Saylor Innovations: pay-per-call data

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is known. The description adds useful behavioral facts beyond the annotations: the output contains top 20 holders, percent of supply, per-wallet insider labels, and that the tool costs $0.01 with a free sample URL. It does not describe response envelope or failure modes, but those are minor for this read-only single-parameter 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?

The description is dense but efficient: it front-loads the purpose, lists the exact output fields, distinguishes the sibling tool, and adds pricing and a free sample link—all in a few clauses. There is no filler or repeated schema information.

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

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

For a simple read-only endpoint with one documented parameter and no nested output, the description covers what an agent needs: what the tool returns, how it differs from the related tool, the cost, and an example sample. The lack of an output schema is mitigated because the description names the output contents explicitly.

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 only parameter, mint, is already documented as a Solana mint address in base58. The description adds no new parameter-level details beyond reinforcing the Solana context, so the schema carries the weight. 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 states a specific verb ('Check'), a specific resource ('holder concentration' for a Solana token), and quantifies the output (top 20 holders with percent of supply and RugCheck's insider label). It also explicitly contrasts itself with check_token_security, so an agent can distinguish the tool immediately without opening the 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?

The description names the key alternative, check_token_security, and explains the difference: this tool gives per-wallet top-20 detail rather than a rolled-up top-10 percentage. That gives an agent a clear basis for choosing between the two. It does not explicitly list all when-not-to-use conditions, but the comparison is enough for practical 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, covering safety. The description adds the non-obvious billing detail 'Costs $0.005,' which is valuable behavioral context beyond the structured 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?

The entire description is one efficient sentence that front-loads the purpose, enumerates the categories, mentions socials, and discloses cost. No filler or redundant restatement of the name or schema.

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, idempotent tool, the description is nearly complete: it states the output domain, lists categories, notes socials, and gives the cost. The only minor gap is that the exact structure of the socials output is not described, but this is acceptable without an output schema for a simple classification 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%, with the single 'mint' parameter already documented as a Solana base58 address. The description adds no additional parameter-level meaning, so the baseline score of 3 applies.

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

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

The description clearly states what the tool does: classifies a token into one of ten named narrative categories and provides socials. This distinguishes it from sibling token tools like check_token_price and check_token_holders, which focus on different data.

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 intended use is implied by the description: call this when you need a token's meme/narrative category and socials. However, it does not explicitly say when not to use it or how it differs from related tools such as check_token_snapshot, so the agent must infer the selection criteria.

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 establish read-only, idempotent, non-destructive behavior. The description adds valuable behavioral context: data comes from two independent sources, the spread is reported and itself meaningful, and there is a specific cost. 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?

Two tight sentences with no filler. The core function is front-loaded, and the cost/polling note is placed second as a natural usage qualifier. Every word earns its place.

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

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

For a one-parameter read-only endpoint with rich annotations, the description is nearly complete: it states what is returned (price, liquidity, spread), the source behavior, and cost. It does not specify units or output shape, but the absence of an output schema and the tool's simplicity make this a minor gap.

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

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

Schema coverage is 100% and the only parameter, mint, is already described as a Solana mint address. The description adds no new parameter-level detail, 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 names a specific resource (Solana token), a concrete operation (fetch price and liquidity), and a distinctive differentiator (two independent sources with reported spread). This clearly separates it from siblings like check_token_security or get_price_history.

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

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

The description gives clear context for when to use it: it is the cheapest endpoint and 'built for polling,' implying repeated low-cost checks. It does not explicitly name alternatives or exclusion criteria, but the polling/cost framing is strong usage 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 mark the tool read-only and idempotent, and the description adds valuable non-inferable behavior: the $0.01 cost, the free sample URL, and the payment-requirements/URL-to-call flow. No contradiction with the annotations 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?

The description is front-loaded with the core purpose, followed by a compact list of outputs and then the cost/sample/payment details. Every sentence carries distinct information with no filler or repetition.

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 covers the main report contents, cost, sample endpoint, and the unusual paid-URL flow. The only weakness is ambiguity about whether the immediate response is the full report or a payment redirect, but an agent still has enough information to call the tool and interpret its result.

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

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

The schema already documents the only parameter, mint, at 100% coverage with 'Solana mint address (base58).' The description reinforces that the target is a Solana token but does not add meaningful parameter-level detail beyond the schema, so the baseline score 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 names a concrete function ('rug risk check') and the resource ('Solana token'), then enumerates specific report contents such as mint/freeze authority, LP lock, holder concentration, RugCheck risks, and a security score. This clearly distinguishes it from sibling tools focused on holders, narrative, or price.

