0.01 USDC payment on Base via x402 per call. That payment requirement materially affects invocation. It doesn't describe latency or failure modes, so not 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?

Front-loaded core purpose followed by audience, input, and price. Tight overall; the 'Input: ?url=' fragment is redundant with the schema but costs little.

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 single-param, no-output-schema read tool, the description covers purpose, output nature (clean main text, no nav/ads), and the payment prerequisite. Return structure specifics are the only gap, and it's minor for a text-extraction 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 coverage is 100% and there is only one parameter (url), which the schema already documents with an example. The description's 'Input: ?url=' adds nothing beyond the structured field, 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?

States a specific verb+resource: 'Extract clean main text content from any web page (no nav/ads)'. The parenthetical disambiguates the output. It doesn't name a sibling tool to distinguish from (e.g. dyoe_wiki), so it stops 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?

'For research & summarizing agents' implies the intended context but gives no explicit when-to-use/when-not or alternative routing. Adequate implied usage, 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?

Annotations already declare readOnlyHint and openWorldHint, so safety is covered. The description goes further by disclosing the cost model ($0.01 USDC on Base per call, paid via x402) and the data source, which materially affects whether an agent should invoke it. It omits error/rate-limit behavior, so not 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 short sentences, purpose front-loaded, followed by input example and price. Every element earns its place, though the query-string notation is slightly informal for a JSON-schema 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?

No output schema exists, so the description carries the burden of describing return shape — it only says 'live exchange rate' and never clarifies the response fields, precision, or what happens when amount is omitted (it is not a required parameter). Adequate but with a real gap.

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

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

Schema description coverage is 100%, so all three parameters are already documented. The embedded example '?from=USD&to=EUR&amount=100' adds a concrete usage pattern but no semantics beyond the schema, which is the baseline-3 case.

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 ('Currency conversion + live exchange rate') and names the underlying data source (ECB). No sibling tool does anything comparable, so an agent can route here without ambiguity.

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 never says when to prefer this tool over siblings like dyoe_crypto or dyoe_market, nor what conditions make it appropriate. It gives an input example but no usage context or 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?

Annotations already cover read-only and open-world status, and the description adds material context beyond them: the concrete data sources (RDAP registry, HTTPS reachability, on-page contact signals, DYOE human-vouch registry), the 'sources disclosed, not a black box' property, and the paid x402/Base pricing model. The gap is that it never says how the $0.10 payment is actually settled (e.g. whether a wallet/approval sibling must be called first), which is the highest-risk unknown for an agent invoking a paid 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?

Front-loaded with the core purpose and deliverable list, then the source-disclosure claim, then input and price — a sensible ordering with no filler sentences. The middle em-dash list is dense and slightly run-on, but every clause carries 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?

There is no output schema, so the description carries the return-value burden — and it discharges it by enumerating the dossier contents an agent will receive. Combined with the disclosed sources and the explicit per-call price, an agent has enough to decide, call, and anticipate 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 description coverage is 100% and there is a single required parameter, so the baseline is 3. The description's 'Input: ?target=domain' restates the parameter name and hints at the expected domain form, but adds no format rules, normalization, or failure behavior beyond the schema's own example.

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 ('Research') and resource ('a company or website') and then enumerates the actual deliverables — legitimacy verdict, domain age, contact paths, social presence, scam red flags. That makes the scope concrete enough to pick over a generic lookup. It does not, however, explicitly differentiate itself from adjacent siblings such as dyoe_verify, dyoe_reputation, or dyoe_audit, which an agent must infer.

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?

'Research a company or website in one call' and 'background checks for agents' imply the use case (consolidated due diligence) but give no explicit when-to-use/when-not and name no alternative tool. Usage is inferable rather than stated, which is the definition of minimum-viable guidance.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds genuinely useful non-annotation context: the call is paid ($0.01 USDC on Base via x402) and takes no input, which 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?

One tight sentence front-loads the purpose, then the cost. No filler, and every clause carries information the agent needs.

