bobai

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

Annotations already establish readOnlyHint=true and destructiveHint=false. The description goes beyond this by disclosing methodology: 'Every id read, nothing extrapolated' and highlighting that some registrations may not even be readable. This adds honesty about scope and limitations without contradicting the annotations.

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

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

The description is a single, information-dense sentence that front-loads the core purpose. The enumerated metrics are each meaningful, and the closing methodological note earns its place. It is slightly stylized but not padded.

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 read-only, zero-parameter statistical tool, the description is sufficiently complete: it names the chain, the registry standard, the specific metrics, and the scope of the read. Without an output schema, it could theoretically describe the return shape more explicitly, but the listed counts give a strong expectation of what will be returned.

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?

With zero parameters and 100% schema description coverage, there is no parameter burden for the description to carry. Baseline 4 applies because no additional parameter-level meaning is needed.

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 as a registry census for ERC-8004 on BNB Smart Chain and enumerates the specific metrics it reports. This distinguishes it from sibling tools like find_agents_on_bnb_chain, which focus on locating agents rather than aggregating registry-level statistics.

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 makes the context unmistakable: this is the aggregate overview tool for the agent registry, listing counts such as registered agents, readable registrations, endpoint availability, responsiveness, and operators. It does not explicitly name alternatives or when-not-to-use, but the census framing is clear enough 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?

Annotations already declare readOnlyHint true, and the description reinforces this with 'Reads...'. It adds valuable behavioral context about the data source and meaning, especially that funded jobs represent real money while registrations are self-reported. It does not mention pagination, rete limits, or return caveats, but none are critical for this simple read 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 tight and well ordered: purpose first, then data dimensions, then the trust distinction, then usage. Every sentence earns its place and there is no filler or redundant explanation.

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 read-only tool with one optional parameter and no output schema, it is complete. It explains what data is returned ('jobs created, jobs funded, deliverables submitted, escrow released'), the two invocation options, and the meaning of the results. Nothing an agent needs to call it correctly 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?

The schema already covers the single optional parameter at 100% coverage, including 'Optional provider address (0x…). Omit for the whole-kernel summary.' The description repeats this idea and adds 'balance,' but does not add substantial new semantic detail beyond the schema. With high schema coverage, baseline 3 is appropriate.

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

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

The description opens with a specific statement of what the tool tells you ('Who has actually been hired and paid on BNB Smart Chain') and names the exact source ('ER C-8183 job escrow kernel') plus the data it reads: jobs created, funded, deliverables submitted, and escrow released. The 'registration is self-reported; a funded job is somebody else's money' line clearly separates it from census/registration-style 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?

It gives clear usage modes: pass an address for one provider's balance, or omit it for the whole-kernel summary. It also implies when this is more trustworthy than a registration-based tool, but it does not explicitly name siblings 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?

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds beyond that by revealing the data source (public audit log) and the verifiability guarantee (every entry verifiable on-chain), which is useful behavioral context for trust and expectations.

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 dense sentence, front-loaded with the core purpose and then specific data points. 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 no-parameter, read-only lookup tool, the description provides everything an agent needs: what outcome the tool proves, which exact data points will appear, and the source/verifiability context. No output schema exists, but the listed outputs largely compensate.

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?

There are zero parameters and schema coverage is 100%, so the description carries no parameter burden. The 0-param baseline of 4 applies, and the description appropriately avoids inventing parameter-like details.

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 resource (the buyback-and-burn activity audit log) and enumerates concrete outputs: last burn with BscScan tx, 7/30-day burn totals, and total bot runs. This clearly separates it from siblings like bobai_burned and bobai_tokenomics, which cover different or narrower 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?

Usage context is implied: an agent would call this when someone asks for burn activity, flywheel proof, or recent buyback-and-burn metrics. However, the description never explicitly states when to prefer this over bobai_burned or other related siblings, nor does it mention 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?

Annotations already carry readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context: the burn is permanent, executed by an autonomous 24/7 bot, and targets the dead/zero address. This clarifies the return value's significance and permanence beyond what annotations alone provide.

