smartmoneyoracle

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

With no annotations, the description carries the full burden. It transparently lists the signal components and the output rating scale (COLD to EXPLOSIVE), which reveals the tool's analytical behavior. It does not discuss side effects, but as a scoring tool it is clearly read-only.

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

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

The description is a single, dense sentence that communicates the core purpose and output rating without filler. Every phrase contributes meaningful 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 simple tool with one parameter and no output schema, the description adequately conveys the purpose and expected rating scale. It might benefit from stating the output format more explicitly, but the essentials are present.

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 description already covers the parameter as 'Token name or symbol (required)'. The tool description adds no additional parameter semantics, such as format examples or case sensitivity, but the schema provides 100% coverage, 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 clearly states the tool computes a combined alpha score using specific components (momentum, volume surge, buy pressure, whale boost). It implicitly distinguishes from flow-focused siblings by focusing on a composite score, though it lacks a concrete verb like 'calculates' and does not explicitly name the asset class.

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 provided on when to use alpha_signal versus its sibling tools (e.g., flow_scan, top_whales). There are no contextual examples, exclusions, or mentions of 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?

With no annotations, the description carries full responsibility for behavioral disclosure. It implies a read-only view ('see') but does not describe the output format (e.g., list of chains with TVL amounts, ordering, currency units) or any caveats about data freshness or chain coverage. This is insufficient for an agent to know what to expect.

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 concise sentences. The core subject ('Cross-chain capital allocation') is front-loaded, and the second sentence adds a plain-language explanation. Every word earns its place.

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

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

For a zero-parameter tool, the core function is stated. However, there is no output schema and the description does not explain what the returned data will look like (e.g., a chart, a table, specific metrics beyond TVL). It is minimally sufficient but leaves room for ambiguity about the output structure.

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 description has no parameter semantics to explain. The baseline of 4 is appropriate since there is nothing that needs clarification.

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

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

The description clearly states the tool's function: showing cross-chain capital allocation in terms of TVL per chain. It uses a specific verb ('see') and resource ('which chains hold how much TVL'), which is distinguishable from sibling tools like flow_scan or protocol_flows (which likely focus on flows rather than static allocation). However, it doesn't explicitly contrast with siblings.

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

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

No guidance is provided on when to use this tool versus alternatives. The description says 'See where the ecosystem money sits' but does not mention use cases, prerequisites, or exclusions. Given the sibling tools exist, the lack of differentiation leaves the agent without clear selection 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?

With no annotations provided, the description carries the full burden. It discloses what data is returned (current TVL, inflows/outflows, chain breakdown) which is useful, but does not mention data freshness, rate limits, or whether it's a read-only operation. It gives a basic behavioral outline without deeper 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 two short sentences, front-loaded with the key purpose, and every word adds value. No redundancy or filler.

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

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

For a simple tool with one parameter and no output schema, the description provides a reasonable overview of what the tool returns. It lacks specifics like example values or formatting, but is sufficiently complete for basic understanding given the tool's simplicity.

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

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

Schema description coverage is 100%, so the single parameter 'protocol' is already well-documented in the schema. The description does not add additional meaning about the parameter, but the schema suffices. 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 provides TVL flow analysis with specific data points (current TVL, 7-day inflow/outflow, chain breakdown). It is specific about the resource (protocol TVL) and the focus on capital movement, which helps distinguish it from sibling tools like chain_flows, though it doesn't explicitly differentiate from protocol_flows.

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 tracking capital movement ('Track where capital is moving') but provides no explicit guidance on when to use this tool versus alternatives like protocol_flows or chain_flows. No exclusions or prerequisites are mentioned.

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 is the sole source of behavioral disclosure. It implies a read-only check by mentioning health and connectivity, and it lists what it returns, but it does not state whether it is safe, what happens on failure, or any response format. Minimal disclosure beyond a simple list.

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

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

The description is extremely concise, consisting of four comma-separated items with no filler. It is front-loaded with the most important info (server health, API connectivity). However, it is so terse that it feels like a fragment, slightly under-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?

The tool has no parameters and no output schema, so the description is the only source of return-value context. It names key outputs (server health, API connectivity, tool list, pricing) but does not elaborate on their meaning or structure. Adequate for a simple health check, but with room for clarity.

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 covers everything. The description adds no parameter-specific detail because none are needed. Baseline 4 applies for zero-parameter tools.

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 lists information categories (server health, API connectivity, tool list, pricing) but lacks a clear verb indicating the action. It is somewhat specific and distinguishes itself from sibling tools focused on data flows, yet it reads more like a caption than a purpose statement.

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 on when to use this tool versus alternatives. The description gives no context about typical use cases, prerequisites, or exclusions. Sibling tool names hint at broader ecosystem, but the description itself offers no usage direction.

