LION — Verified Company & Compliance Data

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

No annotations are provided, so the description carries the full burden. It only mentions the paid nature and HTTP GET endpoint, but does not disclose behavioral traits such as return format, error behavior, or whether it is safe to call repeatedly.

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 very concise, consisting of a single sentence that includes a practical pricing note. However, it could be more structured by separating purpose from cost details.

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 complexity (multi-source data) and lack of output schema, the description is critically incomplete. It does not describe return values, parameter interactions, or any example usage, making it nearly impossible for an agent to invoke correctly.

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

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

Schema coverage is only 25% (only 'mode' has a description), and the description adds no extra meaning for the four parameters. It does not explain what 'q', 'domain', or 'method' represent, leaving the agent to guess.

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 it provides 'multi-source on-chain + market intelligence' but lacks a specific verb and does not differentiate from specialized sibling tools like lion_token_risk_indicators or lion_deep_research, making the purpose somewhat vague.

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 given on when to use this tool over alternatives, nor are there any prerequisites or conditions for use. With over 20 sibling tools, this omission leads to ambiguity.

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

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

With no annotations provided, the description carries full burden and discloses key behaviors: the tool costs $0.03 Base USDC, is a one-call research pack, and accepts a query parameter. It also mentions the x402 paid endpoint and gives an example query. No mention of destructive actions or rate limits, but the cost and input format are clear.

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 contains useful information but is somewhat cluttered, mixing purpose, pricing, use cases, and technical API details in a single paragraph. It could be more structured (e.g., separate sections for purpose, usage, and pricing). However, it is not excessively long.

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 has only 2 parameters, no output schema, and no nested objects, the description is fairly complete: it explains what the tool does, when to use it, the cost, and provides an example query. It does not detail return format, but that is acceptable given no output schema.

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

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

The input schema has 50% description coverage (only 'q' described as 'Company or domain'). The description adds value by giving an example '?q=coinbase.com' for 'q,' but the optional 'domain' parameter is left unexplained, leaving ambiguity. The schema itself is minimal, so the description partially compensates but not 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 provides a 'one-call research pack (web + firmographics + domain)' for company intel, vendor research, or KYB. It uses a specific verb-resource combination ('company dossier') and distinguishes from siblings by emphasizing it's a 'one-call' pack with a lower price point, while mentioning an upsell for more comprehensive 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 description specifies use cases: 'company intel pack, vendor research, KYB taster.' It implicitly guides against using this when full verification is needed by mentioning 'Full verified company file upsell $0.95,' suggesting an alternative. However, it does not explicitly state when not to use this tool or list sibling tools 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?

With no annotations, the description carries the burden but only covers cost ($0.04), payment method (x402 paid), and endpoint. It does not mention read-only nature, side effects, or error handling, leaving gaps in behavioral understanding.

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 concise and front-loaded with the tool's purpose. It includes necessary details like price and alternatives, though the inclusion of technical endpoint details could be streamlined for clarity.

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

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

Given the absence of an output schema and annotations, the description provides a solid overview: functionality, returned data, pricing, and differentiation from siblings. It omits details about return structure or error cases but suffices for agent selection.

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 75% and the description adds minimal extra meaning beyond the schema. It demonstrates usage with an example ('identifier=stripe.com') but does not elaborate on 'fields' or 'format' parameters beyond their schema descriptions.

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 performs company enrichment by domain or name, specifies the returned firmographics pack, and explicitly differentiates from siblings by noting it's an alternative to CompanyEnrich/org-enrich with keyless+attestation features.

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 a clear use case ('when you want keyless + attestation') and names alternatives, showing when to choose this tool. However, it lacks explicit when-not-to-use scenarios or 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?

No annotations are provided, so the description must disclose behavioral traits. It mentions payment requirement (x402, $0.03) and Ed25519 attestation, indicating a paid, authenticated call. However, it does not describe data freshness, rate limits, or whether the tool mutates state. The cost and security info are useful but incomplete.

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 long but contains marketing fluff (pricing comparison, Ed25519, x402). The first sentence could be more concise. While it front-loads the purpose, the extra details reduce clarity and can be trimmed without loss.

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 under-specifies return value structure. It mentions 'web + firmographics + domain trust' but not the format (e.g., JSON keys). Given many sibling tools, more detail on what the agent receives is necessary for proper integration.

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 both parameters. The description adds no new meaning beyond the schema for parameters; it only restates the required parameter as 'Company name or domain'. No elaboration on optional domain override.

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 provides company research combining web, firmographics, and domain trust data. However, it does not distinguish this tool from siblings like lion_company_enrich or lion_domain_enrich, relying on marketing language about pricing rather than functional 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?