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 well-structured sentence delivers all essential meaning with zero waste. The phrasing is tight and directly informative, hitting the key facts (permanent burn, target address, autonomous bot) without 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 a parameterless tool with no output schema, the description is sufficiently complete: it tells the agent exactly what this metric represents and why it matters. Minor gap: it does not specify units (e.g., $BOBAI count vs USD value) or whether the total is updated in real time, but the phrase 'Total $BOBAI' strongly implies token count.

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?

With 0 parameters and 100% schema coverage (empty schema), there is nothing to document. The description explains what the value represents, effectively preempting any confusion about the meaning of the returned figure. This is a baseline-4 case for a parameterless tool.

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 is specific and transparent: states exact resource (total $BOBAI permanently burned) and mechanism (sent to dead/zero address by autonomous 24/7 buyback-and-burn bot). This clearly distinguishes it from sibling tools like bobai_circulating_supply or bobai_price, making the 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?

The description implies this is a read-only metric for checking cumulative burned amount, but does not explicitly state when to prefer it over sibling tools or mention any caveats (e.g., data freshness, chain, or whether this includes all burn events). It provides context but no explicit exclusion or alternative routing.

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 already declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds the useful formula context and the 'current' freshness, but it does not disclose other behavioral traits such as update latency, data source, or edge conditions. There is no contradiction with annotations.

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 efficient sentence thatfront-loads the metric name and uses a parenthetical to add the precise calculation. 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 no-parameter, read-only lookup tool, the description is largely self-sufficient: it names the metric and defines it. The only minor gap is the absence of an output schema and no explicit statement of return format, but the expected return value is obvious from the description.

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, so parameter documentation is not required and the baseline for zero-parameter tools is 4. The description sufficiently explains what the returned metric represents, so no additional parameter semantics are needed.

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 exact resource—current circulating $BOBAI supply—and defines it as total supply minus burned tokens. The lack of an explicit verb is minor, the query intent is unambiguous and the formula distinguishes it from related supply/burn tools.

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

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

No explicit when-to-use guidance or alternatives are given, so an agent must infer usage from the phrase 'Current circulating supply.' The definition implies a natural query context, but it does not tell the agent when to prefer this over bobai_tokenomics, bobai_token_info, or bobai_burned.

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 already mark the tool as read-only and non-destructive. The description adds meaningful behavioral detail: it reads from the chain, reports fee-on-transfer settings, specifies a 3% tax and minimum 15% slippage, and warns that a naive swap reverts without this data. This goes beyond the annotations without contradicting them.

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

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

The description is two sentences with no wasted words. It front-loads the purpose, enumerates the key content, and ends with a functional warning that justifies the tool's existence. Every sentence 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?

With no input schema properties and no output schema, the description carries the full burden of explaining what the agent will receive and why it matters. It lists the critical fields, the fee-on-transfer behavior, and the consequence of skipping this tool. This is complete for a zero-parameter read-only info 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 and the schema coverage is 100%, so no parameter documentation is needed. The description focuses on what the tool returns rather than inputs, which is appropriate for a no-input info tool. Baseline 4 applies 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 purpose: to report the DEX parameters needed for a $BOBAI trade, including router, pair, swap paths, and fee-on-transfer settings. It is specific about what is read and reported, and the mention of a naive swap reverting distinguishes it from general price or liquidity 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?

It gives clear context that this is the tool to use before executing a $BOBAI trade, since a naive swap without these parameters reverts. It does not explicitly name alternative tools or exclusion criteria, but the usage context is unambiguous enough for an agent to choose it over siblings like bobai_price or bobai_liquidity.

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 already declare the tool read-only and non-destructive, so the safety burden is covered. The description adds valuable behavioral context: it is interactive, surveys askable/doable actions, routes to the right tool, and warns about the fee-on-transfer rule.

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?

A single sentence that front-loads the critical 'START HERE' cue and packs in scope, tool-routing value, and the fee-on-transfer caveat without wasted words. Excellent structure for an entry-point guide.

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, read-only routing guide, the description delivers everything needed: when to start, what the guide covers, and the must-know fee-on-transfer rule. No output schema or parameter details are required, and annotations cover the safety profile.

