Alien Plugg x402 API

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

With no annotations, the description carries full burden for behavioral transparency. It reveals the report contents but does not disclose whether it is a read-only operation, how data is sourced, whether authentication is needed, or the output format. The description is more about content than 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 a single, concise sentence that leads with the core purpose ('Daily curated alpha report') and lists key contents. Every word adds value, with 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 no output schema, the description should indicate what the report includes; it does ('top picks, rug warnings, DCA advice'). However, it lacks specifics on format, structure, or how the report is delivered (e.g., list, summary, JSON). This leaves some ambiguity for an agent deciding how to present 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?

The tool has zero parameters, so the schema is fully covered (100%). The description adds no parameter details, which is acceptable since none exist. Baseline of 4 applies as there is nothing for the description to clarify.

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 'daily curated alpha report' with specific content ('top picks, rug warnings, and DCA advice'). It distinguishes from siblings by focusing on a consolidated daily report rather than individual token checks or analyses. However, there is no explicit verb (e.g., 'get', 'generate'), reducing precision slightly.

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. It does not mention scenarios like 'for daily overview' or contrast with specific sibling tools. The description implies usage for those seeking a daily summary, but this is not stated.

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?

Since no annotations are provided, the description carries the full burden of disclosing behavioral traits. It only mentions the stylistic 'brutal' and the indicators, but does not disclose whether the operation is read-only, what the input 'address' should represent, what output format to expect, or any limitations (e.g., rate limits, data sources). This leaves significant gaps for the agent.

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, concise sentence that directly states the tool's focus. It is efficient and every word contributes to the core meaning, with no redundancy or filler. It is appropriately sized and front-loads the key concept ('chart analysis') before listing indicators.

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 a simple schema (one parameter), no output schema, and no annotations, so the description is the primary information source. However, it does not explain what the address is used for, what type of chart is analyzed, or what the response contains. The description is too vague to fully understand the tool's context and limitations, leaving the agent with incomplete information.

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 does not mention the 'address' parameter at all, and the input schema only defines it as a string without further description. With 0% schema description coverage, the agent must rely solely on the parameter name 'address', which is ambiguous (token contract? wallet address? pair address?). The description fails to add any meaning to the parameter, making it difficult to invoke correctly.

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 chart analysis with specific technical indicators (RSI, MACD, support/resistance). This distinguishes it from sibling tools like holder_analysis or honeypot_check, which focus on different aspects. However, the verb is implicit ('chart analysis' rather than an explicit action like 'analyze' or 'fetch'), so it lacks a strong verb+resource structure.

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 alternatives. It does not mention any conditions, exclusions, or comparisons to sibling tools. The description implies it is for chart analysis, but does not explicitly state when it should be chosen over other tools, making it difficult for an agent to select it appropriately.

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 of behavioral disclosure. It only states the basic lookup action without any additional context such as read-only nature, potential delays, error cases, or data limitations. There is no indication of side effects or special behaviors.

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 one concise sentence that immediately states the tool's purpose. It is front-loaded and contains 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?

Given the tool's simplicity (one parameter, no output schema), the description provides a basic understanding but lacks details on return values, edge cases, or usage context. It is sufficient for a simple lookup 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?

The schema has a single 'address' parameter with no description, and schema coverage is 0%. The description does not explicitly explain the address parameter beyond implying it is the creator's address. It adds minimal semantic value beyond the raw schema.

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

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

The description uses the specific verb 'look up' and clearly identifies the resource: a Zora creator's profile and all their launched coins. This is distinct from sibling tools like zora_portfolio or zora_scanner, which likely focus on different 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?

No guidance is provided on when to use this tool versus alternatives. The description only states what it does, with no mention of exclusions, prerequisites, or situations where another tool would be preferred.

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 but only says 'analyze'. It does not disclose whether the operation is read-only, what data source is used, any potential side effects, or what the Gini coefficient output represents.

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, concise sentence with no wasted words, but it omits essential details. It is appropriately brief, though not a model of complete 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?

Given only one parameter and no output schema, the description should at least explain what 'address' refers to and what the result will be (e.g., a numerical Gini coefficient). Instead, it leaves these critical aspects unspecified, making invocation uncertain.

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 has 0% coverage for the 'address' parameter, and the description does not explicitly identify it as the token contract address or explain required format. The phrase 'token holder concentration' implies the address is a token, but this is indirect and incomplete.

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 analyzes token holder concentration using the Gini coefficient, giving a specific verb and resource. It distinguishes from sibling tools like honeypot_check or token_price by focusing on distribution metrics.

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 are any exclusions or context given. The description simply states the function, leaving the agent to infer when it's 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?

Despite no annotations, the description discloses key behavior: it simulates a sell and returns whether selling is possible. This gives the agent a clear expectation of safety and output, though it could mention edge cases or supported networks.

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 focused sentences. The first states the purpose immediately, and the second explains the simulation behavior without unnecessary detail.

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 provides the essential outcome (sell simulation result) despite lacking annotations and output schema. It could be improved by specifying return format, but the core is covered.

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 explicitly define the 'address' parameter beyond the tool's purpose. It fails to clarify that address is the token contract address or what format/network is expected.

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 detects honeypots via 'Detect if a token is a honeypot' and adds the selling simulation mechanism, distinguishing it from general token analysis tools like chart_roast or holder_analysis.

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

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

Usage is implied: use when needing to determine if a token is a honeypot. However, there is no explicit guidance on when to prefer this over sibling tools like zora_rug_check, nor any exclusions or prerequisites stated.

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 for behavior. It mentions output fields but does not disclose ordering, recency definition, pagination, rate limits, or error behavior. The tool's side effects and operational constraints are completely unaddressed.

