Autosophia Solana Lens

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 adds the cost detail 'Free' and describes the action as a 'connectivity check,' which implies a read-only operation. However, it does not explicitly state that the operation is safe, has no side effects, or what it returns. For a simple health probe, this is adequate 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?

The description is a single sentence that is front-loaded with the core purpose ('RPC connectivity check'), followed by two high-value extras: cost ('Free') and usage guidance. Every word earns its place, with no redundancy or filler. It is a model of conciseness.

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

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

For a tool with no parameters and no output schema, the description covers the essential aspects: what it does, when to use it, and cost. It does not specify the return format or how to interpret results, but for a simple connectivity check, the agent can infer that it returns a status. The description is largely complete for the tool's simplicity.

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 input schema is trivially complete at 100% coverage. The description does not need to explain parameter details, as there are none. According to the rubric, 0 parameters yields a baseline of 4, which is appropriate here.

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: 'RPC connectivity check.' This is a specific verb (check) and resource (RPC connectivity), and it distinguishes the tool from siblings like inspect_wallet or payment_info, which serve different purposes. The phrase is unambiguous and directly conveys what the tool does.

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 explicit usage context: 'Use when diagnosing timeouts before paid calls.' This tells the agent when to invoke the tool (when timeouts are suspected) and provides a temporal reason (before spending on paid calls). It does not explicitly name alternative tools or state when not to use it, but the context is clear and sufficient for decision-making.

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

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

With no annotations, the description carries full behavioral burden and it delivers: it declares the call is read-only, states cost ($0.01 per call), typical latency (under 2s), and the data categories returned. This goes well beyond a generic 'inspect wallet' phrasing.

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: purpose, return contents, use cases, commercial/latency notes, and parameter help are packed into three short sentences plus a one-line parameter explanation. There is no filler or repetition of schema 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?

For a single-parameter read-only tool, the description covers purpose, output fields, use cases, cost, latency, and semantics of the only input. No output schema exists, but the description's list of returned data categories gives the agent an adequate expectation of the result.

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 only provides a string property named 'address' with zero description coverage. The tool description compensates fully by labeling that parameter and giving a concrete example address, which is exactly what the agent needs to invoke the tool 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?

Description identifies a clear action and resource: 'One-call profile of a Solana wallet,' and enumerates exactly what the call returns (SOL balance, SPL holdings, activity, failure rate, age, program flag). This scope distinguishes it from siblings like simulate_transaction or payment_info.

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?

It gives explicit application contexts: judge a counterparty, monitor a treasury, or research a wallet before interacting with it. It does not explicitly name alternative sibling tools or state when not to use it, but the guidance is sufficient for selection among these distinct 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?

With no annotations, the description carries the burden of behavioral disclosure. It clearly implies a non-mutating, informational role ('How to pay, step by step'), which is transparent enough. It does not explicitly confirm there are no side effects, but the phrasing strongly suggests it is a guide rather than a payment execution.

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 states the purpose and usage condition without any filler. Every word 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, no-output-schema informational tool, the description fully covers purpose and usage. It even includes the contextual trigger (402 error), making it complete for an agent to decide when to invoke it.

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

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

The tool has zero parameters, so the baseline is 4. The description adds no parameter-specific details, but none are needed since the schema is empty.

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 step-by-step payment instructions, with a specific trigger ('if you got a 402'). This distinguishes it from sibling tools like health or inspect_wallet, which address different concerns.

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 an explicit condition for use: 'Read this if you got a 402 and are not sure what to do.' While it does not name alternatives or when-not-to-use scenarios, the context is specific enough to guide an agent.

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 behavioral transparency burden. It discloses the sample window, the exact output categories, the trend, and the $0.01 per-call cost in USDC. It implies a read-only operation by saying 'returns,' but it does not explicitly state side-effect absence or failure 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?

Every sentence earns its place: purpose, returned data, usage directive, pricing, and parameter explanation. The most important information is front-loaded, and there is no redundant 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?

For a tool with a single optional parameter and no output schema, the description is complete. It covers all returned values, the lookback window, cost, recommended tiers, and parameter usage, so an agent has enough context to invoke it 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 0%, but the description fully compensates for the lone 'accounts' parameter by explaining that it is an optional list of writable account pubkeys and that omitting it yields a global sample. This gives the agent everything needed to use the parameter 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 what the tool does: it returns p50/p75/p90/p99 microlamports from the last 150 slots, the trend, and recommended fee tiers with SOL costs. However, it does not explicitly distinguish itself from sibling tools like simulate_transaction, so it stops short of full sibling differentiation.

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

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

The description gives a clear usage trigger: 'Use before every transaction you need to land.' It also explains how to handle the optional accounts parameter. It does not state when not to use the tool or name alternatives, so it is clear but lacks explicit exclusions.