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 empty schema is fully documented, so there are no parameter semantics for the description to clarify. Baseline 4 applies because the description has no additional burden 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 opens with 'START HERE' and clearly states the resource ($BOBAI) and purpose: an interactive guide covering what you can ask, what you can do, and which tool to call for each. This also differentiates it from sibling tools by positioning it as a meta/routing guide rather than a specific data lookup.

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' and 'for an agent that just discovered $BOBAI' gives explicit context for when to invoke this tool. It doesn't list exclusions or alternatives explicitly, but it clearly signals this is the entry point for tool selection among the 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful context by listing exactly what kind of links and resources will be surfaced, including a live burn audit log, which helps the agent predict the output.

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?

A single, dense sentence with no fluff. The official-link framing is front-loaded and every listed item adds specificity.

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, read-only link tool, the description is sufficiently complete to guide invocation and interpret results. The only minor gap is that 'llms.txt' is not explained, but it is a recognized artifact and the overall coverage is strong.

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 fully covers parameter expectations. The description appropriately focuses on output content rather than parameters, which is exactly what the agent needs.

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 as 'Official $BOBAI links' and enumerates specific content (website, BscScan contract, X, Telegram, etc.), making it easy to distinguish from sibling data-focused tools. It lacks an action verb like 'retrieve' or 'return', 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?

The description implies this tool is for fetching official BOBAI-related URLs and resources, but it does not explicitly state when to use it versus siblings like bobai_purchase_guide or bobai_token_info. There is no exclusion or routing guidance, so the agent must infer the appropriate use case.

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 already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds context like 'Live' and 'perma-locked' but does not disclose details such as data source, update frequency, or calculation methodology for price-impact estimates. This is acceptable given the safety annotations but adds only modest behavioral context beyond them.

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, well-structured sentence that leads with the core purpose ('Live $BOBAI liquidity depth') followed by a compact list of deliverables. Every listed element adds value, and there is no redundant or filler text.

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 parameterless, read-only tool with no output schema, the description covers the essential information an agent needs: what data is available. Minor aspects like which DEX pool is queried or how 'live' is guaranteed are absent, but these are not critical for invoking 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?

The tool accepts no parameters, and the baseline for zero-parameter tools is 4. The description still helps by listing what output areas the tool covers, which indirectly informs the agent what to expect despite having no input schema to elaborate on. No parameter documentation is needed 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 names a specific resource (BOBAI liquidity depth) and enumerates concrete data points it provides: pool reserves, USD liquidity, LP-burned percentage, and price-impact estimates. This clearly distinguishes it from siblings like bobai_price or bobai_burned by emphasizing depth and impact rather than simple price or burn totals.

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: an agent can infer this tool should be used when liquidity depth, pool reserves, or price-impact information is requested. However, it does not explicitly state when not to use it or mention any alternative tools, even though closely related siblings exist such as bobai_dex_info and bobai_burned.

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 already indicate readOnlyHint=true and destructiveHint=false, so the safe read-only nature is established. The description adds meaningful behavioral context beyond annotations: the NFT is auto-minted with no claim/signup, the supply is capped, and the tool reports live remaining supply by tier and rarity. This gives the agent a clear picture of the operation's semantics without contradicting the annotations.

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

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

The description is two sentences with no fluff. The first sentence establishes what the tool is about and the key earning condition; the second sentence states the concrete information provided. All details—threshold, auto-mint, no claim, capped supply, live data, steps—are packed efficiently and 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 zero-parameter, read-only informational tool, the description covers the essentials: what the reward is, the qualifying condition, and what the tool returns (live remaining supply per tier/rarity and exact earning steps). It does not enumerate all tiers or rarity names, but that level of detail is not necessary for invocation. The absence of an output schema makes the return summary in the description particularly valuable.

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 takes zero parameters and the schema has no properties, so there are no parameter semantics to document. The description's mention of buy-tier and rarity relates to the output content, not input parameters, which is appropriate here. Based on the 0-parameter baseline, the description adequately handles this dimension.

