stablecoin-yield

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

No annotations provided, so description carries full burden. It only reveals a $0.01 cost per call via x402, but lacks disclosure of idempotency, side effects, or error handling. Minimal behavioral context.

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

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

The description is concise: one sentence plus a brief example and cost note. No redundancy, but slightly more structured formatting could improve readability.

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

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

For a simple tool with no output schema, the description covers purpose and cost but omits the output format (e.g., list of routes with details). Adequate but could be more complete.

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

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

Schema coverage is 100% with clear descriptions for symbol and from_chain. Description does not add extra meaning beyond the schema's 'lowercase' requirement, meeting the baseline.

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

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

The description clearly states it provides cross-chain route availability for a stablecoin from a given chain, with examples 'bridge USDC from arbitrum'. It distinguishes from siblings focusing on execution quotes or pools, but could more explicitly differentiate.

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 includes use cases like 'bridge USDC from arbitrum' and '跨链路径', implying when to use. However, it does not specify when not to use or mention alternatives like barker_execution_quote for actual quotes.

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 explicitly states the tool is paid ($0.001 per call) and returns real-time data. It describes the output format (ranked rows with specific fields) but does not discuss side effects or safety. The cost disclosure adds transparency beyond typical read-only hints.

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: first defines the tool and outputs, second provides examples. Every word earns its place. No fluff. Front-loads key information.

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

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

Given 4 parameters, no output schema, and moderate complexity, the description covers purpose, parameters, output fields, cost, and example queries. It lacks details on pagination or response structure, but the listed output fields compensate for the missing output schema. Overall complete enough for an agent.

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%, providing baseline. The description adds value by specifying lowercase format for asset and chain, default limit (50), and example values (usdt, usdc, etc.). It also clarifies the sort enum meaning (apy, tvl). These extras justify a score above baseline.

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

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

The description clearly states it queries real-time stablecoin supply yield pools from Barker's index, and lists specific output fields. It distinguishes from siblings by focusing on yield pools, not routes, quotes, or other tools. Example questions reinforce 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 provides example use cases ('best stablecoin yield', 'where to earn on USDC'), guiding when to use the tool. It does not explicitly state when not to use or list alternatives, but the sibling names provide implicit differentiation.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the call is paid ($0.01 via x402), mentions the returned fields (adapter support, is_full, APY, TVL), and clarifies the APY unit (decimal). It does not explicitly state side effects (it is read-only) or rate limits, but the cost disclosure and output details provide good transparency for a discovery 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 a single sentence with a front-loaded uppercase label, followed by details on returns and usage. It includes example queries and cost info without being overly verbose. Every part adds value, though it could be slightly more concise.

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

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

With no output schema, the description adequately explains what the tool returns (executable pools, adapter support, is_full, APY, TVL) and notes APY unit and cost. It covers the main use case and parameter behavior (default min_tvl, limit). Lacks details on error handling or pagination beyond the limit field, but sufficient for its discovery role.

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?

Input schema covers 100% of parameters with descriptions. The tool description adds no additional meaning beyond the schema fields; it only mentions output-related concepts like is_full and APY. Baseline is 3 due to full schema coverage, and no extra param semantics are provided.

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 clearly states the tool's purpose: discovering stablecoin vaults that support direct deposit/redeem via barker_execution_quote. It specifies the return includes executable pools, live deposit capacity, APY/TVL, and explicitly distinguishes it from the sibling tool barker_execution_quote by instructing to call this first. This meets the criteria of a specific verb+resource with 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 provides explicit usage guidance: 'Call this before barker_execution_quote' and notes that every pool listed here can be quoted. It also gives example queries in English and Chinese. However, it does not explicitly state when not to use this tool or mention alternative tools for other purposes, but the context is clear enough.

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

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

No annotations provided, so description carries full burden. It fully declares non-custodial nature (never broadcasts, never holds funds), asset identity resolution (pool resolves ambiguity, symbols rejected), and receiver constraint (vault shares always go to signer_address). No contradictions.

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?

Description is well-structured with bullet points and flow, but slightly verbose. Every sentence adds value, though could be trimmed slightly without losing clarity.

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

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

Given 5 parameters, no output schema, and no annotations, description fully covers purpose, flow, constraints, parameter meanings, and output shape (transaction_request, route, risk summary, approval info). Includes pricing and cross-chain caveats. Complete for an agent to invoke 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 coverage is 100%, and description adds valuable context beyond schema: explains that amount_base_units is integer in token decimals (1 USDC = 1000000), clarifies action defaults to deposit, and emphasizes that receiver is not a parameter. Every parameter gets extra explanation.