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 mentions the metrics tracked but does not explicitly state that the operation is read-only, describe response format, or disclose data sourcing/update behavior. This is a meaningful transparency gap.

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

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

The description is a single sentence that front-loads the verb 'Track' and then efficiently provides examples and metrics. Every word adds value with no repetition or 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 no output schema and no annotations, the description should explain what the agent will receive. It lists the metrics (TVL, changes, categories) but does not describe response structure or behaviors like filtering or sorting. It is minimally adequate but leaves 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?

The tool has zero parameters and an empty input schema, so there are no parameter details to clarify. The baseline of 4 applies because the description need not compensate for missing parameter documentation.

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 tracks institutional-grade protocols with specific examples (Lido, Aave, Maker, Ondo, BlackRock, Ethena) and metrics (TVL, 1d/7d changes, categories). This distinguishes it from sibling tools focused on flows or signals.

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

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

The description gives clear context for when to use the tool: when needing TVL and change metrics for institutional-grade protocols. However, it does not explicitly reference sibling tools or state exclusions, so agents must infer alternatives from the sibling list.

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 of behavioral disclosure. It only says 'right now' (real-time) and mentions filtering, but it omits what the response contains (e.g., list with TVL change percentages), the time window (24h, 7d), or any operational constraints. This leaves significant ambiguity 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 three short sentences, front-loaded with the core purpose and ending with the filter instruction. The second sentence, 'The smart money flow radar,' is somewhat marketing-flavored but not wasteful. Overall concise and well-structured, though not perfectly lean.

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 read-only tool with two optional parameters, the description is minimally viable: it conveys what it does and that it supports filtering. However, with no output schema and no annotations, it doesn't specify the response format or time period, which a complete description should at least hint at. It's adequate but not thorough.

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 schema already documents both parameters. The description adds examples like 'DEX, Lending' which are also present in the schema, providing no additional meaning beyond what's structurally already known. 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 shows 'top protocols gaining and losing TVL right now,' which is a specific verb+resource combination that distinguishes it from siblings like chain_flows (chain-level) and stablecoin_flows (stablecoin-level). The mention of filtering by category adds further specificity.

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

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

The description gives clear context: this is for protocol-level TVL flows, filterable by category like DEX and Lending. It implies when to use it versus chain or stablecoin tools, but it does not explicitly state alternatives or exclusions, so it falls 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?

No annotations are provided, so the description carries the full burden. It discloses the output content (supply, per-coin, chain distribution) but does not describe response format, update frequency, historical depth, or any limitations. For a data-retrieval tool, this leaves ambiguity about whether the result is a snapshot, time series, or list.

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, front-loaded with the core purpose ('Stablecoin supply tracking') and then details the key fields. Every word adds value; no fluff or redundant phrasing.

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 no parameters, the description lists the primary data categories but lacks specifics such as which coins/chains are included or whether the data is current/historical. It is adequate for a simple tool but not fully 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?

The tool has zero parameters and an empty schema, so there is no parameter ambiguity to clarify. Per the baseline for zero-parameter tools, the description does not need to add parameter details; it sufficiently conveys the expected data scope.

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 ('stablecoin supply') and lists the specific data dimensions provided (total supply, per-coin breakdown, chain distribution). While the verb 'tracking' is not an imperative like 'get' or 'list', the scope is unambiguous and distinguishes it from sibling flow-focused tools like chain_flows and protocol_flows.

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 'leading market indicator' implies a market-analysis context, but there is no explicit when-to-use guidance, no exclusions, and no mention of alternatives. The description does not contrast with sibling tools or explain when stablecoin supply data should be used over flow data.

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 bears the full burden. It does not disclose return format, limitations, data recency, or any side effects. The content categories are helpful but behavioral traits are largely absent.

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

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

The description is a single, front-loaded sentence that efficiently conveys the tool's scope and a filter option. No redundant words or filler.

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

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

For a simple tool with two parameters and no output schema, the description provides adequate context about what data is covered, but it lacks detail on how results are returned (e.g., ordering, metrics, or formatting). It's complete enough for basic understanding but leaves several usage questions unanswered.

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 both parameters (chain, limit) with descriptions, giving baseline 3. The description adds limited value—'Filter by chain' restates the parameter without enriching it, and no additional detail about limit or chain-specific behavior is 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?

The description clearly indicates the tool's subject (whale activity across DeFi) and lists specific content categories (top boosted tokens, community takeovers, CoinGecko trending). It is specific enough to differentiate from sibling tools like flow_scan or chain_flows, though it lacks a direct verb such as 'list' or 'get'.

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

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

There is no guidance on when to use this tool versus alternatives like alpha_signal or institutional. The only usage hint is 'Filter by chain,' but no explicit conditions or exclusions are given.

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