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 annotations covering the read-only/open-world profile, the description supplies what remains: scope of metrics and the payment requirement. Return format is unspecified, but that is a minor gap for a zero-arg pricing-gated 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?

Zero parameters, so the baseline is 4. The description reinforces this with 'Input: (none)', leaving no ambiguity about what to pass.

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 (global crypto market overview) and enumerates the exact metrics returned: total market cap, 24h change, BTC/ETH dominance. That field-level detail implicitly separates it from siblings like dyoe_movers or dyoe_trending, but no sibling is named explicitly, so it falls 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?

Usage is only implied by the data it returns — an agent can infer 'use this for aggregate market stats' — but there is no explicit when-to-use statement, no mention of when to prefer dyoe_crypto or dyoe_fx instead, and no stated prerequisites.

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?

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=true). The description adds genuinely new behavioral context: the call is metered at $0.05 USDC on Base paid via x402, and it discloses the shape of the result (verdict plus signals such as checkout, returns, payment methods). It still omits latency, failure modes, and whether a verdict can be inconclusive.

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-loaded with the core question ('Is this online store safe to buy from?'), followed by output content, audience, input, and price in a single dense line. Efficient, though the em-dash chain and pricing/input tail make it slightly crowded.

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 correctly compensates by enumerating what is returned (fraud check, trust verdict, store signals). For a one-parameter, read-only, paid tool the agent has enough to decide and call, with only rate-limit/error behavior left 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?

Schema coverage is 100% and the single 'url' parameter is already well described with an example, so baseline is 3. The description only echoes the parameter as '?url=' and adds no format, validation, or normalization guidance 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?

States a specific verb+resource (store scam/fraud check) plus the concrete deliverable: a safe/caution/avoid trust verdict and store signals. The scope ('counterparty trust for shopping & commerce agents before they pay') makes it distinguishable from generic siblings like dyoe_reputation or dyoe_verify, though it never names which sibling to prefer.

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?

Tells the agent exactly when to invoke it: before paying at an unfamiliar online store, framed as a pre-purchase trust gate for commerce agents. It gives no exclusions or pointer to sibling tools for other trust questions, so it falls short of a full when/when-not statement.

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?

Annotations already declare readOnlyHint and openWorldHint, so safety profile is covered. The description adds genuinely useful context beyond that: the exact cost ($0.01 USDC on Base) and the payment mechanism (x402), which an agent needs before calling. It stops short of disclosing failure/rate-limit behavior.

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 compact sentences that front-load the extraction purpose before the cost. The 'Input: ?url=' fragment is mildly redundant given the schema, but overall the text is tight and waste-free.

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 single-parameter read tool with annotations covering safety and no output schema, the description supplies the missing operational piece (cost/payment) and the returned-field list. Nothing critical for correct invocation is absent, though it never clarifies return shape or error handling.

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 schema already documents the single url parameter with an example, so the schema carries the burden. The description's 'Input: ?url=' merely restates the parameter name without adding format or edge-case meaning. 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 specific verb (Extract) plus the exact resource fields (title, description, OpenGraph image, favicon, canonical) and the input domain (any URL). This is far more specific than the sibling tools and lets an agent distinguish it from dyoe_extract or dyoe_intel without opening a schema.

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?

Names intended use cases ('link previews & summaries'), which implies when to reach for it. However it never states when NOT to use it or points to an alternative sibling (e.g. dyoe_extract), so the routing guidance is only implied.

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?

Annotations already declare readOnlyHint and openWorldHint, so safety is covered. The description adds genuinely useful operational context the annotations do not: the $0.01 USDC cost, the Base chain, and x402 payment mechanics — analogous to auth/rate-limit disclosure. It stops short of describing freshness, caching, or rate behavior.

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?

Extremely compact and front-loaded — the resource and scope come first, with cost and input requirements trailing. 'Input: (none)' is mildly redundant against the empty schema but earns its place by removing ambiguity for a paid call.

