riskoracle

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

With no annotations, the description must fully disclose behavioral traits, but it only states the core function. It doesn't mention whether the operation is read-only, what data sources are used, or any limitations, which is a significant 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, clear sentence with no redundant information. It is concise and front-loaded with the core purpose, though this brevity comes at the cost of missing necessary 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?

Without an output schema or annotations, the description should explain what the tool returns or how the comparison is presented. It also lacks context on how this tool fits with siblings, making it incomplete for reliable selection and 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 schema has 0% description coverage, so the description must compensate. It only implies that 'symbols' should contain 2+ entries, but gives no guidance on 'use_case' or the expected format, making it insufficient for constructing valid calls.

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 compares multiple stablecoins head-to-head, which is a specific verb+resource and distinguishes it from sibling tools that focus on individual metrics. However, it doesn't detail what aspects are compared, so it's not fully rich.

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 no guidance on when to use this tool versus alternatives like risk_assessment or peg_history. There is no mention of use cases, prerequisites, or exclusions, leaving the agent without decision support.

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 of behavioral disclosure. It does not state whether this is a read-only operation, what side effects it might have, or any permissions or rate limits. The phrase 'Cross-chain distribution, bridge risk' gives no behavioral information at all.

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 short, but it is under-specified rather than concise. It is a fragment rather than a meaningful sentence, and it does not earn its place because it provides minimal actionable information beyond the tool name.

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 output schema and no annotations, so the description needs to explain what the tool returns or how it behaves. It does not, leaving the agent with only a vague topic hint. This is incomplete for a data-retrieval tool, though the simple parameter schema provides some 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 single 'symbol' parameter is fully described in the schema ('Stablecoin symbol e.g. USDC, USDT'), so the description adds no additional semantic value. With 100% schema coverage, the baseline 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 'Cross-chain distribution, bridge risk' is a noun phrase with no verb, so it's unclear whether the tool retrieves, calculates, or lists data. It provides some topic indication but does not clearly state its function or distinguish it from sibling tools like 'supply_flow' or 'risk_assessment'.

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 no guidance on when to use this tool or when to choose an alternative. It only offers a vague topical phrase, so an agent cannot determine if it's appropriate for a given task or how it relates to sibling 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 are provided, so the description must carry the full burden of behavioral transparency. It only lists three data categories and does not disclose whether the operation is read-only, how errors are handled, or any side effects. For a data retrieval tool, this is a notable gap, though it does hint at the return content.

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 short, consisting of a noun phrase with three items. It is concise and non-redundant, but it lacks a proper sentence structure and reads more like a keyword list. It could be improved by adding a verb and context, so it is moderately concise but under-specified.

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 single-parameter tool with no output schema, the description sufficiently conveys the return categories (custody model, SIFI status, jurisdiction). It does not elaborate on response formatting, but that is not critical given the tool's simplicity. The absence of output schema is compensated by the explicit field list.

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 a clear description of the symbol parameter ('Stablecoin symbol e.g. USDC, USDT'). The tool description does not add additional meaning to the parameter but does not need to, as the schema already defines it well. 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 lists specific data categories (custody model, SIFI status, jurisdiction) which clearly indicate the tool provides these stablecoin-related attributes. It lacks an explicit verb like 'get' or 'retrieve', but the resource is evident. It implicitly distinguishes itself from siblings by focusing on custody and regulatory status.

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 offers no guidance on when to use this tool versus alternatives like risk_assessment or holder_data. There is no mention of scenarios, prerequisites, or exclusions. The only implied usage is passing a symbol, which is already explicit in the schema.

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 should carry the full burden of behavioral disclosure. It does not explicitly state whether the tool returns a simple list, time series, or any side effects. The read-only nature is implied by the mention of distribution but not clearly disclosed.

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 short and has no redundant words, which is concise. However, it is a noun phrase rather than a complete sentence, lacking a subject-verb structure. It is front-loaded but under-specified, so it does not fully earn its place as a standalone description.

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 only one parameter and no output schema, the description should explain what the return value looks like. 'Top holder distribution, whale concentration' is a high-level topic but does not specify whether the tool returns a list of addresses, percentages, or other details. The lack of output schema and richer description leaves the agent with insufficient context to anticipate the result format.

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 fully describes the 'symbol' parameter with an example ('USDC, USDT'), and the description adds the context that the data concerns holder distribution for that symbol. However, it does not provide additional detail about how the symbol maps to output or any special formatting, so the baseline 3 applies.

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 'Top holder distribution, whale concentration' clearly indicates the tool provides holder distribution and whale concentration data for a given symbol, which distinguishes it from sibling tools like peg_history or supply_flow. However, it lacks an explicit verb such as 'get' or 'retrieve', making it more of a label than a full action 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?

There is no guidance on when to use this tool versus alternatives. The description does not mention use cases, prerequisites, or conditions for choosing this tool over siblings like risk_assessment or leaderboard. It simply names the data topics without any contextual advice.

