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

With no annotations, the description fully carries the burden. It explains noise filtering criteria (avg_tx_usd < $0.02 and high tx-per-buyer ratio), distinguishes verifiable (x402) vs self-reported data, and clarifies percentage and volume formats. It details each view's 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?

The description is lengthy but well-organized, front-loading the core purpose and then drilling into details. Every sentence adds information, though some redundancy could be trimmed. It remains clear and structured.

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, but the description explains what each view returns (e.g., 'hero KPIs', 'daily time series', 'top sellers') and covers noise filtering. It misses exact field names but provides sufficient context for a 4-param 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 100% with good descriptions. The description adds value by explaining the three views in more detail (e.g., 'hero KPIs + cross-protocol comparison table') and provides usage context, but much of the parameter meaning is already in the schema.

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

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

The description clearly states it provides 'Agent-economy payment metrics' from Barker's cross-protocol index, lists specific protocols (x402, Virtuals ACP, etc.), and details three views. It distinguishes from siblings (barker_defi_vaults, barker_market_overview, barker_market_trend) by focusing on agent payments.

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 ('use for 'x402 volume', 'agent payment stats'...') that imply typical use cases, but lacks explicit guidance on when to avoid this tool or mention alternatives. The sibling context helps differentiate, but the description itself doesn't fully guide usage.

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?

Explains the output format, including that supply_apy_total is a decimal to multiply by 100 for percentage. No annotations provided, so description carries full burden; it adds useful behavioral context beyond a simple query description.

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 efficiently convey purpose, output fields, and usage examples. No redundant information; every part 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 output schema, the description explains all return fields. It mentions the index size and provides query examples. Slight gaps (data freshness, pagination) but acceptable for a simple query 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 covers all parameters with descriptions. The description mentions default sort 'apy' (already in schema) and provides example queries, but does not add new meaning to parameters. 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 queries real-time stablecoin supply yield pools from 500+ protocols, with specific output fields. It naturally distinguishes from sibling tools (market overview, trend, payment stats) by focusing on DeFi yield 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?

Explicitly lists example use cases like 'best stablecoin yield' and 'compare lending rates', providing clear context. No exclusion or when-not-to-use, but siblings are different tools, so no confusion expected.

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; description implies a read-only snapshot but does not explicitly state it or disclose caching/authorization details. Adequate for a simple parameterless tool, but could be more transparent.

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

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

Two concise sentences: first defines purpose, second provides usage examples and a formatting note. No superfluous words, well-structured.

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 zero parameters, no output schema, and no annotations, the description sufficiently covers what the tool does, when to use it, and how to interpret results. No major gaps.

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

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

No parameters exist; description adds value by explaining output format (share_pct as decimals). Schema coverage is 100%, so baseline of 3 is met; extra clarity raises score.

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?

Clearly states 'Stablecoin market snapshot' and lists specific data points (total market cap, yield-bearing cap, asset/chain distribution). Distinct from siblings which cover vaults, trends, and payment stats.

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 queries ('stablecoin market cap', 'USDT market share', '稳定币市场份额') and notes decimal format for share_pct. No explicit exclusion of alternatives, but examples sufficiently guide usage.

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

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

With no annotations provided, the description must disclose all behavioral traits. It states the lookback range and that it returns a historical trend, which is adequate. However, it does not mention read-only nature, potential rate limits, or output format details, leaving gaps for an agent.

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 one sentence and example phrases. It efficiently conveys purpose and usage without extraneous text. Front-loading the main description and then examples works well.

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

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

Given the tool's simplicity (1 parameter, no output schema), the description covers purpose, parameter, and usage context. However, it omits what the output looks like (e.g., a time series, delta values), which is needed for an agent to process the result 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% (parameter 'days' with min/max and description). The description adds '7–180 days' which matches the schema. No additional meaning beyond the schema is provided, so a score of 3 is appropriate.

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

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

The description clearly states 'Historical APY trend for stablecoins vs. US Treasury benchmark over a lookback window', which differentiates it from sibling tools like barker_defi_vaults and barker_market_overview. However, it uses a noun phrase rather than an active verb, slightly reducing clarity.

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 examples ('DeFi vs treasury', 'is stablecoin APY going up') that help an agent understand when to invoke this tool. It does not mention when not to use it or list alternatives, which would have improved the score.

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