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 clearly states it buys an unsigned transaction to deposit/redeem from a stablecoin vault. It uses specific verbs ('buy', 'deposit', 'redeem') and distinguishes from sibling tools by outlining the flow (barker_yield_advisor → barker_executable_pools → this tool) and stating it never broadcasts.

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?

Provides explicit flow (barker_yield_advisor → barker_executable_pools → this tool → user signs), states when not to use (no symbols/token addresses, use self/portals adapters for cross-chain), and gives real-world examples in English and Chinese. Also mentions pricing ($0.05 per call via x402).

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?

Discloses it is a 'snapshot' (implying non-mutating) and includes pricing ('paid: $0.001 per call via x402'). Without annotations, this provides reasonable behavioral context. Could be improved by explicitly stating read-only nature.

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?

Description is two sentences plus examples; concise yet packs purpose, usage examples, decimal formatting note, and pricing. Every sentence adds value, no fluff.

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 tool with no output schema, the description covers output content (market cap, distribution), note on decimal formatting, and pricing. It is complete for an AI agent to understand what the tool returns and when to use 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?

No parameters exist (empty input schema), so the description does not need to add parameter information. The 100% schema coverage means schema and description are aligned. Baseline score of 4 is appropriate.

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

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

Description clearly states it provides a 'Stablecoin market snapshot' with specific breakdowns: total market cap, yield-bearing cap, asset distribution, chain distribution. This differentiates it from sibling tools like barker_crosschain_routes and barker_defi_vaults.

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?

Includes example use cases like 'stablecoin market cap', 'USDT market share', and '稳定币市场份额', guiding when to use this tool. However, it does not explicitly state when not to use it or mention 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?

No annotations provided, so description carries full burden. It discloses the tool is paid ($0.001 per call) and returns historical trend data, but lacks details on return format (e.g., time series vs aggregated) and any limits.

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

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

The description is concise with three short sentences: main purpose, example use cases, and pricing. It is front-loaded with the core functionality, though the pricing note could be considered secondary.

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 simple one-parameter tool and no output schema, the description provides adequate context for use but could be more complete by explaining the expected return structure (e.g., a series of data points).

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 covers the single parameter 'days' with range and default, and the tool description reiterates the range. Since schema coverage is 100%, the description adds minimal extra meaning, justifying a baseline score of 3.

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 historical APY trend for stablecoins vs. US Treasury benchmark over a lookback window, which is specific and distinguishes it from sibling tools like barker_market_overview (likely current overview).

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 explicit example use cases ('DeFi vs treasury', 'is stablecoin APY going up'), giving clear context for when to use the tool, though it does not explicitly mention when not to use 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?

No annotations are provided, so the description must carry the full burden. It mentions the cost ($0.005 per call) but does not explicitly state that it is a read-only operation, nor does it disclose side effects, permissions, or rate limits. The behavioral transparency is adequate but not comprehensive.

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 clear sentences plus a parenthetical cost note. It front-loads the tool's purpose and output, then provides usage guidance. Every sentence adds value with no wasted words.

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

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

Given no output schema, the description covers the key output components (APY components, TVL, terms, execution capability, reward breakdown) and mentions the input source. It is mostly complete for a single-pool detail tool, though it could specify data recency or format further.

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%, with the pool_uid description stating 'Pool uid from list tools.' The tool description reinforces this by saying 'by pool_uid' and 'use after...', but adds no deeper semantic meaning beyond what the schema provides. 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 clearly states the tool retrieves a full dossier for a single pool, listing specific components (APY, TVL, terms, execution capability, reward breakdown). It also explicitly distinguishes from sibling tools by indicating it is used after list tools to inspect one pool.

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

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

The description explicitly states when to use the tool: 'Use after barker_defi_vaults / barker_yield_advisor to inspect one pool.' This provides clear context and implies not to use it as a first step or for overviews.

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 provided, so description carries full burden. It discloses cost ($0.005 per call via x402) and unit (APY percent), but does not mention response format, pagination, rate limits, or error behaviors. Adequate but not thorough.

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 are concise and front-loaded with key information. The first sentence covers resource, action, default, unit, and purpose. Second sentence adds use case and cost. No wasted words.