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 subject: an on-chain NFT reward tied to $BOBAI purchases, with a specific threshold ($100 single swap), auto-minting behavior, and the information it provides (remaining supply per tier/rarity and earning steps). Although there is no explicit verb like 'get', the description is specific enough to distinguish it from all sibling tools, including bobai_purchase_guide and bobai_activity.

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 context is implied: an agent interested in the NFT drop, its remaining supply, or the steps to earn one would use this tool. However, there is no explicit when-to-use or when-not-to-use guidance, and no sibling tools are named as alternatives. The description does not help disambiguate against similar bobai-related informational tools beyond the NFT-specific subject matter.

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 already mark the tool as read-only and non-destructive, so the bar is lower. The description adds meaningful behavioral context by disclosing the exact on-chain sources (PancakeSwap V2 reserves × Chainlink feed) and the absence of any off-chain price API. This goes beyond the safety annotations and gives the agent confidence in the data provenance.

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

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

The description is a single, information-dense sentence. It front-loads the core result (price and market cap) and then supplies the computation method and trust rationale. Every clause earns its place with 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?

Given the absence of parameters and output schema, the description covers the essential return values (USD price, BNB price, market cap) and the computation sources. It doesn't specify the exact output format or units, but for a simple read-only price tool this is a minor gap. The description is largely sufficient for an agent 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?

The tool has zero parameters and the schema coverage is effectively complete, so there are no parameter semantics to explain. With no params, a baseline of 4 is appropriate, and the description adds relevant context about what the output contains. The description does not need to compensate for any schema gaps.

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 function: providing the live $BOBAI price in USD and BNB plus market cap. It identifies the exact resource and computation method, which distinguishes it from sibling tools like bobai_dex_info or bobai_token_info. No ambiguity remains about 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 implies usage for getting current price and market cap data, emphasizing the on-chain trust model. However, it does not explicitly state when to use this tool over alternatives or mention any exclusions. An agent can infer the main use case, but direct routing guidance is absent.

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?

Beyond the readOnlyHint annotation, the description explicitly states it returns text, holds no key, and moves nothing—eliminating any risk that an agent might expect an executed on-chain transaction. This is especially valuable given the purchase-oriented name and adds meaningful behavioral context beyond annotations.

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

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

Two sentences with no redundancy: the first states the core deliverable, the second enumerates outputs and safety. Every word contributes value, 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 no-input tool with no output schema, the description is complete: it specifies the deliverable (viem code), what will be reported (quote, slippage floor, fee-on-transfer method name), and the response format (text), plus the read-only safety profile. Nothing else is needed 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?

The tool has zero parameters and an empty schema, so there is no semantic burden on the description. The 'zero-shot' remark reinforces that no additional input or configuration is expected, which aligns perfectly with the schema's coverage.

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 and resource: provides ready-to-run viem code for a $BOBAI purchase with BNB on PancakeSwap V2. This clearly distinguishes it from siblings like bobai_price (price data) or bobai_guide (general guide), leaving no ambiguity about its purpose.

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 strong usage context: an agent that needs to execute a $BOBAI purchase can use this tool and get 'everything it needs zero-shot.' It does not explicitly name sibling alternatives or state when not to use it, but the purchase-specific focus is clear enough for correct selection.

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 already mark readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context: 'Live', 'auto-tracked', 'immutable on-chain ledger', and 'All verifiable, no API key', which go beyond the annotations and tell the agent about freshness, provenance, and access requirements.

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 dense but well-structured, with the core purpose front-loaded ('Live smart-money signals for $BOBAI') followed by clearly separated data categories. Every clause adds a distinct signal type or timeframe, so there is little filler even though the sentence is long.

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 present, the description carries the burden of explaining what the tool returns. It covers concrete metrics and timeframes: 24h/7d in/outflows, top movers with tx, 1d/7d/30d holdings trends, and $100+ buy ledger entries. It is complete enough for an agent to know what to expect, though exact response formatting is not specified.