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 carries the burden of telling the agent what comes back, and it only loosely does so ('top gainers & losers'). It does not indicate how many entries, whether both lists are returned, or in what shape, which matters for a fixed-cost paid 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?

Zero parameters, so the baseline is 4; the description's explicit 'Input: (none)' reinforces the empty schema rather than leaving the agent to wonder if a hidden argument is expected. Nothing further is needed here.

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 concrete resource and scope: 24h top gainers and losers across the top 100 coins, which an agent can immediately match to a 'movers' request. It does not, however, distinguish itself from potentially overlapping siblings like dyoe_trending, dyoe_market, or dyoe_crypto.

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?

'For trading agents' names an audience rather than a usage condition, and no alternative tool or when-not-to-use case is given. The agent must infer that this is the right call for ranking-type 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?

Annotations already declare readOnlyHint and openWorldHint, covering the safety profile. The description adds valuable context beyond that: data is computed only from DYOE's own logged prior assessments, thin history is labeled, and the call costs $0.05 USDC on Base via x402. It does not cover rate limits or authentication beyond payment, but is strong for a read-only 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 purpose is front-loaded and the description is a single tight paragraph. The 'Input: ?target=' line is slightly redundant with the schema, but the pricing and payment details earn their place because they affect invocation.

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 usefully enumerates the return fields (assessment count, verdict history, flags, first/last seen, reputation score, signed credential). It also documents the data source limitation and payment model. It is nearly complete for a one-parameter read 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 single 'target' parameter is fully documented in the schema. The description repeats the parameter name but adds no syntax or format details beyond what the schema provides, making baseline 3 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 ('Look up') and resource ('track record of any domain or wallet') and enumerates the data returned. It distinguishes itself functionally from most siblings, but does not explicitly contrast with nearby tools like dyoe_verify or dyoe_intel, so it falls short of full sibling differentiation.

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 'a credit score for counterparties' implies a use case for evaluating counterparties before transacting, but there is no explicit when-to-use guidance, no when-not-to-use conditions, and no named alternatives. Usage is left 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?

Annotations only declare readOnlyHint=false and openWorldHint=true, so the description carries most of the weight and does it well: it discloses async behavior requiring polling, the $15.00 USDC-on-Base cost, and the x402 payment mechanism. The one blemish is the claim that pricing scales with 'the amount at stake' alongside a flat '$15.00 per call', which reads as inconsistent.

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

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

Three short sentences, front-loaded with what the tool does before the operational and pricing details. Minor waste: the $15.00 price already appears in the title and is repeated in the body.

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 correctly explains the return path (poll for the signed receipt) and covers cost and payment. The only gap is the unresolved price-scaling ambiguity, which matters because amount appears to drive 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%, so all three parameters already carry their own descriptions and examples. The description merely restates the input list and flags counterparty as required, which is already in the schema's required array. 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?

The first sentence gives a specific verb and resource: a named human reviews an agent action against a checklist and signs off. That is far more than a restatement of the name. It does not, however, distinguish itself from close siblings like dyoe_verify or dyoe_approve, so an agent comparing them gets no explicit differentiation.

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 the tool applies (agent actions needing human sign-off) and gives operational guidance by naming the polling endpoint /api/task?id=<id>. It never states when not to use it or which sibling to pick instead, even though dyoe_verify and dyoe_approve sit right next to 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?

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds genuinely useful operational context beyond them: the per-call cost ($0.05 USDC on Base) and payment mechanism (x402), plus the fact that two distinct data categories are returned.

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 core sentence is front-loaded and efficient, but the trailing fragment 'Input: ?symbol=' appears to be leftover API-doc syntax and adds no value given the schema. The price is stated twice (description and title), a minor redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description must convey returns, and it does name the data categories (price, market data, scam/rug-risk). Cost and payment rail are also disclosed. A brief note on return shape or any rate limits would make it complete.

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

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

Schema description coverage is 100% with a single required 'symbol' parameter whose format is documented in the schema. The description's 'Input: ?symbol=' restates the parameter without adding format or constraint detail, 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?