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

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

Given 2 parameters, no output schema, and no annotations, the description covers core usage but lacks details on return format, data fields, or error handling. Adequate for a simple tool but leaves gaps for an AI agent.

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

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

Schema coverage is 0%, so description must compensate. It mentions pool_uid and implies days via 'default 30d', but does not detail acceptable formats or semantics of each parameter. The unit clarification adds value, but incomplete coverage warrants baseline 3.

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 per-pool APY/TVL time series for trend and volatility analysis of one pool_uid. It specifies default window (30d) and unit (APY percent), distinguishing it from sibling tools like barker_pool_detail or barker_market_trend.

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 example queries ('is this pool's APY stable' and Chinese equivalent) but does not explicitly state when not to use this tool or mention alternatives. It implies usage for stability analysis but lacks exclusion criteria.

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 provided, so description carries full burden. It mentions fuzzy search and a cost of $0.001 per call, but lacks details on rate limits, result format, or behavior on no match.

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 wasted words; purpose and pricing are front-loaded. Could add a bit more guidance without sacrificing 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?

Given no output schema and sibling tools, description is minimal. It omits response structure (list of results?) and explicit linkage to sibling tools, leaving gaps for a gateway search 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?

Schema coverage is 0%. Description explains 'keyword' as search term but does not describe 'limit' parameter, leaving its semantics unclear beyond schema min/max constraints.

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

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

The description clearly states the tool performs fuzzy search by keyword (protocol name, pool name, asset) and resolves natural-language references to pool_uid, distinct from sibling detail/history tools.

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

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

The description explains the tool resolves pool references for use in detail/history tools, implying when to use. However, it does not explicitly state when not to use or list alternative tools.

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

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

No annotations provided, so description carries full burden. Discloses it's a read operation, explains on-chain mechanics (balanceOf + convertToAssets), and warns that Barker does not store deposit baseline, requiring user to track principal. Missing rate limits or auth, but adequate for a 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?

Description is detailed but not verbose. Includes critical usage instructions, return values, and pricing. Could be slightly more concise by trimming the Chinese example if not globally needed, but overall well-structured and front-loaded with key 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?

No output schema, so description explains return values: shares and current_value in underlying asset. Covers use case, parameter sources, and pricing. Lacks error handling or edge cases, but for a simple read tool this is sufficient.

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

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

Schema coverage is 100% with descriptions for both parameters. The description adds value by explaining pool_uid's origin (from barker_executable_pools / barker_execution_quote) and clarifying the address parameter's role. This goes beyond the schema's minimal descriptions.

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

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

The description clearly states it reads the current redeemable value of an ERC-4626 vault position on-chain, using specific verbs like 'current redeemable value' and naming parameters (pool_uid, address). It distinguishes from siblings by focusing on vault positions versus pools or execution quotes.

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?

Provides explicit usage context: 'Use after depositing via barker_execution_quote to monitor a position.' Includes example queries in English and Chinese. Lacks explicit when-not-to-use or alternatives, but the sibling list and context make it clear this is for vault positions only.

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 provided, so the description carries the full burden. It discloses output: ranked recommendations with reasons and risk flags, APY unit, and cost per call. Does not mention read-only nature explicitly, but the verb 'Returns' and context imply no side effects. Would benefit from stating it's non-destructive.

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 paragraph of five sentences, front-loaded with the core purpose and query examples. It is concise but could be more structured (e.g., bullet points for cost, output details). Every sentence adds value; no wasted words.

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

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

Given the complexity (5 parameters, no output schema), the description covers the core function, usage examples, and cost. However, it lacks details on the exact structure of the returned recommendations (e.g., fields in each pick). With no output schema, a more explicit return format would improve completeness.

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

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

Schema coverage is 100%, so baseline is 3. The description adds minimal extra meaning beyond the schema (e.g., 'APY unit: percent' and that 'limit' controls top-N). Does not explain the meaning of 'risk' enums or 'asset' values beyond what schema already provides.

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

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

The description clearly states it answers 'Where should I park my stablecoins right now?' by returning a ranked top-N recommendation across 500+ protocols. It distinguishes itself from sibling tools (e.g., barker_pool_detail, barker_defi_vaults) by being a high-level yield advisor rather than a specific pool or vault tool.

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?

Provides example natural language queries like 'best place for my USDC' and 'recommend stablecoin yield with low risk', indicating when to use. Does not explicitly state when not to use or compare with alternatives, but the context from sibling names helps differentiate.

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