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 focused sentence that front-loads the core purpose and adds relevant output details. No filler or redundant phrasing exists.

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

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

The tool is simple with one optional parameter and no output schema. The description covers the basic purpose and output fields, but it omits practical details such as how to use 'limit' and what the response structure looks like, leaving the agent with gaps for a complete 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 description coverage is 0%, and the description does not mention the 'limit' parameter at all. The agent receives no help understanding what limit does, its default value, or acceptable range, making the parameter effectively undocumented.

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 action ('Get'), the specific resource ('newest token launches on Zora'), and the key output fields ('market cap and volume'). This distinguishes it from sibling tools that focus on portfolio, scanning, or rug checks.

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 alternatives like zora_scanner, zora_portfolio, or alien_plugg_alpha. The description implies use for discovering new launches, but it provides no exclusions, prerequisites, or comparison to 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 are provided, so the description carries the full burden of behavioral disclosure. It discloses the data source and query flexibility but omits critical behavioral details such as API rate limits, required authentication, response format, or how errors (e.g., invalid address) are handled. The absence of this context leaves the agent uncertain about expected 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 a single, concise sentence with no redundant information. It front-loads the core purpose and includes only necessary details, making it easily scannable.

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

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

For a simple one-parameter tool with no output schema or annotations, the description covers the essential purpose and query semantics. However, it lacks information about output format or any limitations (e.g., supported networks). Given the low complexity, this is nearly complete, though additional behavioral context would make it fully self-sufficient.

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's 'query' parameter has no description (0% schema coverage), so the description must compensate. It does so by explaining that 'query' can be an id, symbol, or contract address. This adds essential meaning beyond the schema, though it could further clarify formatting requirements for contract addresses (e.g., chain prefix).

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 verb 'Get', the resource 'current token price', and the source 'CoinGecko'. It also specifies multiple query methods ('by id, symbol, or contract address'), making the tool's purpose specific and distinct from sibling 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?

The description implies the tool is used when a current token price is needed, and it accepts flexible identifiers. However, it does not explicitly state when to prefer this tool over alternatives, nor does it mention any exclusions or prerequisites. The context is clear but not elaborated.

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 burden. It implies a read-only operation via 'Get' and describes outputs (PnL, allocation breakdown), but does not explicitly state permissions, prerequisites, or edge cases. Adequate for a simple read tool, but not fully 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?

One sentence with only 10 words, front-loaded with the main verb and resource. No redundant or unnecessary information, making it highly concise and well-structured.

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

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

The description covers the core purpose and hints at output (PnL, allocation breakdown), but with no output schema and only minimal parameter detail, it leaves gaps in expected return format and potential errors. It is adequate for a simple tool but not comprehensive.

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 the 'address' parameter. The description implies address is the wallet address to query, but does not explicitly state its format, chain, or necessity. It only partially compensates for the missing schema information.

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 uses specific verb 'Get', resource 'wallet holdings on Zora', and adds details about PnL and allocation breakdown. This clearly distinguishes it from sibling tools like creator_lookup or token_price, making its purpose unambiguous.

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

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

No guidance is given on when to use this tool vs alternatives. Sibling tools such as holder_analysis and zora_scanner exist, but the description does not provide any context, prerequisites, or exclusions for choosing this tool.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the output format (risk score, verdict, reasoning) but does not disclose other behavioral traits such as whether it performs on-chain analysis, makes external network calls, or is read-only. The term 'check' implies a read operation, but the description remains minimal on deeper 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 a single, efficient sentence that front-loads the purpose and mentions the output. It contains no fluff and earns every word.

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

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

Given the tool's simplicity (one parameter, no output schema, no annotations), the description covers the core purpose and output structure. It does not explain edge cases like what happens if the address is invalid or not on Zora, but for a basic check tool, it is reasonably 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 only an 'address' parameter with zero description, so the description must compensate. The description's use of 'any Zora token' implies that the address is the token's contract address, adding meaning beyond the bare schema. However, it does not specify the exact format or any constraints (e.g., chain, type), so it is not fully exhaustive.

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 action ('Check any Zora token') and the resource ('any Zora token'), with a specific purpose ('rug risk'). It also details the output (0-100 risk score with verdict and reasoning), which distinguishes it from sibling tools like honeypot_check by focusing on Zora tokens and a quantitative risk score.

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

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

The description gives clear context for when to use the tool: when you need to assess rug risk for a Zora token. However, it does not explicitly state when not to use it or mention alternative tools like honeypot_check, so it lacks exclusion/alternative 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?

There are no annotations, so the description must fully disclose behavior. It states what is returned (top movers with market cap, volume, 24h change, signals) but does not reveal safety attributes (e.g., read-only nature), data source limitations, rate limits, or any caveats. More context is needed for a scan tool.

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

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

The description is two sentences, front-loaded with the main purpose, and every clause delivers useful information. It is concise without sacrificing 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?

With no parameters and no output schema, the description sufficiently outlines the tool's purpose and return fields. It does not elaborate on output formatting or pagination, but for a simple scanning tool, the given details are adequate.

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

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

The tool has zero parameters, and the schema reflects that with an empty properties object. The description adds no parameter details because none exist, which satisfies the baseline for 0 params. The output fields are mentioned, but that does not affect parameter 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?

The description clearly identifies the tool's function: 'Scan Zora for trending coins and trading signals'—a specific verb and resource. It also lists concrete outputs (market cap, volume, 24h change, BUY/SELL/STRONG_BUY signals), distinguishing it from sibling tools like new_launches or token_price.

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

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

The description implies when to use the tool (when a user wants trending coins and trading signals on Zora), but it does not explicitly mention alternatives or exclusion cases. It lacks direct comparison to sibling tools, so guidance is implied rather than articulated.

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