47620 Solana Data

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

With no annotations, the description carries the burden of behavioral disclosure. It usefully discloses the monetary cost ($0.002 USDC) and the comprehensive scope of the balance lookup, but it does not state whether the operation is read-only, how errors are surfaced, or any rate-limit constraints.

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, front-loaded sentence that conveys the core behavior, scope, and cost with no filler. Every clause earns its place.

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

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

For a simple one-parameter read tool with no output schema, the description sufficiently explains what the call returns (native and SPL balances) and the cost. It does not detail response formatting or failure modes, but the low complexity and full schema coverage keep the gap minor.

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

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

Schema description coverage is 100% and the single parameter is adequately described as 'Solana wallet address'. The tool description adds no further semantic detail beyond the schema, so the baseline of 3 applies.

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

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

The description clearly identifies the resource (a Solana address) and the exact data returned: native SOL balance plus all SPL token balances including USDC. It is distinguishable from sibling tools by content focus, though it does not explicitly name an alternative.

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 no guidance on when to use this tool instead of siblings like solana_token, solana_tx, or solana_trending. It states the pay-per-call cost but not the conditions or contexts in which this tool is the appropriate choice.

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 behavioral disclosure burden. It does disclose the call's expected outputs and the pay-per-call cost of $0.001 USDC, which is useful. However, it does not mention auth requirements, rate limits, availability, or response format, leaving some behavioral traits undisclosed.

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

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

The description is a single sentence that front-loads the resource, immediately lists the three returned metrics, and ends with the pricing detail. There is no filler and every phrase earns its place.

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

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

For a zero-parameter, low-complexity read-only health tool, the description provides all essential selection information: the resource, the exact returned values, and the cost. The lack of an output schema is acceptable because the expected data points are stated directly in prose.

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 zero parameters and 100% schema description coverage, so there are no parameter semantics for the description to clarify. The baseline of 4 applies because parameter documentation is effectively a non-issue.

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 reports Solana network health and names three concrete outputs: current slot, epoch, and SOL/USD price. This is specific enough to distinguish it from the token, account, transaction, and trending siblings, even though it does not explicitly contrast itself with 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?

No explicit when-to-use, when-not-to-use, or alternative tool guidance is provided. The agent must infer from the 'network health' label and the sibling names that this is the right tool for chain status and price checks. For a zero-parameter health endpoint this is acceptable, but the usage context remains implicit.

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 of explaining behavior. It discloses the returned information, the 0-100 risk score, the proceed/review verdict, and the pay-per-call cost. It does not explicitly state that the call is read-only or describe error behavior, but for a risk-check tool this is reasonably 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 compact and front-loaded: it states the triggering condition first, then lists outputs, then the purpose and cost. Every sentence provides necessary information and there is no filler or repetition.

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

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

For a single-parameter tool with no annotations and no output schema, this description is complete. It explains when to use it, what it returns, why it matters, and even discloses the per-call cost. An agent has enough context to select and invoke the tool 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 description coverage is 100%, so the baseline applies. The single 'address' parameter is already described as 'Solana address to check before paying' in the schema. The tool description adds context about SOL/USDC and risk, but does not add new parameter-level semantics beyond the schema.

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

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

The description clearly states the tool's purpose: a pre-payment risk check for Solana addresses. It specifies the resource (Solana address), the action (check risk before sending SOL/USDC), and the outputs (account type, balance, activity, risk score, verdict), which distinguishes it from sibling tools like solana_account.

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

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

The description explicitly tells the agent when to use it: before sending SOL/USDC to any address, and to avoid paying dead, wrong, or program addresses. It does not explicitly name alternative tools or exclusions, but the triggering condition is clear enough for an agent to route correctly.

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 of behavioral disclosure. It usefully reveals that the call aggregates multiple network data points, is a single call rather than separate ones, and carries a pay-per-call cost of $0.01 USDC. However, it does not disclose output format, failure behavior, or whether any authentication or rate limits apply.

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 compact, front-loaded with the core value proposition, and every sentence provides distinct information: what the tool returns, why it is advantageous, and what it costs. There is no filler or redundancy.

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

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

For a zero-parameter tool, the description gives a solid picture of what the agent will receive: health, slot, epoch progress, price, and trending pairs. It also covers pricing, which is behaviorally relevant. There is no output schema, but the enumerated data categories are adequate for an agent to decide whether to invoke 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?

The tool has zero parameters, so there is no parameter semantics for the description to add. With an empty input schema and no parameters, the baseline of 4 applies because no param documentation is needed; the description focuses instead on what the call returns.

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: providing a whole-network picture in one call, enumerating specific data points such as cluster health, current slot, epoch progress, SOL/USD price, and top trending pairs. It distinguishes itself from sibling tools by explicitly positioning it as a consolidated alternative to making multiple separate calls.

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 clear context for when to use this tool: when a broad, multi-signal snapshot is needed and paying for one combined call is cheaper than several individual calls. It does not explicitly state when NOT to use it or name the specific sibling alternatives, but the usage context is evident 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, the description carries the burden of behavioral disclosure. It does add meaningful context by stating the tool is pay-per-call at $0.002 USDC and that data is live, which goes beyond a generic fetch. However, it does not mention error behavior, rate limits, or what happens for invalid mint addresses.

