memeoracle

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

With no annotations, the description must disclose behavioral traits. It states the output is tokens with volume and momentum scores, implying a read-only operation, but does not mention caching, rate limits, or any side effects. The behavior is partially transparent 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?

The description is two sentences, front-loaded with purpose and examples. Every word contributes value, no redundancy or filler.

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

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

Given only two parameters and no output schema, the description adequately explains the tool's output concept (top tokens by volume with momentum) and intended use (chain scouting). It is nearly complete for a simple tool, though it could mention if authentication or prerequisites are needed.

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 (chain and limit) with defaults and ranges. The description adds minimal extra meaning ('solana, ethereum, base, bsc, etc.') but does not significantly enhance understanding 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 returns 'top tokens by volume with momentum scores' for a specific chain, using the verb 'scouting' and listing supported chains. It distinguishes from siblings like 'token_scan' and 'trending_memes' by focusing on broad chain-level trending tokens.

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 Solana, Base, Ethereum, and BSC scouting but does not explicitly state when to use it versus alternatives like 'token_scan' or 'new_launches'. No direct when-to-use or when-not-to-use guidance is provided.

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

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

No annotations provided, so description carries full burden. It lists returned info but doesn't explicitly state it's read-only or disclose any behavioral traits like caching or 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?

Single sentence, front-loaded with key info, concise and to the point. 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 no parameters and no output schema, description covers all likely outputs: server health, API connectivity, chains, tools, pricing. Complete for 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?

No parameters; baseline is 4 per rules. Description does not need to add param info since there are none.

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 returns server health, API connectivity (named specific APIs), supported chains, tool list, and pricing. It distinguishes from siblings which are analysis tools.

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

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

No explicit when/when-not/alternatives provided, but the name and description imply it's for checking system status. Missing explicit guidance.

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

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

No annotations are provided, so the description carries the full burden. It discloses premium payment, free trial units, scoring scale, and rating system. It does not detail data update frequency or rate limits, but is transparent enough for a read-only scoring 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 a single paragraph containing all essential information: premium label, what the tool does, score range, rating, calling instructions, and free units. It is front-loaded but slightly dense; minor splitting could improve 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?

No output schema exists, so the description properly explains the return values (score 0-100, ratings). It covers the premium access requirement and free units. For a 3-param tool with no complex behavior, the description is sufficiently complete.

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

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

The input schema has 100% coverage with descriptions for chain, query, and address. The description adds no extra meaning beyond what the schema already provides (e.g., no additional syntax or constraints). 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 the tool computes composite momentum scoring from volume surges, price acceleration, buy pressure, and boost activity, outputting a score 0-100 with ratings COLD/WARMING/HOT/EXPLOSIVE. This distinguishes it from siblings like rug_check or whale_watch.

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 explains the premium requirement and that it's for momentum scoring, but does not explicitly list when to use versus alternatives. However, the context is clear given sibling tool names are all distinct.

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, and description does not disclose behavioral traits beyond the obvious 'discover' operation. Missing details on authentication, rate limits, or whether the tool is read-only.

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

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

Two sentences, no wasted words. Front-loaded with purpose and value proposition. Efficiently communicates core functionality.

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 is simple with two optional parameters. Description gives enough to understand purpose but lacks details on output format, ordering, or how 'freshest' is determined (e.g., time-based). Without output schema, more explanation would improve 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?

Input schema covers 100% of parameters with descriptions. The description adds context about 'first minutes/hours' but does not enhance parameter meaning beyond schema's chain and limit 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?

Description clearly states the tool discovers freshest token launches with profiles, descriptions, and social links. Differentiates from siblings by focusing on early-stage tokens in first minutes/hours.

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?

Implies usage for catching early token launches, but lacks explicit when-to-use or when-not-to-use compared to siblings like rug_check or token_scan. No alternatives or exclusions mentioned.

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 fully discloses the premium nature, payment cost, API call method, output format (risk score 0-100 with flags), and free initial units. This adequately covers 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 a single, information-dense sentence that front-loads the core purpose. It efficiently conveys the key details without 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 covers the main aspects: purpose, payment, API call, output. However, it does not clarify the relationship between the three parameters (e.g., whether address is preferred over query) or any parameter dependencies. Despite no output schema, the return format is summarized. Overall adequate but could be more 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?

Each parameter has a description in the schema (chain ID, query, address). The tool description does not add further semantic value beyond confirming the purpose of these parameters. Since schema coverage is 100%, 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's function as a risk assessment for tokens, listing specific analyses (liquidity, age, volume, buy/sell ratio, FDV). This distinguishes it from sibling tools like chain_radar or health_check, which focus on other aspects.