No explicit guidance on when to use this tool versus alternatives. The description mentions 'keyless call' but does not specify scenarios, prerequisites, or when not to use it. Sibling tools like lion_company_dossier are not referenced.

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

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

With no annotations provided, the description carries full disclosure burden. It reveals the paid nature ($0.05), the multi-check composition, the PASS/WARN/BLOCK output, the optional signed receipt, and the keyless payment method. It does not mention rate limits or auth requirements beyond keyless.

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 dense sentence covering key features, payment details, and differentiation. It is reasonably concise but could be better structured (e.g., separating payment info or listing checks). No wasted words, but density may reduce clarity.

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

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

Given no output schema, the description should explain return values more fully. It mentions PASS/WARN/BLOCK and a receipt option, but lacks detail on the output structure or fields, which an agent would need for integrating the results.

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

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

Schema coverage is 100%, so the baseline is 3. The description mentions address, name, token, domain, and receipt as optional contexts but does not add meaningful constraints or formatting guidance beyond what the schema already provides.

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

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

The description clearly states the tool as a 'Counterparty compliance pack' that combines OFAC SDN screening, entity sanctions, domain trust, token risk, firmographics, and a signed receipt, outputting PASS/WARN/BLOCK. It explicitly distinguishes from 'one-shot OFAC tools' and mentions key differences from sibling tools like sanctions-only screens.

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 indicates this is for 'AML KYC due diligence for agents' and highlights the bundled attestation advantage over simpler tools. However, it does not explicitly state when not to use it or list specific alternative tools for different use cases.

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

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

No annotations are provided, so the description must fully disclose behavior. It mentions 'keyless' and 'Ed25519-attested' but does not describe side effects, authentication requirements, or rate limits. The behavioral traits are insufficiently explained.

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, but it includes unnecessary jargon and pricing info. It is concise but not well-structured for agent understanding.

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 no output schema, incomplete parameter info, and a large set of sibling tools, the description is far from sufficient. An agent would struggle to determine when to use this 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 0%, and the description does not explain what 'chain' and 'identifier' mean. Without any parameter documentation, the agent cannot correctly fill in these fields.

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 hints at combining keyless RPC and Ed25519-attested enrichment, but it is cryptic and does not clearly state what the tool does. It mentions pricing and endpoint, but the core functionality is vague.

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

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

No guidance on when to use this tool versus siblings. No alternatives or exclusions are mentioned. The description lacks any context for 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?

The description discloses Ed25519 attestation and a paid x402 model with price, which adds behavioral context beyond the basic purpose. However, it does not mention rate limits or authentication details beyond payment.

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 very concise: two sentences cover purpose, sources, attestation, and pricing. No unnecessary words.

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 is fairly complete given no output schema and no annotations. It explains data scope, sources, and payment model. Could add response format or authentication but not required.

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% with clear parameter descriptions. The description reiterates the search modes but does not add significant new constraints or formatting details.

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 it provides CPG product data and shop prices, searchable by barcode or name, sourced from Open Food Facts and Open Prices. This distinguishes it from sibling tools focused on companies, domains, or enrichment.

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 for CPG product intel with prices, but does not explicitly state when not to use or list alternatives. Given sibling tools are unrelated, 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?

With no annotations provided, the description carries full burden. It states the tool is FREE and returns a recommendation, but does not disclose whether it is read-only, any side effects, or consent requirements. The mention of a default path and upsell suggests commercial intent but not full behavioral traits.

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

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

The description is two sentences, front-loading the core purpose and then adding default details. Every sentence adds value with no wasted words. However, the structure could be slightly improved by separating the core function from the pricing example.

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 and the tool returns a recommended path and sample, the description lacks details on the output format, what the sample contains, and how the recommendation is structured. For a tool with a single parameter and no nested objects, this is incomplete.

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% with a single parameter 'need' described as 'What you need in plain language'. The description repeats this with 'Tell LION what you need', adding no new meaning. Baseline 3 is appropriate as the schema already documents the parameter adequately.

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

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

The description clearly states the tool's function: tell LION what you need, and it returns a recommended paid path and a sample. The verb 'tell' and resource 'need' are specific. However, it does not explicitly distinguish itself from the many sibling tools, though it implies a different role as a recommender/front-end.

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 provides no guidance on when to use this tool versus the 28 sibling tools. It mentions 'FREE' and upsells, but does not say when not to use it or what alternatives exist for different needs. This is a significant gap for an AI agent deciding between 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?

No annotations exist; description discloses pricing, authentication (Ed25519-attested), and that it accesses web data, but does not explicitly state if mutation occurs or other behavioral traits like rate limits.