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

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

The 'is this token safe to buy?' framing establishes a clear pre-purchase safety-assessment use case, which is distinct from the related token tools. It does not explicitly name alternatives or exclusions, but the context is sufficient for an agent to decide when to invoke 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?

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile, so the bar for additional disclosure is lower. The description adds real behavioral context beyond the annotations: the call costs $0.01 (a paid operation, which an agent should know before invoking), and the data is 'sampled' (age) with a 'failed-transaction rate' and behavioural flags, implying heuristic rather than exhaustive computation. No contradiction with annotations 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?

The description is a single, efficient sentence with the core subject ('On-chain profile for a Solana wallet') front-loaded, followed by a compact enumeration of report contents and a closing cost note. Every clause earns its place, and the cost disclosure is important enough to include. No filler or 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 simple single-parameter read tool with full annotation coverage and 100% schema coverage, this is largely complete. Because there is no output schema, the description compensates by enumerating what the report contains (SOL balance, token positions, recent activity, etc.), giving the agent a sense of the return payload. The main gaps are the unspecified nature of 'behavioural flags' and the output format, but these are minor relative to the annotated safety profile and fully documented parameter.

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

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

Schema coverage is 100%: the single required parameter `address` is already described as a 'Solana wallet address (base58)' in the schema. The description only reinforces that the wallet is Solana-based and does not add syntax, format, or validation detail beyond the schema. With full schema coverage, 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 clear resource (Solana wallet) and a specific deliverable (an on-chain profile report) and enumerates its contents concretely: SOL balance, token positions, recent activity, sampled age, failed-transaction rate, and behavioural flags. It differentiates clearly from the token-focused siblings (check_token_holders, check_token_price, etc.) since it targets a wallet address rather than a token. An agent can immediately tell this apart from the sibling set.

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 or when-not-to-use guidance, and no named alternatives or exclusions. The usage context is only implied by the content (a wallet-level profile), which an agent can infer but is not told. It does not state, for example, 'for a token-level report, use check_token_* instead.' This is adequate but leaves the selection logic unstated.

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 carry readOnly, idempotent, and non-destructive signals, so the description need not re-state them. It adds the affordable per-mint price and lighter payload comparison, but it does not disclose output shape or any rate-limit/error behavior beyond what the annotation hints provide.

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 are efficient and front-load the action and scope. The final sentence somewhat repeats the one-request idea already in the first sentence, which keeps it from a 5.

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 batch tool, the description covers purpose, range, token format, pricing, and when to use it. With no output schema, it could say a bit more about what the returned scores contain, but the main context an agent needs to call it correctly 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% and the schema already documents mints as Solana mint addresses in base58, 2 to 10. The description repeats the 2-10 range but adds no new param-level meaning, so baseline 3 is appropriate.

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

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

Description begins with a specific verb-plus-resource: produces Watchdog scores for 2-10 Solana tokens side by side in one request. It also names get_token_snapshot as a sibling alternative, so an agent can distinguish it from similar token tools.

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

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

It clearly frames the tool for screening a watchlist in one call and compares pricing to get_token_snapshot, implying when the lighter payload is preferable. It stops short of explicitly saying when not to use it or naming other alternatives, so not a full 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 cover readOnly, openWorld, idempotent, and non-destructive hints, so the description is not required to repeat them. It adds valuable behavioral details: the cost ($0.003), the return of payment instructions for the Saylor endpoint, and the lack of a provider account requirement. These are beyond what annotations provide and are essential for an agent to decide whether and how to invoke the 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?

Two sentences, each earning its place: the first states the purpose and output fields, the second adds cost and access requirements. The purpose is front-loaded, and there is no redundant or filler content.

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

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

The tool is simple with a single parameter, and the schema and annotations cover safety and parameter details. The description adds cost and authentication context, which is important. It does not describe the return format, but since there is no output schema, that might be a gap; however, the description hints at 'payment instructions' and the data fields, which is sufficient for an agent to understand the result. Slight lack of return structure prevents a 5.

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 schema description coverage is 100%, meaning the schema already fully documents the 'country' parameter, including an example ('US or GB') and the note that aggregates are excluded. The description only repeats 'two-letter country code' and does not add any additional semantics, formatting details, or edge-case guidance. Baseline 3 applies because 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 uses a specific verb ('Resolve') and clearly specifies the resource (two-letter country code) and the expected output (World Bank name, region, capital, income group, lending classification). It distinctly positions this tool as a data-enrichment lookup, which differentiates it from sibling tools like get_economy_report or get_fx_report without needing to name them.