Specific verb ('Look up') plus resource and scope: price/market data and a scam/rug-risk read, framed as a combined call. An agent can distinguish it from plain market-data siblings by the bundled trust/safety read. However, no sibling is named, so it doesn't fully differentiate from dyoe_market or dyoe_crypto.

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 described scope ('market data and counterparty trust in one call'), but there is no explicit when-to-use vs when-not, and no routing to dyoe_market/dyoe_crypto for pure price lookups.

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?

Annotations only declare readOnlyHint/openWorldHint; the description adds material context beyond that: the response vocabulary (proceed/caution/stop, reasons, signed attestation), the fact that it is a zero-mutation pre-flight despite the 'transaction' name, and the paid-call mechanics ($0.10 USDC on Base per call via x402) which an agent must know before invoking. It also clarifies this is a consolidation of three checks rather than a fourth check.

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-loaded with the purpose and the go/no-go value proposition, then the return values, then inputs and price — a sensible priority order with no filler. The query-string example is slightly redundant against the JSON schema but still earns its place as a usage illustration.

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 correctly carries the return-value burden (proceed/caution/stop, reasons, attestation), and pricing is disclosed. The gap is that the schema marks all 3 parameters optional (required: 0) and the description never says what happens with partial input — e.g. domain-only vetting — which an agent would need to know.

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 semantic meaning by mapping each input to the check it drives: domain → counterparty legitimacy, wallet → payee sanctions/disposable detection, amount → policy threshold. The inline '?domain=merchant.com&wallet=0x...&amount=500' example reinforces the shape of a real 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?

Specific verb ('Vet') plus specific resource and scope ('an entire payment before an agent sends money'), and it immediately enumerates the three dimensions checked: domain legitimacy, wallet sanction/disposable status, and amount policy. That scope ('entire payment') is what distinguishes it from the per-check siblings like dyoe_verify / dyoe_wallet / dyoe_merchant, even though those names aren't cited directly.

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?

'Vet an entire payment before an agent sends money' gives a clear trigger condition, and 'one go/no-go instead of three calls' establishes that this is the aggregate alternative to multiple single-check calls. It lacks an explicit negative case (e.g. 'use dyoe_wallet if you only need a wallet check'), so the routing guidance is clear but not fully enumerated.

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?

Annotations already cover the safety profile (readOnlyHint, openWorldHint), and the description adds critical operational context beyond them: this call costs $0.01 USDC on Base and is settled via x402. That payment requirement is exactly the kind of behavior an agent must know before invoking. It does not describe return shape or data freshness beyond 'right now'.

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 sentences, front-loaded with the resource and purpose, then the empty input and price. No wasted text, though the pricing details are compressed into a somewhat dense clause.

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-only, paid tool with no output schema, the description covers purpose, inputs, and cost. The only real gap is what the response contains and how 'trending' is scoped, which an agent would have to discover on first 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?

Zero parameters, so the baseline is 4. The description explicitly confirms 'Input: (none)', which reinforces the empty schema and removes any doubt about required arguments.

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 ('coins trending right now') with a clear read-oriented purpose. It doesn't explicitly differentiate from similarly themed siblings such as dyoe_movers or dyoe_market, so it falls 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?

The audience phrase 'for trading & research agents' implies when the tool is useful, but there is no when-to-use vs. when-not guidance and no named alternative among the many market/coin siblings. Usage is implied, not specified.

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?

Annotations already declare readOnlyHint and openWorldHint, so the description's added disclosure of price ($0.01 USDC on Base), payment mechanism (x402), and return fields (verdict, trust_score, domain age, red_flags) is valuable and exceeds the structured annotations. No contradiction with annotations.

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

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

Three sentences, front-loaded with the core purpose before return values and pricing. Every sentence adds useful information without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter read-only tool with no output schema, the description covers purpose, usage context, return values, and payment details. Nothing critical for correct invocation 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 schema already documents the single target parameter. The description repeats '?target=domain' and only loosely suggests broader target types (website/business/wallet), but adds no format or syntax 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 verb (check) and resource (website, business, wallet) with a clear outcome (scam detection, fraud/phishing/rug-risk screening). However, it does not explicitly distinguish itself from overlapping siblings such as dyoe_reputation or dyoe_intel, so it falls 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?