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?

Contains multiple pieces of information in a dense paragraph; includes upsell and pricing details that could be considered secondary. Could be more 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?

Given one parameter and no output schema, the description lacks details on the return format or what 'deep research' yields, leaving some ambiguity.

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 already fully describes parameter 'q' with example. Description adds minor reiteration but no new semantics.

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

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

Clearly states it performs company research combining web, scrape, firmographics, and domain trust data. Distinguishes from siblings through mention of multiple data sources in one call and specific pricing.

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 usage direction ('Use before/after people enrichment') but does not compare with alternatives or state when not to use.

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

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

With no annotations, the description must fully disclose behavior. It reveals the tool is 'keyless' and uses Base USDC for micropayments, and that it provides live data. However, it does not mention rate limits, failure modes, or whether the operation is read-only (likely safe). The description adds some value beyond the schema but is incomplete.

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 concise, fitting key information (purpose, data types, payment model, example) into a few lines. However, the structure is somewhat disjointed, mixing technical details with pricing. Still, it is efficient and front-loaded.

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 no output schema and one parameter, the description covers the main aspects: what data is returned (DNS records, trust score), usage context (paid, keyless), and an example. It does not describe the return format or any additional behaviors, but it is adequate for a 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?

The description provides an example usage '?domain=stripe.com' but adds no new semantics beyond the schema's description 'Domain e.g. stripe.com'. Since schema coverage is 100%, the baseline of 3 is appropriate. No additional parameter meaning is conveyed.

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 enriches domains with live DNS records (MX, SPF, DMARC, A) and an HTTPS trust score, using specific verbs and resources. This differentiates it from sibling tools like lion_domain_intel by specifying the exact data points provided.

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 pricing and the x402 payment mechanism, indicating it's a paid tool, but does not explicitly state when to use it vs alternatives like lion_domain_intel. No when-not guidance is provided. While the context of cost is useful, guidelines for tool selection are lacking.

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

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

No annotations are provided, so the description carries full burden for behavioral transparency. It mentions DNS queries and HTTPS probe but does not disclose whether the operation is read-only (likely), has side effects, or requires special authorization. The pricing note (keyless, $0.005) hints at cost but lacks detail on rate limits or idempotency.

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 brief (two sentences) and front-loaded with the core purpose. The second sentence about pricing may be marginally useful but is short. Overall, no wasted words.

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 parameter and no output schema, the description provides adequate context for use but lacks detail on return format, pagination, or failure modes. It covers the input and high-level behavior but leaves some uncertainty about data structure.

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 input schema has a single 'domain' parameter with 0% coverage. The description adds significant meaning by explaining the domain will be used for DNS and HTTPS checks, going beyond the bare schema. However, it doesn't specify format (e.g., FQDN with or without scheme).

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 it provides 'Live domain trust signals' by checking specific DNS records (MX, SPF, DMARC, A) and performing an HTTPS probe via Cloudflare DoH. This is a specific verb+resource combination, distinguishing it from general domain enrichment tools like lion_domain_enrich.

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 assessing domain trust signals but does not explicitly state when to use it over alternatives (e.g., lion_domain_enrich). No exclusions or when-not-to-use guidance 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?

The description discloses that the tool is paid ($0.005 on Base) and uses x402 payment, which is a key behavioral trait. However, without annotations, it does not address failure modes, rate limits, or whether it makes external API calls, leaving significant gaps.

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

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

The description is a single sentence that conveys the main purpose and pricing information concisely. The bracketed technical detail (x402 paid, price) is relevant but could be streamlined for readability.

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 complexity of a 'bundle' tool with no output schema, the description lacks details on what the enrichment includes, the structure of the response, or any constraints on the identifier input. The large sibling set underscores the need for more contextual completeness.

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

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

Schema coverage is 100% with adequate parameter descriptions. The description adds context by linking 'tx context' to the tx parameter and specifying 'Base' chain, but does not substantially enhance meaning 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 clearly identifies the tool as a LION Research Bundle combining enrichment with transaction context, differentiating it from other enrichment tools by specifying a price and the inclusion of 'tx context'. The purpose is stated upfront with a specific verb-resource combination.

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 explicit guidance on when to use this tool versus siblings like lion_company_enrich or lion_enrich_v1. The description does not specify prerequisites, exclude certain use cases, or recommend 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?

With no annotations, the description carries the full burden. It discloses pricing, keyless access, output format, and an upsell path. However, it does not detail side effects, rate limits, or idempotency. The upsell mention hints at behavioral context (potential redirect to paid file).

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 concise and front-loaded with the main purpose. It packs pricing, sources, aliases, and keyless feature into a few sentences. The upsell info adds some noise but remains 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?