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

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

The description mentions 'for data enrichment,' which implies a use case but does not explicitly state when to use this tool versus alternatives or when not to use it. There is no guidance on exclusions (e.g., aggregates are excluded, but that's in the schema, not the description). The usage context is present but not fully articulated.

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 mark the tool as read-only, open-world, idempotent, and non-destructive, and the description adds valuable context beyond those: it costs $0.003, returns payment instructions for the Saylor endpoint, and requires no provider account. This gives an agent critical cost and invocation context without contradicting the 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, each earning its place: the first states the core purpose, the second clarifies the tool's boundary, and the third communicates cost and access requirements. It is front-loaded and free of redundant wording.

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 a single parameter, no output schema, and comprehensive annotations, the description provides everything needed to call the tool correctly: the input, the expected output content, the cost, and the payment/access behavior. No critical information 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 coverage is 100% and the single 'cve' parameter is already documented with an example (CVE-2021-44228). The description reinforces that the parameter identifies a CVE but does not add substantive new parameter semantics 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 uses a specific verb 'Resolve' with a clear resource, CVE, and enumerates the concrete outputs: description, status, CVSS metrics, weakness identifiers, and vendor/reference links. It also distinguishes itself from security-scanning tools by stating 'This does not scan a system or prove safety.'

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 clearly indicates when to use the tool: when a CVE identifier needs to be resolved into published vulnerability details. It also gives an explicit when-not boundary by stating it does not scan a system or prove safety, though it does not name a specific alternative 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?

Annotations already declare read-only, idempotent, non-destructive behavior; the description goes beyond them by disclosing the $0.003 cost, the returned payment instructions, and that no provider account is required. These are exactly the operational traits an agent needs before invoking the tool. 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?

Four short sentences, front-loaded with the core purpose and followed by essential operational facts: exclusions, cost, and authentication context. Every sentence earns its place; the cost disclosure is material information for tool selection, not 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?

For a single-parameter tool with rich annotations and no output schema, the description enumerates the returned artifact categories and their exclusions while also covering cost and account requirements. Nothing an agent needs in order to call 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 coverage is 100%: the sole parameter is documented with its optional https://doi.org/ prefix. The description merely echoes that the parameter is a DOI without adding new format or usage nuance. With complete schema coverage, 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 names a specific action ('Resolve a DOI') and resource, then lists the exact delivered outputs: normalized metadata, citation text, identifiers, and source links. The explicit exclusion of abstracts and full text sharpens the boundary against document-retrieval tools. Among 27 sibling tools, the DOI/citation scope is 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 intended use case—having a DOI and needing citation-level metadata—is clearly implied by the first sentence, and the abstract/full-text exclusion signals what this tool is not for. However, no alternative tool is named and no explicit when-not condition is stated, so an agent must infer routing from DOI-specific vocabulary rather than being directed.

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?

The description adds meaningful behavioral details beyond annotations: it discloses a cost of $0.003, returns payment instructions for the Saylor endpoint, and notes no provider account is required. It also describes the output contents (years, units, source links, missing values), which enriches the annotation-only safety profile.

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 with no waste. The core action is front-loaded, followed by cost and output details. Every sentence adds value.

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

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

The description covers the output contents, cost, and authentication requirements. Since there is no output schema, it adequately explains what the agent will receive. It could be more complete by specifying what 'recent' means, but that is minor.

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 schema already documents the country parameter well with an example and exclusion of aggregates. The description does not add further meaning about the parameter itself, so it stays at the baseline for full schema coverage.

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

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

The description clearly states the tool retrieves up to five recent annual observations for population, GDP, and consumer-price inflation. It specifies the resource (economic indicators) and verb (get), but does not explicitly differentiate from sibling tools like get_country_report, which may overlap.

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

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

No guidance is provided on when to use this tool versus alternatives. The description does not mention any exclusions or conditions, leaving the agent to infer usage solely from the content.

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, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds useful behavioral context: it returns price and payment instructions, is free, and the agent then pays and receives data. It also clarifies the input is a fully-qualified URL from search_endpoints, adding value beyond annotations without contradicting them.