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 schema description coverage is 100%, so there are no parameter meanings left to document. The description appropriately focuses on the data the tool returns rather than input 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 states that the tool provides live smart-money signals for $BOBAI and enumerates the signal categories: tax reserve/buyback pressure, whale flows and holdings, recent $100+ buys, and burn momentum. It is specific to the token and its content, though it does not explicitly differentiate itself from related siblings like bobai_price or bobai_burned.

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 about when to use this tool versus the many sibling tools. The description implies usefulness for whale/smart-money tracking but never states explicit alternatives, exclusions, or a decision rule for selection.

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 already communicate the safe read-only nature of the tool. The description adds useful context about the token being verified and renounced, but it does not disclose data freshness, caching, or how the burned amount is computed; with the annotation safety profile covered, this is adequate but not rich.

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 dense sentence packs the resource, chain, contract status, and a full field list with no filler. The important token identity is front-loaded before the details.

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 no-parameter read-only tool, the description provides enough information to anticipate the returned metadata in the absence of an output schema. It could further clarify the precise output shape or point to more specialized siblings, but nothing critical is missing for basic invocation.

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

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

The tool has zero parameters, so the schema imposes no selection burden; the baseline for 0 params is 4. The description reinforces that no input is needed and enumerates the token fields the agent can expect in the result.

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 as returning on-chain metadata for $BOBAI (contract, name, symbol, decimals, supplies, burned amount) and adds helpful context that it is a verified, renounced BEP-20 token. It does not explicitly contrast itself with siblings like bobai_burned or bobai_circulating_supply, so it misses some 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?

No guidance is given about when to choose this tool over the many specialized siblings (bobai_burned, bobai_circulating_supply, bobai_price, etc.). An agent must infer that this is the broad token-info option, and the description never states exclusions or 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 already declare readOnlyHint=true and destructiveHint=false, and the description adds meaningful framing beyond that: it is 'neutral, verifiable,' informational, and explicitly not an endorsement. It also reveals the kind of content the tool returns by listing tax->buyback->burn, renounced contract, burned LP, and fair launch. No contradiction with annotations is present.

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

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

The description is two sentences with no filler. The first sentence leads with the core purpose and concrete token mechanics, and the second sentence adds a valuable boundary ('NOT a buy recommendation'). 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 parameterless, read-only informational tool, the description is complete: it states what is covered, the key topics, and an important disclaimer. There is no output schema, but 'describes how the token works' sufficiently tells an agent what kind of response to expect.

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 is empty with zero parameters, so there are no parameter semantics to document. The description still compensates by explaining the subject matter and scope, which is sufficient for a parameterless informational tool.

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 resource ($BOBAI) and a specific function: describing the token's neutral, verifiable value-accrual mechanics. It details the exact scope — deflationary tax->buyback->burn design and trust properties — and explicitly says it 'describes how the token works,' not a buy recommendation. This clearly differentiates it from siblings like bobai_price or bobai_purchase_guide.

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 the tool: when an agent needs the token's mechanics, design, and trust properties rather than a price or a recommendation. It explicitly states what it is NOT (a buy recommendation), which is a useful exclusion. However, it does not name alternative sibling tools or give explicit when-to-use vs. when-not-to-use conditions, so it stops short of full routing 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?

Annotations already communicate readOnlyHint=true and destructiveHint=false, so the description does not need to state that this is a safe read operation. It adds scoping context ('any BSC wallet address' and two token types) but does not reveal return format, units, or error behavior. This is adequate but not rich.

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 short, front-loaded sentence carries all essential information. There is no fluff, repetition, or 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 single-parameter, read-only balance lookup, the description plus schema are largely sufficient. The lack of an output schema means the agent must infer the exact response shape, but the description does state what will be returned (BNB and $BOBAI balance), which covers the primary expectation.

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 only parameter, 'address', with its format ('0x + 40 hex chars'), so description-level parameter guidance is unnecessary. The tool description adds only the notion of 'any' address, which slightly reinforces that no specific wallet ownership 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 identifies the resource (balances) and the scope (any BSC wallet address), making the purpose easy to grasp. It lacks an explicit verb like 'get' or 'query', but the phrasing is unambiguous and distinct from sibling tools focused on supply, price, liquidity, or NFT 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 'any BSC wallet address' implies that this tool is appropriate for checking balances of arbitrary addresses, which is useful usage context. However, it does not explicitly contrast with sibling tools or state when not to use it, leaving some routing inference to the 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?