Provides clear context for when to use it: 'before an agent trusts or pays it'. No exclusions or alternative tools are named, so it lacks the explicit when-not/alternatives guidance that would earn a 5.

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?

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds valuable behavioral context beyond that: the price ($0.05 USDC on Base), the x402 payment mechanism, and the shape of the verdict output (safe/caution/avoid). No return format or latency/auth caveats beyond the payment note.

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-loaded with purpose, then the checks, then outputs, then input and price in distinct clauses. Dense but every element earns its place; no redundancy.

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 single-parameter, read-only screening tool with no output schema, the description supplies the trigger context, the checks, the return fields (verdict, sanctioned flag, activity, red_flags), and the cost. Nothing an agent needs to invoke it 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 description is 100% covered and already documents the single 'address' parameter with an example. The description restates the input format ('?address=0x...') but adds no semantics beyond what the schema provides, 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?

Names a specific verb ('Screen') and resource ('crypto wallet address') and enumerates the exact checks performed (OFAC sanctions, on-chain footprint, human-vouch overlay). No sibling tool overlaps this screening role, so an agent can identify it cleanly.

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?

States the clear use context: 'Screen a crypto wallet address before an agent sends funds to it', giving the trigger condition. However, it does not name an alternative or state when-not to use this (e.g. versus a reputation or intel sibling), so no exclusions 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?

Annotations already cover safe-read (readOnlyHint) and open-world scope, and the description adds non-trivial behavioral context the annotations don't: the $0.01 USDC cost on Base paid via x402. Cost/payment mechanics are exactly the kind of thing an agent needs before calling. It does not, however, mention rate limits, latency, or failure/error behavior.

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

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

A single compact sentence with the capability statement front-loaded, followed by cost. The 'Input: ?city=Atlanta' fragment duplicates schema information and is mild waste, but overall it is tight and readable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description does state what comes back (current conditions + 3-day forecast) and covers payment mechanics. Only minor gaps remain around response shape specifics and error behavior, which are acceptable for a one-parameter read 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% and the single 'city' parameter is already documented in the schema, so the schema carries the burden. The description's 'Input: ?city=Atlanta' restates the same example rather than adding meaning. 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+resource with scope: current conditions plus a 3-day forecast for any city. The audience note ('for travel & planning agents') further narrows intent. It is clear enough to distinguish from siblings like dyoe_fx or dyoe_destination, though it doesn't name a sibling directly.

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 'for travel & planning agents' implies the usage context but gives no explicit when-to-use, when-not-to-use, or named alternatives among the 21 sibling tools. Guidance is present but only inferred.

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?

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds genuinely useful behavior the annotations lack: the cost model ($0.01 USDC on Base per call, paid via x402), which is effectively an auth/payment prerequisite. It omits rate limits and output characteristics.

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 sentences, front-loaded with the purpose before the pricing detail. Minor waste: 'Input: ?topic=Bitcoin' duplicates the schema and the $0.01 price is already carried in the title.

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 should say something about what the summary looks like (length, format, structure), and it does not. Purpose, cost, and payment mechanism are complete enough to invoke it, but the return contract is 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?

Schema description coverage is 100% and the single parameter is fully documented in the schema, so the baseline is 3. The description's 'Input: ?topic=Bitcoin' merely restates the schema example without adding syntax, constraints, or format meaning beyond it.

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: 'Factual summary of any topic from Wikipedia.' An agent immediately knows what the tool returns and the source domain. It does not, however, differentiate itself from any sibling tool by name or contrast, though no sibling appears to overlap with Wikipedia summarization.

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?

'for research agents' implies a usage context but gives no explicit when-to-use, when-not-to-use, or alternative tools. There are no exclusions and no prerequisites stated 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.