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 with zero fluff. It front-loads the purpose ('Given an endpoint URL from search_endpoints...'), states the return contents, and adds the 'Free.' note. Every sentence earns its place; it is concise and well-structured.

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

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

The tool is simple (one parameter, no output schema), and the annotations already cover safety and idempotency. The description explains the return content (URL, price, payment instructions), the source of the input, and the overall flow. Nothing an agent needs to call 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 coverage is 100% (the url parameter is fully described as a full https URL including query parameters). The description adds meaning by specifying the URL should come from search_endpoints and have its parameters filled in, which clarifies the expected source and format. This enriches the parameter's semantics 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 states a specific verb ('returns'), a clear resource (endpoint price/payment instructions), and a distinct flow: given an endpoint URL from search_endpoints, it provides the exact resource URL, price, and x402 payment instructions. It also mentions 'Free.' to signal cost. This clearly differentiates from search_endpoints (which finds endpoints) and other sibling tools that check tokens or reports.

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

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

The description explicitly says 'Given an endpoint URL from search_endpoints', which establishes the tool's place in the workflow: use after search_endpoints to obtain payment details. It implies the usage context (post-search, pre-payment) and the flow of paying over HTTP. However, it does not explicitly state when not to use it or name alternatives, but the context is clear enough.

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/idempotent/non-destructive behavior, and the description adds meaningful operational details: the call costs $0.003, no provider account is required, and the data is ECB-sourced. 'Returns payment instructions for the Saylor endpoint' is an odd disclosure but does not contradict the annotation hints.

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 and front-loaded with the main purpose; every sentence carries a distinct fact (scope, non-quote status, free source, cost, auth). The 'Returns payment instructions' sentence is the least cleanly tied to the rest but is not 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?

For a one-parameter, read-only, annotated tool this is nearly complete: the description covers what is returned (rates, observation date, currency codes) and how the call is constrained. Without an output schema it could specify the response shape more precisely, but the information an agent needs to select and invoke it 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 coverage is 100% and the only parameter, 'base', is already described as a three-letter ECB-supported currency code. The description's 'per one unit of a base currency' clarifies rate semantics slightly, so it earns the baseline 3 but adds little 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 opening sentence names a specific verb ('Get') and resource ('daily reference exchange rates per one unit of a base currency'), and the disclaimer 'Not executable trading quotes' sharpens the scope. It is clear enough to distinguish from sibling report tools by resource type, though it never names a sibling directly. The later phrase 'Returns payment instructions' slightly muddies the core function.

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

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

The description gives useful context: it is for reference rates, not executable quotes, and notes the same ECB data is available free from ecb.europa.eu. However, it does not give explicit when-to-use guidance or point to an internal alternative among the siblings; usage is mostly implied by the tool name and first sentence.

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, idempotentHint, and destructiveHint false, so the tool is known to be safe and non-mutating. The description adds substantial behavioral detail: free guides return the full body immediately, paid guides return payment requirements (a URL) instead of the body, and a PAYMENT-SIGNATURE header is needed to complete payment. It also specifies the cost and payment networks. This goes far beyond the annotations and is crucial for correct invocation.

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 three sentences with zero wasted words. The core purpose is front-loaded ('Fetch a guide by id'), followed by the free/paid distinction and payment flow. Every sentence adds essential information, and the structure is logical and scannable.

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

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

Given there is no output schema, the description fully explains what the tool returns in both cases (free vs paid), including the payment completion step. It covers the cost, payment methods, and the required header, which is all an agent needs to correctly invoke the tool and handle the result. Nothing critical 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?

There is only one parameter, 'id', and the schema already describes it as 'Guide id, from search_guides' with 100% coverage. The description repeats the purpose ('by id') but adds no new format, syntax, or constraints beyond the schema. Baseline of 3 is appropriate since the schema fully documents the parameter.

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

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

The description states a specific verb ('Fetch') and resource ('a guide by id'), clearly distinguishing it from search_guides which finds guides. It also clarifies the free vs paid distinction, so an agent knows exactly what this tool does and how it differs from siblings.

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: use this when you have a guide id (from search_guides, as noted in the schema). It provides clear context about free vs paid behavior and how to complete payment, but it does not explicitly state exclusions or name alternatives like 'use search_guides to find guides first.' Still, the context is clear enough for correct selection.

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, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds valuable behavioral context: the tool costs $0.003, returns payment instructions for the Saylor endpoint, and requires no provider account. This goes beyond the annotations without contradicting them.