Given 3 parameters and no output schema or annotations, the description covers the core functionality and data sources. However, it lacks explanation of the expected input for 'identifier' and the structure of the enrichment output beyond format.

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 description adds meaning to the 'format' parameter by suggesting 'apollo_org' and lists example fields (name, employees, etc.) that likely relate to the 'fields' parameter. However, it does not explain the 'identifier' parameter or provide comprehensive guidance on field syntax.

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 enriches company/organization data with fields like name, employees, country, industry, and website from Wikidata+SEC. It provides aliases and hints at the output format. However, it does not explicitly differentiate from similar sibling tools like lion_company_enrich or lion_org_enrich.

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 'keyless' and 'format=apollo_org' but does not provide explicit guidance on when to use this tool versus alternatives, nor does it specify 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?

Discloses key behavioral traits: fail-safe if lists unavailable, cost ($0.01), keyless authentication, Ed25519 attestation, and the HTTP method. Since annotations are absent, this provides necessary transparency beyond the basic purpose.

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?

Highly concise and front-loaded: two sentences plus a bracketed technical note. Every sentence adds value (purpose, behavior, cost, authentication). No wasted words.

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?

Despite good purpose clarity, the description lacks completeness for a tool with 3 parameters, no output schema, and no annotations. It does not explain the return format beyond 'PASS/BLOCK', the usage of optional parameters, rate limits, or prerequisites.

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

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

Schema description coverage is only 33% (only 'name' has a description). The description does not clarify the roles of 'entity' and 'company' parameters, nor does it explain if they are alternatives to 'name'. Minimal added meaning 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?

Clearly states it screens an entity name against multi-list sanctions (OFAC/EU/UN) and returns PASS/BLOCK. The verb 'Screen' and resource 'entity name' are specific. However, it does not explicitly differentiate itself from sibling tools like lion_sanctions_screen, though the name implies an entity focus.

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 explicit guidance on when to use this tool versus alternatives (e.g., lion_sanctions_screen, lion_multi_sanctions_bundle). The description implies it's for entity sanctions screening but does not provide conditions 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?

With no annotations, the description must fully disclose behavior. It indicates read-only actions ('reads') and payment requirement ('x402 paid'), which are key traits. However, it does not mention error handling, response format, or any limitations beyond pricing. Basic transparency is achieved but lacks depth.

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

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

Description is a single sentence with key information upfront ('Keyless multi-chain JSON-RPC reads'). It includes pricing and payment details efficiently, though the formatting with brackets and pricing could be clearer. No wasted words.

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 parameters, no output schema), the description covers the core functionality, supported chains, and payment model. It does not explain return values, but lack of output schema reduces that need. Minor gaps in error behavior and limitations, but overall sufficient for a 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 coverage is 100% with all three parameters described. The description adds pricing context and hints at the 'chain' parameter via '?chain=ethereum', but does not provide additional semantics beyond the schema. 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?

Description clearly states it performs 'Keyless multi-chain JSON-RPC reads' on 'Base + Ethereum', distinguishing it from sibling tools which focus on enrichment, research, and company data. The verb 'reads' and resource 'JSON-RPC' are specific.

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

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

No guidance on when to use this tool versus alternatives. The description mentions pricing and payment method but does not explain preferred scenarios, prerequisites, or when to avoid using it. Sibling tools are all different functions, so no direct comparison 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?

Discloses key traits: no API key required, cost ($0.005 Base USDC x402), and Ed25519 attestation. However, with no annotations, it could better explain behaviors like rate limits, error responses, or response structure.

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 and front-loaded with purpose, though somewhat fragmented into short phrases. Every piece of information adds value with minimal fluff.

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?

Despite no output schema and optional parameters, the description covers data source, cost, authentication, and sample output fields. Missing details like pagination or error handling, but sufficient for a straightforward lookup 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% with descriptions for all three parameters. The description adds mention of output fields (LEI, jurisdiction, etc.) but does not significantly enhance parameter meaning 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 clearly states it performs LEI lookup by LEI code, legal name, or domain, listing returned fields. While it distinguishes itself from siblings by its specific LEI focus, it does not explicitly differentiate from similar company lookup tools in the sibling list.

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 context for usage such as 'Keyless Global LEI Index Golden Copy' and lists related search terms, but does not specify when not to use or suggest alternatives among the 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?

With no annotations, the description carries full burden. It mentions the paid nature and HTTP method, but lacks details on rate limits, error handling, or definition of 'solar PV potential'. Minimal behavioral 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?

Single sentence plus cost info. No redundancy, information is front-loaded. Highly concise.

