VulnHunt Security Intelligence

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 does disclose one behavioral trait — that missing data is not conflated with unavailability — which is a genuinely useful semantic caveat. But permission needs, mutation/read status, and output behavior are unstated.

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 short, front-loaded sentence with no padding. Concise, though the brevity comes at the cost of substance rather than through efficient information density.

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?

An output schema exists, so return values need not be explained. However, for a comparison tool with a required GPU parameter, an optional provider filter, zero schema documentation, and no annotations, the description omits too much for an agent to call it correctly.

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

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

Schema description coverage is 0%: 'gpu' and 'providers' have no textual explanation in the schema. The description does not compensate — it never says what 'gpu' accepts or how the comma/default-empty 'providers' string is interpreted or filtered on.

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 'Compare providers without treating missing data as unavailable' gestures at a comparison over providers, but never names the resource being compared (GPUs) or what aspect is compared (price, availability). It reads as a behavioral caveat rather than a statement of what the tool does.

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

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

No when-to-use guidance and no mention of alternatives. Sibling tools like gpufeed_get_cheapest and gpufeed_get_availability clearly overlap, yet the description gives no routing signal to distinguish this comparison tool from them.

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, so the description carries the full burden. It discloses that it returns an estimate with assumptions exposed, which is meaningful behavioral context – the output is not a flat price but a derivation. It does not mention auth needs, rate limits, or what happens with unavailable GPU types, but for a read-only estimation tool that is a moderate 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?

One sentence, front-loaded with the action and the data basis, with no filler. It is under-informative rather than over-long, so conciseness is high even though completeness suffers.

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?

An output schema exists, so return values need not be explained, but the description omits parameter intent (0% schema coverage) and any routing guidance among seven siblings. For a 2-required-param tool with no annotations, more 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?

Schema coverage is 0% and the description mentions none of the three parameters (gpu, count, hours). 'GPU compute cost' and the tool name hint that gpu and hours are expected, but count (multi-GPU scaling) and the expected value format of gpu (slug? model name?) are undocumented in both description and 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?

States a clear verb (Estimate) and resource (GPU compute cost) and specifies the basis (observed prices). However, it gives no differentiation from siblings like gpufeed_get_cheapest or gpufeed_recommend, so an agent must infer when to use this vs. cheaper/recommend endpoints.

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 when-to-use, when-not-to-use, or named alternative. With seven sibling gpufeed_* tools, the absence of any routing guidance leaves the agent to guess. The phrase 'with assumptions exposed' hints at a use case but does not state conditions.

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 does disclose real behavioral context by specifying that results are 'observed' listings drawn from 'free-first sources', which hints at data provenance and source-priority behavior. It stops short of covering freshness, rate limits, auth needs, or what happens when no listings 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?

A single front-loaded sentence with zero filler. The scope qualifier follows immediately after the core action, so nothing needs re-reading.

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?

An output schema exists, so return values needn't be explained, but the tool still has two parameters at 0% schema coverage and no annotations. One sentence is insufficient to cover either parameter semantics or when this tool should be selected over its numerous siblings.

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 0%, so the description must compensate, and it largely does not. 'GPU listings' faintly implies the required 'gpu' parameter, but the 'count' parameter (default 1) is entirely unexplained in both schema and description, leaving the agent to guess its meaning and limits.

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 gives a clear verb and resource ('Return observed GPU listings') plus a scope qualifier ('from free-first sources'), which distinguishes it from siblings like gpufeed_get_cheapest or gpufeed_get_history. However, 'observed' and 'free-first' are left undefined, and no sibling is named explicitly, so the differentiation is implied rather than stated.

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 when-to-use guidance, no conditions, and no named alternative among the many gpufeed siblings (get_cheapest, compare_providers, recommend). 'Free-first sources' hints at a sourcing policy but tells the agent nothing about when this tool is the right choice.

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 behavioral burden. It does not state permissions, whether 'verified' means availability-checked, rate limits, failure behavior, or how count/hours affect the result; only the phrase 'free-first' hints at ordering.

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?

Single sentence, front-loaded with the action and result. It contains no padding or wasted words, though it is under-specified rather than efficiently complete.

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?

An output schema exists, so return values need not be explained. However, with no annotations and 0% schema description coverage across three parameters, the description omits key context: parameter meanings, selection guidance, and behavioral constraints.

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 0%, and the description explains none of the three parameters. It does not define 'gpu', 'count', or 'hours', nor their default values or units. The word 'GPU' is not enough to disambiguate the required parameter.

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

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

States a specific verb and resource ('Return ... GPU offer'), and the qualifier 'cheapest verified free-first' distinguishes it from sibling price, availability, and recommendation tools. It does not name those siblings or fully unpack 'free-first', but the core purpose is clear.

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 when-to-use guidance, no alternatives, and no exclusions. An agent cannot tell from the description when to choose this over gpufeed_recommend, gpufeed_compare_providers, or gpufeed_get_availability.

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 disclosure burden and largely fails it: no mention of permission requirements, rate limits, default lookback window, result cap, or whether missing data is omitted versus interpolated. 'Verified' hints at a data-quality filter but is never defined, so the agent cannot know what observations are actually excluded.

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?

It is a single front-loaded sentence with zero padding, which is structurally clean. But at this length for a four-parameter tool it is under-specified rather than concise, so it cannot rate highly on this dimension.