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

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

With no annotations, the description carries the full burden. It discloses that submissions go to a queue and public board, contact details are never shared, and entries are reviewed before publishing. These are meaningful behavioral traits beyond the schema, though it stops short of describing the response or any side effects.

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

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

The description is three sentences, front-loaded with the primary purpose, then adds key facts (free, queue, privacy) and a final instruction. Every sentence earns its place with no redundant or filler content, striking an ideal length for the tool's simplicity.

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 purpose, data flow, privacy, and willingness-to-pay, but omits details on all parameters and the expected response. For a simple submission tool with 4 params and no output schema, it is adequate but has clear gaps around tried/contact and what happens after submission beyond 'reviewed before publishing'.

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%, so the description must compensate. It implicitly covers 'need' ('what you needed') and 'would_pay_usd' ('what you would pay'), but does not explain 'tried' or 'contact'. Two of the four parameters remain unexplained, leaving the agent to guess their format and purpose.

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 opens with a clear verb and resource: 'Tell this server what you needed and could not get.' This distinctly identifies the tool as a request for missing capabilities, contrasting with siblings like health, inspect_wallet, and simulate_transaction. It fully conveys the tool's core function.

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

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

It provides context on when to use by mentioning 'free' and the process of going to an operator queue and public board, which helps agents understand this is for unmet needs. It doesn't explicitly state alternatives or exclusions, but the 'free — no payment required' line signals a contrast with payment-related siblings, offering partial usage 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?

With no annotations, the description carries the full burden, and it delivers: it discloses read-only behavior ('never signs or sends'), pricing, no account/API key requirement, typical response time, and the concrete data sources. This goes well beyond minimal disclosure.

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 information-dense but every sentence earns its place: purpose, trigger, output details, practical benefits, pricing, safety, and parameter format. The parameter explanation is cleanly separated at the end.

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 one-parameter tool with no output schema and no annotations, the description is complete: it tells the agent when to invoke it, what input is required, what output to expect, and important behavioral constraints. Nothing critical is 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?

Schema description coverage is 0%, but the description compensates fully by explaining that 'mint' is an SPL token mint address and providing a concrete example address. For a one-parameter tool, this is sufficient and clear.

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 a specific verb and resource: it delivers a go/no-go risk verdict on a Solana SPL token. It specifies the output (0–100 risk score, reasons, slippage curve) and its use case, which distinguishes it from siblings like inspect_wallet or simulate_transaction.

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?

It gives an explicit trigger: 'Use when you are about to buy, swap, or approve an unfamiliar mint.' It also mentions what it replaces (multiple RPC round-trips and a quote sweep), providing clear context, though it does not explicitly compare to sibling tools or state when not to use it.

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

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It mentions the tool will convey limits and capabilities, but it doesn't disclose whether the tool is read-only, has side effects, or what the response format is. The nature of an info tool implies no side effects, but this is not explicitly stated.

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, extremely concise, and front-loaded with 'Start here.' Every word adds value, making it an exemplary model of efficiency.

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 no-parameter informational tool, the description is largely complete. It defines the tool's purpose and when to use it. It could be more explicit about the tool's read-only nature, but the content is sufficient for an agent to select and invoke it 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 the baseline score is 4 per the rubric. There is no need for the description to explain parameters, and the schema confirms an empty properties object.

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 this tool as an informational starting point, stating it provides 'what this server sells, what it will not do, and the exact limits.' This distinguishes it from sibling tools by positioning it as the entry point for understanding the service, though it lacks a specific verb for an operation.

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 'Start here' explicitly instructs the agent to use this tool first before others, providing clear usage context. It doesn't explicitly name alternatives or exclusions, but the directive to start here is sufficient guidance for when to use 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, the description carries the full burden, and it delivers: it states the simulation runs on mainnet, never sends, costs $0.01 per call, and returns specific diagnostics. This openly discloses the side-effect-free nature and the pricing, leaving little 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?

Every sentence earns its place: purpose, output contents, usage trigger, no-send guarantee, cost, and parameter format. The most decision-relevant information is front-loaded, making the description efficient and easy to parse.

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?

Even though there is no output schema and no annotations, the description lists expected return values, explains the input format, and states the cost. For a single-parameter simulation tool, this is complete enough for an agent to call it 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 0%, but the description adds crucial encoding details—'base64-encoded signed or unsigned Solana transaction'—telling the agent exactly what to pass. This fully compensates for the bare schema, which only labels the field as 'Transaction Base64'.

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 opens with the intended outcome ('Find out whether your transaction will succeed') and precisely names the operation: simulate on mainnet, returning decoded errors, logs, compute units, and expected account changes. 'Never sends — simulation only' clearly distinguishes it from any actual submission tool among the siblings.

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?

It provides an explicit trigger: 'Use before submitting any unfamiliar or high-value transaction,' and clarifies that it only simulates, never sends. It doesn't name specific alternative sibling tools or state when not to use it, but the guidance is still clear and actionable.

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