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 3 optional params and no output schema, the description covers input and cost but omits return structure, error cases, and limits. Adequate but not fully 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 parameters (lat, lon, address) have 0% description coverage. The description adds meaning by clarifying that address OR lat+lon pair should be used, which is not in the schema. Valuable addition.

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 it provides 'Location + solar PV potential' and specifies the query methods (address or lat/lon). This differentiates it from sibling tools like lion_domain_enrich or lion_company_enrich.

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 via address or coordinates and notes it's paid, but does not explicitly state when to use this tool over alternatives or provide exclusions (e.g., when to use lion_domain_enrich instead).

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

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

With no annotations provided, the description carries the full burden. It reveals that the tool requires x402 payment ($0.02 on Base), returns a LION_SIGNED_COMPLIANCE_RECEIPT_V1 portable proof, and produces PASS/WARN/BLOCK outputs. This provides useful behavioral context beyond basic functionality.

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 moderately concise but includes some redundant phrases like '$0.02 Base USDC keyless x402' and 'Matches: ...'. It is front-loaded with the core purpose, but could be tighter by removing extraneous details.

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 lack of an output schema, the description partially compensates by mentioning the compliance receipt and classification (PASS/WARN/BLOCK). However, it does not explain the structure or fields of the receipt, leaving some gap in expected output understanding.

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 has 100% description coverage for the three optional parameters (name, domain, address). The description adds context like 'multi-list screen' for name and 'OFAC SDN address screen' for address, but does not significantly enhance understanding beyond what the schema already provides.

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

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

The description clearly states the tool is a multi-list sanctions compliance bundle including OFAC SDN, entity name sanctions, domain trust, and a compliance receipt. It mentions PASS/WARN/BLOCK outcomes and AML KYC due diligence. However, it does not explicitly differentiate from similar sibling tools like lion_sanctions_screen or lion_entity_sanctions_screen, 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 does not provide guidance on when to use this tool versus alternatives such as individual sanctions screens. The phrase 'Matches: multi-list sanctions, compliance receipt, OFAC EU UN screen' is cryptic and does not clearly state selection criteria 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?

No annotations provided; description carries full burden. Mentions cost and identifier requirement but does not disclose side effects, rate limits, or whether it is read-only. The '[x402 paid]' hint indicates it is a paid API call, but behavioral traits are unclear.

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?

Description is short but fragmented with inconsistent punctuation and jargon. It conveys key points (cost, format, identifier) but lacks clear structure.

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?

Tool has 3 params, no output schema, and many siblings (29). Description does not explain return format, error handling, or how it differs from similar enrich tools. Incomplete for effective 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?

Schema has 3 parameters with 0% description coverage. Description adds meaning for 'format' (apollo_org) and 'identifier' (domain or name), but 'fields' is not explained. Partial improvement over bare 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?

Description indicates it enriches organization data ('Org enrich') with firmographics, but is cryptic with jargon like 'Apollo-shaped optional' and 'drop-in'. It does not clearly differentiate from sibling tools like lion_company_enrich or lion_company_dossier.

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

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

No guidance on when to use this tool versus alternatives. No exclusions, prerequisites, or context for usage. Implied usage from description is minimal.

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

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

No annotations; description only states it is a keyless OSM search and includes payment info. Does not disclose result format, rate limits, authentication needs, or other behavioral traits.

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?

Single sentence is very concise, no unnecessary words. Payment info is relevant. Could be slightly more informative without harming conciseness.

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 3 parameters and no output schema, the description is too brief. Does not specify what the tool returns or any additional context needed for use.

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

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

Schema description coverage is 0%. Description does not explain the three parameters (q, lat, lon). The agent must infer meaning from parameter names only, which is inadequate.

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 clearly states 'Point of interest / business search (keyless, OSM)', which is a specific verb (search) and resource (POI/business). It distinguishes from sibling tools like lion_company_dossier or lion_web_search by focusing on POI data via OpenStreetMap.

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

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

No guidance on when to use this tool vs. alternatives. Does not mention when not to use it or provide comparative context with 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?

No annotations provided. Description only mentions it's free, implying non-destructive, but lacks details on rate limits, data freshness, or what the teaser actually contains, leaving behavioral traits unclear.

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 short and to-the-point, no wasted words. However, it lacks structure and key information that could be added without much bloat.

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 no output schema and an undocumented parameter, the description fails to convey what the tool returns or how to properly call it. Incomplete for effective agent usage.

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

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

The single parameter 'entity' has no description in the schema (0% coverage) and the tool description does not explain what it expects (e.g., company name, domain). Agent has no guidance on how to provide input.