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 of disclosure. It only mentions the ranking order (by risk score) but does not disclose whether it is a read-only operation, how pagination works, what the response structure looks like, or any rate-limiting behavior. This is minimal and under-specified.

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, concise phrase with no filler words. It is front-loaded and every word contributes to its meaning, making it exemplary in terms of spatial economy.

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 lack of output schema and annotations, the description should explain what the returned data looks like and how the ranking is structured. It does not. The tool is simple, but the description is too thin to give an agent enough context to interpret results or handle edge cases.

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 one parameter 'limit' with 0% schema description coverage, and the tool description does not mention or explain it at all. The description fails to add any meaning to the parameter, leaving the agent to guess its purpose and effect.

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 the resource (stablecoins) and the purpose (ranked by risk score), which clearly indicates the tool returns a ranking. While it lacks an explicit verb like 'list' or 'get', the noun phrase is informative and distinguishes it from sibling tools such as peg_status or supply_flow.

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 obtaining a risk-based ranking but gives no guidance on when to use this instead of alternatives like 'compare' or 'risk_assessment'. No exclusions, prerequisites, or contextual cues are provided.

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 given, and the description contains no behavioral details. It does not disclose whether the tool reads, mutates, returns static data, or has any side effects, permissions, or rate 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 a three-word fragment, not a complete sentence. While very brief, it is under-specified and provides no structure, making it an example of under-specification rather than effective 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?

With no output schema and no annotations, the description must carry full context. It fails to state what the tool returns, how it operates, or what the methodology entails, making it wholly inadequate even for a no-parameter 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 input schema has zero parameters, so there are no parameter semantics to explain. According to the 0-params baseline, the schema is complete and the description does not need to add parameter 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 'Risk scoring methodology' names a concept but doesn't specify an action or resource. It distinguishes from siblings only by the phrase 'risk scoring,' yet the tool name 'methodology' makes the description largely a restatement with no clear verb or outcome.

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 siblings like 'risk_assessment' or 'compare.' There is no mention of alternatives, prerequisites, or exclusions.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It only states '30-day peg history' and does not disclose what data is returned (e.g., timestamps, price deviations, methodology), whether it is read-only, or any other behavioral traits. The agent must rely on the parameter schema and assumptions.

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 at four words, but this is under-specification rather than deliberate conciseness. It does not waste words but also fails to provide necessary context, making it minimally acceptable.

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 a single parameter and no output schema, but the description is too sparse to be complete. It does not explain what 'history' means (e.g., price data, deviation metrics), the time horizon beyond '30-day', or any expected output format. Given the availability of sibling tools, more context is needed.

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, with the 'symbol' description explicitly stating 'Stablecoin symbol e.g. USDC, USDT'. The tool description adds no additional parameter meaning beyond this, so the baseline 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 '30-day peg history' identifies the resource as historical peg data over a 30-day window, which distinguishes it from sibling tools like peg_status. However, it lacks an explicit verb (e.g., 'Get' or 'Retrieve') and is terse, making it somewhat vague about what exactly is returned.

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 such as peg_status or risk_assessment. The description does not mention exclusions, prerequisites, or compare-and-contrast with sibling tools, leaving the agent to infer usage from the name alone.

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 does state that the tool returns deviation and stability, indicating it is a read-only status check. However, it does not disclose any potential limitations, rate limits, or data freshness details, which for a 'current' status tool would be useful context. No contradictions exist.

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 exceptionally concise, using only six words to convey the tool's purpose and core outputs. It is front-loaded and contains no filler, perfectly sized for a simple status query tool.

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 is minimally adequate. It mentions the return concepts (deviation, stability) but omits details like exact format, units, or whether the status is time-bound. Given the simplicity, a score of 3 reflects that it works but leaves 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 schema already fully documents the single parameter 'symbol' with a clear example (USDC, USDT), covering 100% of parameter meaning. The description adds no additional parameter semantics, but the schema suffices, 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 identifies the resource (current peg status) and specifies the key aspects returned (deviation, stability), distinguishing it from sibling peg_history which focuses on historical data. However, it lacks an explicit verb like 'get' or 'retrieve', making it slightly less direct.

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. For example, there is no mention that peg_status is for current snapshots while peg_history covers trends, nor any other usage context. The user must infer applicability from the tool name alone.

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. 'Server ping' implies a simple read-only connectivity check, but it does not describe the response format, potential errors, or any side effects. For a trivial tool this is adequate but still minimal.

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 words and perfectly front-loaded. Every word earns its place, with zero 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?

Given the extremely low complexity and absence of schema or output schema, 'Server ping' is a complete description. It fully captures the tool's function for a standard health check, making further detail unnecessary.

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

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

The tool has zero parameters, so the baseline is 4. The description does not need to elaborate on parameter semantics because there are none.