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 with no wasted words. It front-loads the primary purpose and return contents, then adds cost and authentication context. Every sentence contributes useful information.

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

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

For a simple one-parameter, read-only tool, the description is largely complete: it states the result fields, the limit of five packages, the cost, and the account requirement. The only minor gap is that 'Saylor endpoint' is not explained, but this does not prevent correct invocation.

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

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

The schema already fully documents the single parameter 'q' with a description of 'Search terms, 2–160 characters.' The tool description adds no additional parameter semantics beyond implying that 'q' is the search query for npm packages, so the schema carries the burden.

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

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

The description clearly states the tool's function: finding up to five npm packages with specific fields like versions, descriptions, and registry ranking scores. It is specific about the resource (npm packages) and the action, but it does not explicitly differentiate itself from the sibling get_package_report, leaving some 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 implies use for npm package discovery and provides useful context about cost and no provider account being required. However, it does not state when to prefer this tool over alternatives or mention any exclusions, so usage guidance is only implied rather than explicit.

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 idempotentHint, covering the safety profile. The description adds significant extra context: the cost ($0.003), payment instructions for the Saylor endpoint, and the explicit statement that it does not download or execute package code. This goes beyond what annotations provide.

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 with zero waste. The core purpose is front-loaded, followed by essential caveats (cost, payment, safety). It is concise and well-structured, earning every word.

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 tool with no output schema, the description covers all necessary aspects: what data is returned, cost, payment process, and safety. It is complete for an agent to invoke correctly without additional assumptions.

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 schema fully describes the 'name' parameter with a clear explanation of the expected format, so the description adds no parameter-specific meaning. Since schema coverage is 100%, a baseline of 3 is appropriate, and the description does not compensate further.

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

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

The description clearly states the tool inspects the latest npm package release and enumerates specific details (version, license, dependency counts, engine requirements, deprecation notice, source links). It distinguishes itself from sibling token/wallet tools and even clarifies it does not execute code, making the purpose 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 description implies usage when one needs npm package release information, but it does not explicitly contrast with alternatives like get_npmsearch_report or mention when not to use this tool. There is no exclusion or alternative guidance, so the agent must infer the appropriate context.

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 readOnly/openWorld/idempotent/non-destructive, and the description adds substantial behavioral context beyond that: a hard cost of $0.003, payment instruction handling, no provider account requirement, and a clear metadata-only boundary. This fully discloses what the agent and user should expect from the call.

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

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

Three sentences, each earning its place: the first states the core capability and output fields, the second sets the scope boundary (metadata not full text), and the third covers cost and authentication. Front-loaded and free of 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 tool with no output schema, the description covers everything an agent needs: purpose, result shape, result limit, cost, payment instructions, and auth requirements. Nothing material 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 coverage is 100%, so the q parameter is already fully documented as 'Search terms, 2–160 characters.' The description adds a result limit ('up to five') but no additional parameter detail, so a baseline of 3 is appropriate since 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 states a clear verb ('Find'), a specific resource ('publications'), and concrete return fields (DOI identifiers, authors, publication years, citation counts). It also distinguishes itself from related report tools by specifying the publication domain and the metadata-only scope.

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

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

The description gives clear context for when to use the tool: when publication metadata is needed, and explicitly says it does not return abstracts or full text, which hints at when not to use it. It does not name alternatives, but the boundary it draws is enough for an agent to route correctly among the many report siblings.

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 provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the description doesn't repeat those. It adds useful behavioral context: it pulls from the highest-liquidity pool and costs $0.01, which are not in 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?

The description is two sentences with zero fluff. It front-loads the core purpose, then adds the unique differentiator and cost. Every sentence earns its place.

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

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

Given the tool's simplicity (3 params, all documented) and that annotations cover safety, the description provides enough context for an agent to call it correctly. It mentions the source (highest-liquidity pool), the unique time-series nature, and cost. Without an output schema, it hints at the return format (OHLCV candles) but doesn't detail it, which is acceptable.

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

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

Schema description coverage is 100%, so all parameters (mint, limit, timeframe) are already documented with clear descriptions. The description adds contextual meaning by mentioning OHLCV candles and highest-liquidity pool, but this doesn't go beyond what the schema already implies. Baseline 3 is appropriate when schema covers parameters fully.

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

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

The description clearly states the tool returns OHLCV candles for a Solana token from its highest-liquidity pool, which is specific and distinguishes it from siblings by noting it's the only time-series data in the catalog. The verb and resource are clear, and it differentiates from other point-in-time snapshot endpoints.