Beyond the readOnlyHint/destructiveHint annotations, the description discloses meaningful behavior: it reads live from chain, measures transfer tax from executed trades rather than labels, performs a sell simulation on the router from a fresh address, and is uncached with no API key. These are real behavioral traits an agent would otherwise not know.

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 long but front-loaded with the core purpose and every clause earns its place by naming a distinct output or supported protocol. The main sentence is dense and list-heavy, which loses a little readability, but it is not padded or repetitive.

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 complex tool with no output schema, the description covers what the tool returns (cost per size, depth, tax, LP ownership/burn, sellability, four.meme curve fields), which protocols it works on, and its operational caveats. An agent has enough context to select and invoke it correctly and to interpret the result shape.

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 single address parameter is already fully documented in the schema (token address, pool/pair, or explorer/link). The description adds value by broadening the contract to 'ANY token or pool' and explicitly covering the no-pool-yet four.meme case, but most parameter meaning still comes from 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 opens with a specific verb and resource: 'Measure what a trade on BNB Smart Chain would actually cost, for ANY token or pool — before placing it.' It enumerates the concrete outputs (price impact, swap fee, transfer tax, 1% depth, LP status, sell simulation), making it clearly distinct from sibling token-info, route, and census tools even though it never names 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?

It states a clear invocation context: use it before placing a trade to learn real cost, and it notes a fallback case for four.meme tokens with no pool. It does not, however, explicitly name when-not-to-use conditions or compare itself with siblings such as pancakeswap_best_route or bobai_dex_info, so it stops short of full alternative routing.

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 already mark this as readOnly and non-destructive, so the description's added value is its live behavior: it contacts ERC-8004 agents, checks whether they actually answer, and matches against the tools they return and their on-chain descriptions. It also sets expectations by rejecting self-reported categories and curated lists, which helps the agent interpret results.

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 opens with the core purpose and then adds methodology, expectations, and usage guidance in four short sentences. Each clause carries distinct 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 low-complexity read-only search with one required and one optional parameter, the description gives enough context to select and invoke the tool correctly: what it searches, how it verifies, and when to use it. No output schema exists, but the return behavior is implied by the purpose and the annotations cover the safety profile, so there is no material gap.

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 100% of parameters, including query examples and the 'speaks' protocol constraint, so the baseline is 3. The description's phrase 'can do a given thing' mirrors the query parameter without adding syntax, formats, or validation 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 first sentence states a specific action ('find') and resource ('AI agents on BNB Smart Chain that can do a given thing'), making the core purpose unambiguous. The second and third sentences sharpen the definition by describing the live-verification method and explicitly distinguishing this search from self-reported or curated lists, which separates it from related agent tools like bnb_agent_census and bnb_agent_employment.

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 last sentence provides explicit placement guidance: use this tool before assuming no agent exists for a task. It does not name sibling tools to use instead or state exclusions, so it falls just short of an explicit when/when-not/alternatives rule.

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 readOnlyHint=true and destructiveHint=false annotations present, the bar is lower, yet the description still adds substantial behavioral context: it explains that quoted prices come from the venue itself, that the transfer tax is applied between legs because it is taken outside the pool where quoters cannot see it, and that the tool cannot detect an owner who has not acted yet. These are genuine disclosures beyond the annotations, with no contradiction.

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 well-organized with FIRST/SECOND structure and front-loads the core purpose, but it is long and occasionally stylistic ('where no quoter can see it', 'and it says so') where plainer wording would do. Every sentence carries some information, yet the prose is denser than necessary for an AI agent to parse efficiently.

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?

There is no output schema, so the description carries the full burden of explaining return values, and it does: best route, cost of every other route, round-trip with and without tax, and required slippage. It also covers the tool's limitations and the two questions it answers, leaving an agent with a complete picture despite medium-high complexity and no structured output metadata.