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 clearly states it is a 'FREE teaser for a company/domain', indicating a lightweight preview. It distinguishes from paid deeper research tools, though the exact scope of 'teaser' is vague.

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?

Implicitly suggests using it for quick free looks and mentions upgrades for deeper research. However, does not explicitly state when to use this tool vs alternatives or conditions for not using it.

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

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

No annotations are provided, so the description carries full burden. It discloses the tool is paid ($0.005), Ed25519-attested, and returns fuller fields with multi-list metadata. However, it does not describe the return format, success/failure indicators, or any rate limits. The read-only nature is implied but not explicit.

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-loading the core purpose. It includes essential details like price and attestation without excess. Could be slightly tighter (e.g., the x402 note is technical), 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?

Given the tool's simplicity (single param, no output schema), the description covers the main purpose. However, it lacks explanation of what 'fuller fields' and 'multi-list metadata' entail, and how the Ed25519 attestation is used. These gaps could hinder an agent from properly interpreting results.

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% (one parameter described). The description's parameter context ('EVM address to OFAC SDN / sanctions screen') is very similar to the schema description, adding no new meaning. 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 clearly states the tool screens an address against the OFAC SDN list. It specifies the verb ('screen'), resource (address), and distinguishes it from the cheaper wallet-screen by noting fuller fields and multi-list metadata. The mentions of 'Matches: OFAC SDN, AML address screen' further clarify 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 contrasts this tool with wallet-screen, suggesting use when more detail is needed. However, it does not address other siblings like lion_entity_sanctions_screen or lion_multi_sanctions_bundle, leaving the agent without guidance on when to choose this tool over those 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?

No annotations are provided, so the description carries the full burden. It discloses the cost ($0.02 Base USDC) and payment method (x402), which is a behavioral trait. However, it does not mention rate limits, timeouts, content size limits, or authentication requirements (keyless suggests none). The output format is described, adding value beyond the schema.

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

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

The description is extremely concise with two short sentences that immediately convey the tool's purpose, input, output, and cost. No unnecessary words; 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?

For a single-parameter tool with no output schema, the description provides essential context: input format, output fields, and cost. It lacks information about any limitations (e.g., max page size, timeout) but is otherwise sufficient for an agent to decide whether to use 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 coverage is 100% with the parameter 'url' described as 'Absolute http(s) URL'. The description adds no further meaning about the parameter itself; it only provides context about pricing and output. Baseline 3 is appropriate since the schema already documents the parameter adequately.

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

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

The description clearly states the tool performs a web scrape ('Keyless attested web scrape'), specifies the input as a URL parameter, and explicitly lists the output fields (title, markdown, word_count). This distinguishes it from sibling tools like lion_web_search which is for search, not scraping.

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 for web scraping but does not provide explicit guidance on when to use this tool versus alternatives, nor does it list prerequisites or when not to use it. Sibling tools include several enrichment and intelligence tools, but none are direct scraping alternatives, so the lack of explicit differentiation is minor.

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

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

With no annotations, the description must disclose behavioral traits. It notes 'keyless' (no authentication required) and 'attested' (data integrity), and includes pricing. However, it does not state whether the tool is read-only, rate limits, data freshness, or error behavior. This is insufficient for a tool with 0% schema coverage and no output schema.

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

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

The description is a single sentence with additional bracketed technical details (pricing, API path). It front-loads the core purpose but buries important info in parentheses. Could be restructured for clarity, but is relatively concise.

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 no annotations, no output schema, and undocumented parameters, the description is incomplete. It tells what the tool does but not how to invoke it (parameter guidance), what to expect as output, or usage constraints. The complexity is low, but the description does not fill the gaps.

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

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

The input schema has two parameters (cik, ticker) with no descriptions (0% schema_description_coverage). The tool description does not explain what these parameters mean or how to use them (e.g., one or both required, format). Description fails to add any semantic value 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 'SEC EDGAR financials for public companies', clearly indicating the tool retrieves financial data from SEC filings for public companies. It differentiates from siblings like lion_company_dossier (broader profile) and lion_company_enrich (enrichment) by focusing specifically on financials. However, it could be more precise about the type of financial data (e.g., income statements, balance sheets).

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 provides minimal usage guidance. It mentions 'keyless, attested' and pricing ($0.005), hinting at cost-based usage, but does not specify when to use this tool over siblings like lion_company_dossier or lion_adaptive_query. No explicit context for 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?

No annotations are provided, so the description carries full burden. It reveals that the tool is 'keyless' and 'paid' with a price, but fails to describe what the tool actually returns (e.g., sentiment, trending topics, or raw posts) or any side effects. The term 'attention/trend' is vague.