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: one clause states the returned data and input scope, and one clause states the cost. There is no redundant or filler content, and the most important information is 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?

For a simple one-parameter read-style tool with no output schema, the description covers the input, the returned fields, and the cost model. It does not describe response format or failure cases, but the tool's low complexity and the description's directness make it largely 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 coverage is 100%, so the schema already documents the single 'mint' parameter as an SPL token mint address. The description adds only 'any' and 'Solana' context, which does not materially improve understanding beyond the schema. A baseline of 3 is appropriate.

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

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

The description names the resource (Solana SPL token mint) and the data returned (price, liquidity, 24h volume, DEX pairs), which clearly distinguishes it from the account, transaction, health, and trending siblings. It lacks an explicit verb like 'get' or 'fetch', but the intent is unambiguous.

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

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

No guidance is given about when to choose this tool over the sibling tools. The phrase 'for any Solana SPL token mint' implies the input condition, but there is no explicit when-to-use, exclusions, or reference to alternatives such as solana_account or solana_trending.

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 behavioral disclosure burden. It adds valuable context such as pay-per-call pricing and the categories of data returned. However, it does not disclose potential failure modes, data freshness guarantees, auth requirements, or whether the call mutates anything or is read-only, leaving some agent-facing ambiguity.

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

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

Three sentences, each earning its place: what it returns, when to use it, and cost. The main deliverable is front-loaded in the first sentence. Minor structure improvements could separate pricing into a more prominent callout, but overall it is tight and readable.

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, no output schema, and no annotations, the description provides a solid picture: purpose, included data categories, use case, and cost. It does not describe the output shape or error behavior, but the listed report contents approximate the return set well enough for a single-mint research 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 covers the single `mint` parameter with a clear description ('SPL token mint address'), so schema coverage is 100%. The description does not add meaning beyond naming the token context, but none is strictly needed for a single, well-documented parameter.

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

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

The description names a specific verb/resource ('Full token due-diligence') and enumerates concrete items (live price, liquidity, 24h volume, DEX pairs, supply, mint authority). It also distinguishes itself from 'multiple lookups,' making clear this is an aggregator tool rather than a single-purpose lookup, which helps separate it from siblings like solana_token.

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?

States a clear use case: 'Use for token research instead of multiple lookups.' This implies it is the preferred choice when broad token data is needed and that narrower tools may be more appropriate for single metrics, though it does not explicitly name alternatives or when not to use it.

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

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

Annotations are absent, so the description carries the full burden. It discloses pay-per-call cost and the notion of being a live feed, but does not state whether the operation is read-only, what error handling or rate limits exist, or how the response is structured. For a tool that agents will call, these are significant omissions.

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, with three short sentences that front-load the core purpose first. The second sentence about being a fresh feed adds a slight redundancy but still conveys usage context. The cost mention is important and well placed. There is minimal fluff, and it is easily skimmable.

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 no output schema, the description should at least indicate the nature of the returned data (e.g., an array of pair objects with volume fields), but it only says 'DEX pairs' without structural details. It also omits any authentication or setup prerequisites. For a simple tool with no parameters, this is still incomplete for an agent that needs to consume the response 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?

The tool has zero parameters, so schema coverage is 100% by default. The description does not need to explain parameters. The baseline for 0 parameters is 4, and no additional parameter information is required.

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

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

The description clearly states the tool returns live trending/new Solana DEX pairs ranked by 24h volume. The resource and sorting criterion are specific, and the purpose is distinct from sibling tools like solana_token or solana_account. Even though the verb is implicit, the meaning is unambiguous.

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

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

The description implies this tool is for retrieving current market data (trending/new pairs) and mentions it is a 'fresh feed for agents', suggesting repeated polling. However, it gives no explicit guidance on when to use this tool versus the siblings (e.g., solana_health for network status, solana_token for token details) nor any exclusions. Usage context is implied but not explicit.

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

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

With no annotations, the description carries the full burden. It does disclose a meaningful behavioral trait: pay-per-call with a specific cost ($0.003 USDC), which is valuable for an agent deciding whether to invoke it. It also describes the output categories, but it does not mention potential errors, signature format requirements, or whether the call 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?

The description is a concise single sentence that front-loads the core output information and appends the pay-per-call cost. Every clause adds useful information, and there is no wasted wording.

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

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

For a simple tool with one required parameter and no output schema, the description is largely complete: it tells the agent what data will be returned and warns about the cost. It could be improved by noting any special formatting requirements for the signature, such as base58 encoding or mainnet specificity, but these are not critical 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?

Schema coverage is 100%, so the baseline is 3. The schema already documents the single 'signature' parameter. The description adds confirmation that the signature is for a Solana transaction, but it does not add format details, network context, or example values beyond what the schema conveys.

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 resource: a Solana transaction signature, and lists the exact data it returns (status, slot, fee, block time, transfer summary). It lacks an explicit verb like 'retrieves' or 'gets', but the noun-phrase style is still unambiguous and distinguishes it from the sibling tools, which cover health, token, account, and trending 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?

There is no guidance on when to use this tool versus the siblings solana_health, solana_token, solana_account, or solana_trending. The use case is implied by the resource type, but no explicit context, prerequisites, or exclusions are provided.

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