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

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

It explicitly states this is the only time-series data and every other endpoint is a point-in-time snapshot, which tells the agent when to use this tool (for historical price data) and implies alternatives for snapshots. It also mentions cost, which is a usage consideration. It doesn't name specific sibling tools, but the general distinction is sufficient.

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 cover read-only/idempotent/non-destructive hints. The description adds valuable behavioral disclosures: 'No code execution' addresses a safety concern, and the $0.003 cost plus payment instructions are critical for an agent deciding to call it. It also clarifies no provider account is required, exceeding the annotation baseline.

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 with zero fluff. The core purpose is front-loaded, followed by critical cost and security notes. Every sentence earns its place.

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

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

For a simple one-parameter tool with no output schema, the description fully covers what data is returned, cost, execution safety, and authentication requirements. No gaps remain for an agent 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?

Input schema covers 100% of the parameter with a clear description ('Public Python package name'). The description does not add new parameter-level details like case sensitivity or formatting, so it stays at the baseline for high schema coverage.

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

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

Description gives a specific verb ('Inspect') with a resource ('Python package') and enumerates exact data fields (latest release, Python compatibility, dependencies, license, advisories). The Python-specific scope clearly distinguishes it from siblings like get_npmsearch_report and get_package_report.

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 makes the tool's context obvious (Python packages on PyPI) and implies it is the appropriate choice for Python package metadata. It does not explicitly name alternative tools or exclusions, but the python-specific scope and sibling names provide sufficient 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, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds the cost ($0.005) and outlines the output fields (age, liquidity, buy/sell flow, risk flags), which are useful behavioral details beyond the annotations. No contradiction 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?

The description is a single sentence that front-loads the core purpose ('Brand-new Solana pools'), then efficiently adds cost and data composition. Every word earns its place with 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 simple list tool with two optional parameters and no output schema, the description covers what the tool returns (age, liquidity, buy/sell flow, risk flags) and the cost. Annotations handle the safety profile, so nothing essential is missing for an agent to decide when and how to call it.

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

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

The schema covers 100% of parameters with descriptions for minLiquidity and maxAgeMinutes. The tool description does not add any extra meaning about these parameters beyond what the schema already provides, so the baseline of 3 applies.

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

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

The description clearly states the resource (Solana pools) and the distinguishing attribute (brand-new, seconds to minutes old). It also lists the data included (age, liquidity, buy/sell flow, risk flags), making it distinct from siblings like get_trending_pools or get_token_snapshot.

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 'the most perishable data here' implies this is for the newest pools, but it does not explicitly name alternatives or conditions for when not to use it. The usage context is implied rather than stated, so an agent must infer that fresher data is the intended use case.

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 carry the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), lowering the bar. The description adds genuine value beyond them by disclosing the $0.005 cost, a real behavioral trait an agent needs before committing, plus the comprehensive data scope. No contradiction with annotations; the return format isn't detailed but there is no output schema to contradict.

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

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

A single sentence that front-loads purpose, lists contents, and closes with the cost. Zero filler; every clause earns its place and the cost disclosure is placed at the end where it reads naturally. Ideal density for an agent-facing definition.

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 aggregate snapshot with strong annotations and full schema coverage, the description is nearly complete: it enumerates the data categories returned and the cost. It doesn't describe the response structure or pagination, and with no output schema to lean on that is a minor gap, but the enumerated contents give an agent enough to judge relevance before calling.

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

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

Schema coverage is 100% — the sole parameter mint is already described as a 'Solana mint address (base58)'. The description adds no extra parameter semantics beyond what the schema documents, so the baseline 3 applies. The description implies the mint targets a Solana token but adds no 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?

States a specific verb+resource: 'Complete Watchdog snapshot for a Solana token in one call' and enumerates the delivered data (price, liquidity, holders, pairs, socials, security flags, scores). The word 'Complete' plus the single-call framing distinguishes it from single-aspect siblings like check_token_price, check_token_holders, and check_token_security, so 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 phrase 'in one call' implies this is the all-in-one aggregation tool versus the granular single-aspect checkers, and the $0.005 cost signals a paid call. However, it never names an alternative or states when NOT to use it (e.g., when only price is needed, prefer check_token_price). The usage context is clear but implicit; no explicit exclusions or alternative 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?

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds the monetary side effect ('Costs $0.01') and the returned metric set, which goes beyond what the annotations and schema convey.