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 token risk evaluation but does not provide explicit when-to-use or when-not-to-use guidance. It mentions payment requirements but not alternatives among siblings.

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

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

No annotations are present, so the description must convey behavioral traits. It lists the types of data returned ('price, liquidity, volume...') but does not disclose potential side effects (none expected for read-only), rate limits, or data freshness. The description is adequate but lacks depth about operational 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 consists of two sentences: the first covers the output scope, the second covers search methods. It is concise and front-loaded, though the list of data points 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 no output schema, the description lists many fields but does not specify return structure or error handling. It is partially complete for a scanning tool but lacks details on edge cases or missing data.

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

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

The input schema has 100% description coverage, so the schema already explains each parameter. The description adds 'Search by name, symbol, or contract address,' which paraphrases the schema. It does not provide additional semantic meaning beyond what the schema offers.

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 'deep scan' of tokens, listing specific data points (price, liquidity, volume, etc.) and search methods (name, symbol, contract address). This distinct purpose is well differentiated from sibling tools like rug_check or whale_watch.

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

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

The description implies the tool is for obtaining comprehensive token information, but it does not specify when to use it over siblings (e.g., for rug check vs. general scan). No explicit when-not or alternative guidance is provided, leaving the agent to infer usage context.

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

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

No annotations are provided, so the description must fully disclose behavior. It mentions data sources (DexScreener + CoinGecko) and filter options, but lacks details on data freshness, rate limits, or what 'most-boosted' means. The description is adequate but leaves 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?

Two sentences: first states purpose and sources, second adds filter. No redundant words, information is front-loaded. Efficient and to the point.

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 no output schema, so the description should hint at return structure. It doesn't, which is a minor gap. However, given the straightforward nature (a list of memecoins), the description is largely sufficient for selection and invocation.

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

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

The input schema already describes both parameters with 100% coverage. The description adds value by listing example chain values in parentheses, slightly augmenting the chain parameter. For limit, no extra info is added, but baseline is high.

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

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

The description clearly states the tool retrieves 'hottest trending and most-boosted memecoins' from specific sources, with a filter option. This distinct purpose stands out from sibling tools like 'rug_check' or 'token_scan', which serve different functions.

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 finding trending memecoins and provides a filter by chain. While not explicitly stating when to avoid or switch to alternatives, the name and context make it clear, and no conflicting guidance is given.

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

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

Discloses the need for payment, free trial allowance, and output categories. No annotations are provided, so the description covers core behaviors. Lacks mention of rate limits or failure modes, but sufficiently transparent.

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 relatively concise despite using emoji and color symbols. It front-loads the premium requirement and quickly covers key details. Slightly verbose due to emoji, but still 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 complexity (premium payment, multiple data sources, classification output), the description covers all essentials: payment mechanism, free units, output categories. No output schema exists, so it appropriately explains the return values.

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 (chain, query, address). The description adds no extra meaning beyond what the schema provides, justifying the baseline score of 3.

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

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

The description clearly states the tool's purpose: viral potential analysis using Google Trends and DexScreener, outputting specific categories (DEAD, QUIET, etc.). It distinguishes itself from sibling tools by detailing its unique data sources and classification output.

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?

Explicitly mentions premium status, payment requirements ($0.05 via x402), free units for new wallets, and the calling URL with header. While it doesn't compare to siblings, the context for using this paid tool is clear.

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?

Without annotations, the description carries the burden of behavioral disclosure. It implies a read-only operation by stating it 'shows' data, but lacks details on data freshness, rate limits, or potential side effects. Some behavioral context is provided by describing output types.

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

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

The description is two sentences with no wasted words. It is front-loaded with the key concept 'Smart money signals' and efficiently explains the two output types.

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 tool with two optional parameters and no output schema, the description adequately explains what the tool returns. It covers the two signal types, which is sufficient for an agent to understand the core functionality, though output format details are missing.

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

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

All parameters (chain, limit) have descriptions in the schema (100% coverage), so the baseline is 3. The description does not add parameter details beyond what the schema provides.

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

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

The description clearly states the tool provides 'smart money signals' specifically 'top boosted tokens (whale activity) and community takeovers (CTO detection).' This distinguishes it from sibling tools like chain_radar or health_check, though it does not explicitly differentiate from them.

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

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

The description offers no guidance on when to use this tool versus alternatives. It merely describes the output without stating typical use cases, prerequisites, or scenarios to avoid.

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