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, which is concise, but it compresses too much info (sources, pricing, endpoint) into a run-on style. It could be better structured to front-load the core purpose.

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 lack of output schema and parameter descriptions, the description should provide more context about the tool's functionality and return values. It falls short, especially for a paid tool where agents need clear expectations.

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

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

Schema description coverage is 0% for three optional parameters (q, topic, entity). The description provides no hints about their meaning or expected values, leaving the agent without any guidance on how to populate them.

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 identifies the tool as providing social signal intel from HN and Reddit, but lacks an explicit verb (e.g., 'Retrieve' or 'Get'). The purpose is clear enough to distinguish from siblings like lion_web_search, but the phrasing is more of a label than a concise statement.

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

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

No guidance on when to use this tool versus alternatives. The description does not mention scenarios, prerequisites, or comparisons to sibling tools, leaving the agent to guess about appropriate usage.

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

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

No annotations provided, so description carries full burden. It reveals the paid x402 model and endpoint URL, which is useful. However, it lacks information about whether the tool is read-only, return format, or any side effects.

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 concise sentences with no wasted words. Includes essential payment and endpoint context. Could be slightly improved with clearer separation of purpose and pricing.

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, yet description does not explain what the tool returns (e.g., risk score, indicators, format). The tool's purpose is clear, but the missing return value information significantly reduces completeness.

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

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

Schema description coverage is 100% with clear descriptions for both parameters ('base|ethereum|solana' and 'Token contract or mint'). The description adds no further meaning beyond specifying that it accepts tokens on those chains.

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 clearly states 'Pre-trade token risk indicators' with explicit mention of supported chains (Base/Eth/Solana), making the tool's purpose and resource immediately clear. The function is distinct from siblings like lion_wallet_screen or lion_keyless_base_rpc.

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 pre-trade risk checks but does not specify when to prefer this tool over alternatives, nor does it mention any prerequisites 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?

No annotations provided, so description carries full burden. It discloses the core function and pricing, but does not explain error handling, response format, or authorization requirements. Adequate but not thorough.

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?

Description is short and front-loaded with the key purpose. The pricing and API path details are extra but not excessive. Every part serves a purpose, though slightly cluttered.

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, the description is fairly complete. However, lacks detail on return structure and potential error states. No output schema exists to compensate, so more detail would be helpful.

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 covers 100% of parameters with adequate description. The description adds minor context (Base chain, format hint) but does not provide significant additional meaning 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?

Description clearly states it provides a Base transaction receipt and decoded calldata, which is a specific and unambiguous purpose. It distinguishes itself from sibling tools like lion_keyless_base_rpc which likely provides raw RPC responses.

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

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

No guidance on when to use this tool versus alternatives. Does not mention when not to use it, such as for non-Base chains or when only raw data is needed. It only gives technical details.

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

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

No annotations are present, so the description carries the full burden. It mentions 'keyless' (no API key) and 'paid' with a price, but fails to disclose behavior on invalid VAT, rate limits, latency, or error handling.

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 with a brief technical note, making it concise. However, the price note may be extraneous for an AI agent.

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 3 parameters with low schema coverage, no output schema, and no annotations, the description is incomplete. It does not explain the validation result (e.g., boolean or detailed data) or clarify usage of optional parameters (e.g., whether only 'vat' is needed or a combination).

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 description adds context for the 'vat' parameter (format example) and indicates EU VAT validation via VIES, but provides no additional meaning for 'number' or 'country' parameters. Schema coverage is low (33%), and the description partially compensates for 'vat' but not the others.

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 validates EU VAT/tax IDs via VIES, with a specific example of a VAT number. However, it does not explicitly differentiate from sibling tools like 'lion_company_dossier' or 'lion_compliance_bundle' which might have overlapping functionality.

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, nor any prerequisites or conditions. The description lacks context such as 'use this to verify VAT numbers before invoicing' or similar.

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?

Despite no annotations, the description discloses key behaviors: cost ($0.95), payment via USDC x402, Ed25519 attestation, graceful degradation per-section. This provides substantial transparency for 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?

The description is adequately concise but dense with jargon (e.g., 'Ed25519-attested', 'degrade per-section'). The value proposition is front-loaded, but the structure could be cleaner.

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 outlines output components (firmographics, SEC, domain trust) but lacks details on output format or how attestation is represented. Given no output schema, more completeness would be beneficial.

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% with a clear description of the 'domain' parameter. The tool description adds no additional semantics beyond the schema baseline.

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 explicitly states the tool provides verified company data including firmographics, SEC, and domain trust with attestation. It mentions matches to related terms but does not clearly differentiate from sibling tools like lion_company_enrich or lion_company_dossier.