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 'Server ping' clearly identifies the tool as a health check for server connectivity using the standard ping metaphor. It is specific enough to distinguish it from sibling tools that perform data-related queries, such as holder_data or custody_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?

No usage guidance is provided. The description does not state when to use this tool versus alternatives, nor does it mention any prerequisites or context. Although the purpose is self-evident, the description offers no explicit guidance on usage scenarios.

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 fully disclose behavioral traits. It only lists 'track record, latency, limits' without explaining whether the tool is read-only, what side effects exist, or what exactly the returned data represents. This is insufficient for responsible invocation.

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 but at the expense of clarity. It is under-specified, offering only a fragment rather than a coherent statement of function, similar to the 'Process' example.

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 there is no output schema or annotations, the description needs to explain return structure and any caveats. It lists three data dimensions but doesn't describe their format, granularity, or how they relate, leaving the agent with insufficient information to predict the tool's response.

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 fully describes the 'symbol' parameter with examples (USDC, USDT), achieving 100% coverage. The description adds no additional semantics, so the baseline 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 is a noun phrase ('Redemption track record, latency, limits') with no verb, making it unclear what action the tool performs. It vaguely suggests the tool provides redemption-related data but doesn't specify a clear resource or operation, and it doesn't articulate how it differs from siblings like peg_history or supply_flow.

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 offers no guidance on when to use this tool versus alternatives. There are no contextual clues, prerequisites, or references to sibling tools, leaving the agent without direction 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?

With no annotations, the description carries the burden of explaining behavior. It does add useful context: the score is based on 7 signals, uses a 100-point scale, and returns a SAFE/CAUTION/AVOID classification. However, it doesn't disclose whether the tool is read-only, what data sources are used, or any side effects or limitations.

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, tightly packed line that immediately conveys the core output, scale, and risk categories. Every word adds value, and it is front-loaded with the key concept 'Full risk score'.

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 there is no output schema and no annotations, the description should explain what the tool returns and how to use it. It does mention the output scale and categories, but it omits essential context: what the 7 signals are, how chain and use_case affect the score, and whether the result includes a numeric score plus label. This is sufficient to begin a call but leaves 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?

The input schema has 0% description coverage, and the description provides no meaning for the parameters (chain, symbol, use_case). The mention of '7 signals' is unrelated to the parameter names. The description fails to compensate for the schema's complete lack of 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 identifies the tool as producing a full risk score with a specific scale (100-point) and output categories (SAFE/CAUTION/AVOID). It distinguishes itself from sibling tools like peg_status or supply_flow by emphasizing 'full risk score' and '7 signals', though it lacks an explicit verb like 'calculate' or 'return'.

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 guidance is given on when to use this tool vs. alternatives. Sibling tools exist (e.g., methodology, compare, peg_status), but the description does not mention them or explain which situations call for risk_assessment instead.

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 must disclose behavioral traits on its own. It reveals the topic (minting/burning, net flow) but says nothing about whether the tool is read-only, what data is returned, or any limitations or side effects. This is insufficient for a data query 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 very short and front-loaded, but it is a fragment rather than a complete sentence. While there is no waste, the brevity comes at the cost of clarity—key details like the verb and object are missing.

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 single parameter and no output schema, the description should explain what the tool returns (e.g., values, time series, units) and in what context to use it. The current description is too vague to prepare an agent 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?

Schema description coverage is 100% for the only parameter (symbol), so a baseline of 3 is appropriate. The tool description adds nothing beyond the schema; it does not clarify how symbol relates to the output or any expected format or 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 names the resource (supply minting/burning, net flow) but lacks a clear verb like 'fetch' or 'list.' The meaning is inferable but ambiguous—does it return current values, historical series, or aggregations? It partially distinguishes from siblings by focusing on supply dynamics, but not definitively.

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 on when to use this tool versus alternatives such as peg_status or redemption_data. The description does not mention excluded cases, prerequisites, or preferred contexts, leaving the agent without decision support.

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. 'List' implies a read-only operation, but it does not disclose any behavioral details such as whether results are paginated, ordered, or what 'supported' means in terms of chain or network. This is minimal disclosure beyond the basic action.

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, front-loaded sentence communicates exactly what the tool does with no wasted words. This is appropriately concise for a zero-parameter list tool.

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, zero-parameter list tool, the description is essentially complete. It does not explain return values or output format, but given the lack of output schema, that is not strictly required. A slightly richer context about the relationship to price/data tools could push it higher.

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

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

The tool has zero parameters, so the baseline is 4. No parameter explanations are needed, and the description does not attempt to invent them.

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 'List supported stablecoins' uses a specific verb and resource, clearly identifying the tool's function. It is distinct from sibling tools like peg_status or risk_assessment, though it does not explicitly reference 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?

The usage is implied by the name and description: use this tool when you need the list of supported stablecoins. However, it provides no explicit guidance on when to use this vs. alternatives, or any context about its role among the sibling tools.

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