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 of 3 applies. The description reinforces the meaning of 'usd' by referencing 'this size' and slippage at size, but it adds no parameter-specific syntax or format details beyond what the schema already documents. It is adequate, not additive.

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 verb and resource: it determines the best route for a PancakeSwap swap, selecting among up to five pools by actual quoted return at the given size rather than by depth. It also distinguishes itself from nearby siblings like pancakeswap_fee_tiers, pancakeswap_range_plan, and bsc_pool_scan by framing itself as the pre-signing route/slippage decision tool for a swap.

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 opening clause 'For an agent about to swap on PancakeSwap' gives a clear trigger condition, and the closing warning 'It is not a safety certificate' tells the agent when not to rely on it. It does not name specific sibling alternatives to use instead, but the context is strong enough that the intended placement is unambiguous.

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 already mark this as read-only and non-destructive, and the description adds substantial behavioral context: the measurement window is about forty minutes, values are not annualized, two ranking denominators are used, in-range capital is reconstructed from the tick book, and tiers with no trades are also reported. This is far beyond what the annotations convey.

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 long but every sentence carries essential information about methodology, denominators, window, and output. It is front-loaded with the intended use case and avoids fluff. The complexity of the tool justifies the length.

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 carries the burden of explaining what the agent will get: swaps, turnover, fees paid, fees per $1,000 of capital under two denominators, both rankings, and non-trading tiers. It also discloses the time window and measurement style, making the tool's behavior sufficiently clear for correct invocation and interpretation.

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% and the only parameter, address, is already documented as accepting a BSC token address or a PancakeSwap pool address to pin the pair. The description does not add additional parameter-level detail or syntax guidance beyond this, so the 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 states a specific purpose: measuring PancakeSwap fee tiers to help a liquidity provider decide where to put liquidity. It specifies the resource (PancakeSwap pools at V2 0.25% and V3 fee tiers) and clearly differentiates from sibling tools by focusing on actual fees paid vs simple TVL rankings.

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 clearly frames when to use it: when a liquidity provider is deciding where to deploy capital across fee tiers. It gives strong context but does not explicitly name alternatives or exclusion conditions, such as 'use pancakeswap_range_plan for range selection instead', so it stops short of a 5.

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?

The description goes well beyond the readOnlyHint/destructiveHint annotations. It discloses the replay methodology, the use of actual V3 Swap events, the live forty-minute window, the per-width outputs, the absence of impermanent loss modeling, and the trade-off warning that IL is worst where fees are best. This gives the agent meaningful behavioral expectations without contradicting the annotations.

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 longer and more narrative than necessary for a two-parameter tool. The first sentence contains useful context but is padded with phrases like 'the decision concentrated liquidity actually forces.' Still, each sentence contributes substantive information about behavior, outputs, limitations, and the time window, so it is not wasteful enough to warrant a 2.

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 does a decent job conveying what the tool returns: fees per candidate width, in-range duration, and exit count. However, it never explains how candidate widths are specified or what exact set of widths is considered, which is a meaningful gap for an agent trying to interpret or request results. The temporal window and lack of IL modeling are covered, but the overall contract remains somewhat underspecified.

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 covers both parameters at 100%, so the baseline is 3. The description adds some context by tying 'stated size' to capitalUsd and mentioning pool/token address pining, but it does not explain parameter formats or defaults beyond what the schema states. The phrase 'per candidate width' introduces a concept not reflected in the schema, which slightly reduces clarity.

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 this tool helps a liquidity provider choose a PRICE RANGE for a PancakeSwap V3 pool by replaying real swaps and computing fees, in-range time, and exits. It distinguishes itself from modeling/forecasting tools by explicitly saying 'This does not model and does not forecast,' though it does not name a specific sibling 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 opening sentence gives a clear use case: a liquidity provider who has already picked a pool and now needs to decide on a price range. It also implicitly says when not to use it for forecasting or impermanent loss analysis. It does not explicitly compare to alternatives like pancakeswap_fee_tiers or pancakeswap_best_route, but the situational framing is reasonably clear.

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