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 with no filler; every clause carries information about resource, time window, output metrics, and cost. It avoids duplicating schema or annotation data.

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

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

For a simple read-only tool with one optional parameter and full schema coverage, the description is nearly complete. It could clarify the default limit behavior, but that is a minor gap given the schema already documents 'Max 50.'

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 optional parameter already has a descriptive description ('Max 50'). The tool description adds no parameter-level semantics, so the baseline score of 3 applies.

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

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

The description names a specific resource (Solana pools), a state ('currently trending'), and the returned metrics (price, liquidity, volume, 24h change), which clearly distinguishes it from token/price-focused siblings like check_token_price and get_price_history.

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

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

The intended use is implied: call it when you need currently trending Solana pools and their market metrics. However, it does not explicitly state when not to use it or name alternatives, so it earns only partial credit.

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?

Beyond the annotations, the description adds meaningful behavioral detail: nothing is hosted, credentials remain with the renter, the call is free, no performance/profitability data can be reported, and trading risks total loss. This contextualizes the read-only, non-destructive, idempotent annotations and sets accurate expectations.

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 three sentences, front-loaded with the core purpose, then adding operational and risk context that is directly relevant to an agent's decision to call it. No sentence is wasted or redundant.

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

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

Even without an output schema, the description tells the agent what to expect: rentable bots, prices, durations, and the important caveat that no performance data is reported. For a parameterless list tool, this is fully sufficient for correct selection and invocation.

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

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

The tool has zero parameters and the schema is fully complete, so there is nothing for the description to clarify about inputs. The description instead usefully conveys what the returned list includes: prices and durations.

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

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

The description opens with a clear verb and resource: it lists trading bots available to rent, with prices and durations. It distinguishes this from siblings by describing a specific rental marketplace concept that no other sibling tool covers.

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

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

The description gives clear context for when to use the tool: when seeking rentable trading bots with fixed periods, pricing, and buy-in expectations. It explains the self-hosted model and that no credentials are sent, which guides trust expectations, though it does not explicitly name alternatives or say when not to use 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 cover read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond those: it is free (cost/rate implication) and returns the complete result in a single call ('One call reveals the whole shape'), which implies no pagination or partial results. 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?

Two short sentences with zero filler. The resource and scope come first, then the behavioral notes. Every clause adds distinct information: catalog scope, counts, cost, and one-call completeness.

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, read-only, idempotent list operation, the description plus annotations fully equip an agent to call it. No output schema exists, but the simple return (categories and tags with counts) is adequately implied. Nothing critical 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?

The tool has zero parameters, and schema coverage is trivially 100%. The baseline for 0-param tools is 4, and the description correctly emphasizes that no input is needed ('One call reveals the whole shape'). No parameter-level detail is required.

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 ('Every category and tag in the catalog') and adds the outcome (counts, full shape). It is unambiguous about what this tool returns. It does not name sibling tools or contrast itself, but the resource is distinct enough among siblings like list_bot_rentals and list_data_endpoints.

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 context is implied by 'One call reveals the whole shape' — an agent can infer this is the go-to tool for exploring the catalog taxonomy. However, there is no explicit when-to-use guidance, no exclusions, and no mention of alternatives, leaving routing to inference.

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

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

Annotations already declare readOnly, idempotent, and non-destructive behavior, lowering the burden on the description. The description adds useful context that the tool is free, that results include prices and payment instructions, and that it is meant as an entry point. No annotation contradiction.

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 with no filler. The first defines what the tool returns in a compact list of data categories, and the second gives a direct usage directive. Key context, including cost and ordering, is packed efficiently.

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

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

For a zero-parameter list tool with rich annotations, the description covers purpose, scope, cost, and invocation ordering. It does not describe the output structure, but with no output schema and simple list semantics, this is a minor gap rather than a blocking omission.

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

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

There are zero parameters and schema coverage is 100%, so there is no parameter ambiguity for the description to resolve. This matches the baseline for a no-parameter tool; nothing more is needed in the description.

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 title and description identify a clear verb (list) and resource (data endpoints), then spell out the scope: 'live Solana token, wallet, launch and market data' plus pricing/payment details. This distinguishes it from sibling tools like get_endpoint or search_endpoints by presenting itself as the broad catalog of everything available.

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

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

The description explicitly tells the agent when to use it: 'call this first to see what exists.' This is actionable and prevents agents from guessing which endpoint to start with. It does not name sibling alternatives or state when not to use it, but the first-call directive provides strong usage 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?