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 explicit guidance on when to use this tool versus alternatives. The description lacks context on prerequisites, paywalls, or when using other tools might be more appropriate.

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

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

With no annotations, the description must cover behavioral traits. It mentions pricing and that it returns PASS/WARN/BLOCK, but omits details like rate limits, authentication (beyond 'keyless'), error handling, or side effects. The word 'pre-pay gate' hints at payment required but is vague.

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 somewhat verbose with marketing language and pricing upsells, but the main purpose is front-loaded. It could be more concise without losing essential 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?

The tool has only one parameter and no output schema, so the description should explain the return value beyond just PASS/WARN/BLOCK. It lacks details on response format, and the inclusion of pricing and upsells adds noise without improving comprehensiveness.

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 covers 100% of parameters with description for address. The tool description adds little beyond the schema; it mentions 'wallet address' and 'EVM 0x…' which are already in the schema. Baseline of 3 applies due to high 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 it screens wallet addresses against OFAC SDN lists, using the verb 'screen' and specifying 'wallet-screen'. It distinguishes from siblings by emphasizing cost and specific use case for wallet screening.

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 using this tool for wallet screening before settling counterparties (x402), but does not explicitly compare with sibling tools like lion_sanctions_screen or lion_entity_sanctions_screen, nor does it state 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?

The description discloses that it is a paid GET endpoint with a specific price and route, but with no annotations, it fails to reveal behavioral traits such as read/write nature, data returned, or side effects. The information is minimal and insufficient for an agent to understand 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 very concise (one sentence) but lacks structure. It front-loads the purpose poorly and includes technical details in brackets. While not verbose, it could be better organized for clarity.

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

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

Given the optional parameters, no output schema, no annotations, and many sibling enrichment tools, the description is grossly incomplete. It does not explain what the 'bundle' contains, how to construct input, or what the response looks like, leaving significant gaps.

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

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

The input schema has two optional parameters (domain, identifier) with 0% description coverage, and the description does not mention them at all. No meaning is added beyond the schema, leaving the agent unsure of what to provide.

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 'Keyless off-chain company enrichment vectors,' indicating it provides company enrichment data, but it is vague about what the tool specifically returns and how it differs from sibling tools like lion_company_enrich or lion_domain_enrich. The mention of 'x402 paid' and a price suggests a paid endpoint, but the core purpose is unclear.

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. There is no mention of scenarios, prerequisites, or exclusions. The description lacks any context for appropriate usage.

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 discloses that results are Ed25519-attested and that the tool uses x402 payment at $0.025, which provides useful behavioral context. However, it does not mention return format, rate limits, or failure modes, and there are no annotations to supplement this.

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 concise and front-loaded with the core purpose. However, it includes extraneous pricing details that could be moved to annotations, making it slightly less streamlined. Still, it is efficient with no wasted words.

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 simple tool (1 parameter, no output schema, no annotations), the description covers purpose, cost, and attestation. However, it lacks details on return format and usage constraints, leaving some gaps for an agent to fully understand the tool.

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

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

The schema already covers the single parameter 'q' with a clear description 'Search query'. The description adds little extra meaning beyond the schema, such as 'for agent grounding', but does not enhance parameter understanding. With 100% schema coverage, 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 clearly states it is a 'Keyless attested web search' for 'agent grounding', with a query parameter (?q=). This verb-resource combination is specific and distinguishes it from sibling tools that focus on companies, domains, or other entities.

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 web search with attested results and mentions agent grounding, but does not explicitly state when to use this tool over alternatives like lion_deep_research or lion_scrape. No exclusion criteria or alternative recommendations are given.

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

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

No annotations are provided, so the description must disclose behavior. It mentions 'keyless' (suggesting no auth) and 'CC0' (license), and a paid endpoint, but does not state whether the tool is read-only, modifies data, or requires certain inputs. Behavioral traits are missing.

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 only one sentence, which is concise, but it is poorly structured: it includes pricing syntax in brackets without explanation. It does not front-load the core purpose.

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 no output schema, no annotations, and 3 undocumented parameters, the description is severely incomplete. It fails to provide enough information for an agent to correctly select and invoke the 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 0% and the description does not explain the three parameters (q, qid, entity). No details on what each parameter does or how they relate to Wikidata firmographics are given.

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 only states 'Wikidata firmographics' which is a noun phrase and essentially repeats the tool name. It lacks a verb indicating the action performed, such as 'retrieve' or 'query'. The mention of 'keyless, CC0' and pricing adds context but does not clarify the 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?

There is no guidance on when to use this tool versus sibling tools like lion_company_enrich or lion_org_enrich. No prerequisites, context, or alternatives are provided.

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