zero-core-intel

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

No annotations are provided, so the description bears the burden of disclosure. It lists what is checked (status, uptime, payment network configuration), which suggests a read-only operation, but it doesn't explicitly state side effects, permission requirements, or return behavior. Adequate but minimal.

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, clear sentence with no redundant or filler words. It earns its place by concisely stating the tool's 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?

For a simple health-check tool with no parameters and no output schema, the description provides sufficient context about what is checked. It could mention output format or what 'status' entails, but the low complexity makes the description 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 tool has zero parameters, so the schema is trivially complete. The description doesn't need to explain parameters or add parameter details, and with no parameters, the baseline of 4 is appropriate.

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

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

The description states a specific action ('Check') and a specific resource ('Harvey Intel server status, uptime, and payment network configuration'). It clearly distinguishes itself from sibling tools that retrieve market or token data, as this is about system health.

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 when needing server health information but provides no explicit guidance on when to choose this tool over alternatives or any exclusions. Since it's a simple health check, the implied usage is moderately 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?

With no annotations, the description must fully convey behavioral traits. It states the tool lists tools with pricing and input requirements, which suggests a read-only discovery operation, but it does not explicitly mention absence of side effects, authentication requirements, or output structure. Since 'list' implies a read operation, this is minimally transparent but lacks extra context like pagination or response format.

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 short sentences with no filler. The primary action and purpose are front-loaded in the first sentence, and the usage guidance is in the second. Every word earns its place, making it exceptionally 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?

For a simple tool with no parameters and no output schema, the description adequately conveys what it does and when to use it. The output is described conceptually ('list with pricing and input requirements'), but the absence of a detailed output schema means the description could have added more specifics about the returned fields or structure, though it remains sufficient for basic discovery purposes.

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 per the baseline rule, a score of 4 is appropriate. The description does not need to explain parameter semantics, and it does not attempt to. The mention of 'input requirements' refers to the contents of the output (other tools' requirements), not this tool's own parameters.

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

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

The description clearly states the tool's function: 'List all available Harvey Intel tools with pricing and input requirements.' The verb 'List' and the resource 'available Harvey Intel tools' are specific, and the additional detail about pricing/input requirements distinguishes this discovery tool from sibling tools that provide actual intelligence 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 phrase 'Use this for discovery' provides an explicit use case, implying this tool is for discovering what tools exist rather than invoking them. It does not explicitly state when not to use it, but given the sibling tools are all data retrieval functions, the context effectively differentiates this tool from alternatives.

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

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

Annotations are empty, so the description carries the full burden. It discloses the meaningful output surface (score calibration basis, risk flags, honeypot detection, temporal prediction), but says nothing about whether the call is read-only, cost/latency of a 'full' scan versus preview, or any 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?

One compact sentence that front-loads what the tool does and follows with the return contents. No filler, though the marketing-flavored 'calibrated on the real outcomes of tokens RugSlayer scanned' phrase is heavier than it needs to be.

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

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

With no output schema, the description usefully enumerates the returned fields (score 0-100, risk level, rug stage, honeypot, flags, temporal prediction), which is what an agent needs to know. The main gap is the absence of any routing versus scan_token_preview.

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?

Single required parameter with 100% schema description coverage ('Solana token mint address (base58)'), so the schema already documents format and meaning. The description adds no further detail about the mint argument; baseline 3 applies.

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

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

States a specific verb+resource (risk analysis for a Solana token) and names the analyzable entity precisely. The word 'Full' hints it is the heavier counterpart to scan_token_preview, but the sibling is never named, so differentiation must be inferred.

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 when-to-use guidance, no conditions, no mention of scan_token_preview as the lighter alternative even though it is the obvious sibling. The agent is left to guess whether this or the preview variant is 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 provided, the description carries the full burden of behavioral disclosure. It discloses that the tool returns a risk level classification (LOW/MEDIUM/HIGH/CRITICAL) and implies it is a lightweight preview by calling itself 'Quick' and 'Free preview'. However, it does not mention whether the call is read-only, error behavior for invalid mint addresses, or any rate limits, which would be useful but are not critical for a simple preview 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 extremely concise, using two sentences to state the purpose, output values, and usage guidance. It is front-loaded with the core action ('Quick risk level check') and wastes no words, earning a perfect score.

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

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

Given the tool's low complexity (one parameter, no output schema), the description adequately covers what it does, what it returns, and how it differs from the full analysis tool scan_token. It does not explain what each risk level means or how it is calculated, but for a free preview, this is acceptable. The description is complete enough for an agent to invoke it correctly in many contexts.

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 fully describes the single parameter 'mint' with 'Solana token mint address (base58)'. The description does not add any additional meaning beyond the schema, so with 100% schema description coverage, a 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 performs a 'Quick risk level check' for a Solana token, with a specific output of LOW/MEDIUM/HIGH/CRITICAL. It distinguishes itself from the sibling tool scan_token by explicitly saying 'use scan_token for full analysis', making its scope and resource clearly defined.

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

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

The description explicitly provides usage guidance: it is a 'Free preview' intended for a quick check, with the alternative 'use scan_token for full analysis' when more comprehensive results are needed. This tells the agent when to select this tool versus its sibling scan_token.

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