Beyond the annotations (readOnly, openWorld, idempotent, non-destructive), the description discloses that the search is free, requires no account or API key, uses x402, and returns a specific set of fields: url, example call, free sample response URL, price, and description. This is rich behavioral context that the annotations do not provide.

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 long, but the lengthy category list serves a clear purpose for a search tool by showing the breadth of searchable content. The workflow sentence at the end is compact. It could be better structured with line breaks, but every part earns its place.

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

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

With no output schema, the description appropriately names the return fields and the follow-up step (get_endpoint), which is enough to invoke the tool correctly. It does not mention pagination or sorting behavior, but the schema covers the limit parameter and the tool's core use is clearly defined.

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 query parameter is already documented in the schema with concrete examples, and the description's domain list helps the agent formulate queries. However, the description does not add meaning for the limit parameter, and with 50% schema description coverage the description only partially compensates for undocumented 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 opens with a specific verb and resource: 'Search the full Saylor catalog of 240+ pay-per-call data endpoints'. It clearly states the scope (full catalog) and enumerates dozens of domains, so an agent can distinguish this broad discovery tool from the many narrow check_* and get_* sibling tools. The title and description align.

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 establishes a clear workflow: use this tool to search and discover endpoints, then 'call get_endpoint for payment details.' It also clarifies that the search itself is free and requires no account. However, it does not explicitly contrast with list_data_endpoints or list_categories, so it stops short of fully explicit alternative 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the read-only safety profile is covered. The description adds valuable behavioral context beyond that: the guides are free ('no payment') and the operation returns only metadata, never bodies. These details help an agent set expectations without contradicting 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 short sentences with no fluff. Purpose is front-loaded, followed by cost and return-type constraints. Every sentence earns its place.

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

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

The description covers purpose, cost, and the metadata-only return constraint, and annotations cover safety. However, with no output schema, the description does not detail what metadata fields are returned or how results are paginated. For a tool with 5 optional parameters, this leaves some room for agent uncertainty about the exact response shape.

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

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

Schema description coverage is 60%, so the schema documents tag, query, and free_only but leaves limit and category underdocumented. The description adds some indirect parameter context by listing topic areas (which map to categories) and mentioning 'Free — no payment' (relating to free_only), but it doesn't systematically explain parameters. This is adequate but not a strong compensation for the coverage gap.

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

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

Description states the specific verb 'Search' plus the resource 'Saylor Innovations technical guides' and lists topic areas. It further distinguishes itself from siblings like get_guide by explicitly saying 'Returns metadata only, never bodies.'

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

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

The description implies the use case—finding technical guides before retrieving them—and the 'never bodies' line hints at a boundary with get_guide. However, it never explicitly says 'use this to discover guides, then call get_guide for full content' or names any alternative. No clear when-not-to-use guidance is provided.

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

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

Annotations declare readOnlyHint, idempotentHint, and destructiveHint false; the description adds context that the tool clones into a disposable environment (non-persistent), runs only declared scripts, and charges $0.25 per attempt. It discloses cost and the limitation on semantic correctness, which go beyond annotations. No contradiction is present.

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 three sentences with no fluff. It front-loads the core action, then states exclusions and cost. Every sentence adds essential information, and the structure is scannable.

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

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

Given there is no output schema, the description explains what is returned: 'structured logs plus the resolved commit' and 'the paid HTTP endpoint and x402 instructions.' It covers the core behavior, limitations, and cost. It could mention timeout behavior or error handling, but for an agent to decide whether to invoke, it is sufficiently 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 80%, so the schema already documents most parameters. The description adds that the task is a 'declared test, lint, or build script' and that it runs in a microVM, which reinforces the task and repository semantics. However, it does not clarify ref, timeoutSeconds, or packageManager beyond the schema. 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 specific verbs and resources: 'Clone a public GitHub repository into a disposable Firecracker microVM, install dependencies, run one declared test, lint, or build script, and return structured logs plus the resolved commit.' It clearly defines the action and output, and distinguishes from sibling tools focused on tokens, wallets, and reports. The clarification 'verifies execution, not semantic correctness' further sharpens the purpose.

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

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

The description explicitly states exclusions: 'private repositories and arbitrary shell commands are not accepted,' and implies the scope of use (public repo verification). It does not name alternative tools, but the sibling set makes the uniqueness obvious. It also mentions the cost and payment endpoint, which guides whether to use it.

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