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 existence of an output schema excuses the description from explaining return shape, but everything else is missing: no parameter meaning, no usage context, no behavioral caveats, and no differentiation from sibling price tools. For a query tool with four inputs and zero annotation coverage, this is too thin to call 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 description coverage is 0% and the description adds nothing about any of the four parameters. The roles of 'gpu', 'days' (default 7), 'limit' (default 100), and 'provider' (default empty string) — including what an empty provider means and what units 'days' uses — are entirely undocumented.

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

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

The description states a verb+resource ('Return ... GPU price observations') and adds a distinguishing qualifier, 'persisted verified', that separates it from live-quote tools. However, it never mentions the historical/time-series nature implied by the name 'get_history', and it does nothing to separate it from siblings like gpufeed_get_price_index or gpufeed_get_cheapest.

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 explicit when-to-use statement and no named alternative. The word 'persisted' weakly implies this is for retrospective rather than current data, but that is inference, not guidance, and the agent is left to guess how this differs from the five other price-related siblings.

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

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

With no annotations, the description carries the full behavioral burden, yet it only reveals that statistics are computed over 'persisted' observations. It omits whether the data is cached, what aggregation or windowing is applied, and any read-only/permission context an agent would need before calling it.

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?

It is a single front-loaded sentence with no padding, which is structurally clean. But it is terse to the point of under-specification for a tool with two undocumented parameters, so conciseness here shades into incompleteness.

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?

An output schema exists, so return formatting needn't be described. Still, for a computed index tool with no annotations and 0% parameter coverage, the description omits which statistics are returned, the meaning of the observation window, and how it relates to sibling price/availability tools.

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 0% and there are two parameters, so the description must compensate. It never explains the required 'gpu' identifier (string, id vs. model name?) nor the 'days' window (default 7) or what it limits, leaving both parameters semantically undocumented.

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 gives a verb ('Return') and a resource ('descriptive statistics over persisted GPU observations'), so the general action is clear. However, it never mentions pricing or an 'index' despite the tool name get_price_index, and it doesn't state which statistics are produced, so it barely distinguishes itself from siblings like gpufeed_get_history or gpufeed_get_cheapest.

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 when-to-use guidance, no prerequisites, and no mention of alternatives such as gpufeed_get_history or gpufeed_get_cheapest. An agent gets no signal about when this index is preferable to the other gpufeed retrieval 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 carries the full behavioral burden. It does not state whether the recommendation is deterministic, what 'bounded' means, whether results are cached/live, or how cost is defined. An output schema exists, so return values are covered, but the core behavior of the recommendation is opaque.

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

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

A single sentence, so nothing is wasted, but it is under-specified rather than concise. 'Bounded lowest-observed-cost recommendation for further verification' packs jargon without front-loading a clear action or object.

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 3-parameter tool with no annotations and no requirement to explain outputs (output schema exists), the description should at least define the GPU input and the 'bounded' recommendation semantics. It leaves the agent unable to confidently invoke the tool or interpret the cost basis.

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 0% and the description adds nothing about any of the three parameters. 'gpu' is required but its expected format (model name? ID?) is undocumented, and 'count'/'hours' defaults are uninterpreted. With low coverage the description must compensate but instead says nothing.

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 verb 'recommend' and the vague resource 'lowest-observed-cost' are present, but the subject is never named — it never says it recommends GPUs, though the 'gpu' parameter and gpufeed_* siblings imply it. The phrase 'for further verification' obscures the actual output rather than clarifying it. It is distinguishable from gpufeed_get_cheapest only by the word 'recommend', which is not enough.

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 when-to-use, when-not-to-use, or alternative is mentioned, despite siblings like gpufeed_get_cheapest and gpufeed_compare_providers that an agent would obviously need to disambiguate against. The fragment 'for further verification' hints at a downstream workflow but gives no actionable selection guidance.

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

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

No annotations are provided, so the description carries the full burden. It implies a read-only status retrieval, but doesn't confirm side-effect-free behavior, rate limits, caching, or what 'guardrail' and 'metering' status mean operationally. For a no-annotation tool this 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?

A single eight-word sentence that front-loads the verb and lists the returned facets. No filler, no restatement of 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?

An output schema exists, so return-value explanations are not required. The description tells the agent what categories of status are returned, which is adequate for a zero-arg read tool, though it could mention when this status is useful to check.

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

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

The tool takes zero parameters, so there is no parameter semantics to explain; per the rubric this earns a baseline of 4. Schema coverage is 100% and irrelevant here.

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

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

States a specific verb ('Return') and enumerates the resource facets (scope, guardrail, metering, provider status) for the GPUFEED service. This is clear enough to distinguish it from siblings like gpufeed_get_availability or gpufeed_compare_providers, though 'scope' and 'guardrail' are generic terms that could be clearer.

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 status/health-check tool versus the many other gpufeed_* tools. A user might reasonably invoke it before other calls, but the description never says so. No exclusions or alternatives 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'List supported chains' and offers no detail about read-only guarantees, authentication needs, rate limits, or output behavior. The verb 'List' weakly implies safety, but nothing beyond that is 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 a single, front-loaded sentence with no filler words. It is appropriately sized for a simple listing operation with no parameters.

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 with an output schema, 'List supported chains' is nearly complete and the output schema can cover return values. However, it lacks any context about what chains are supported or how this relates to the sibling tools, leaving a small but real gap.

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

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

The tool has zero parameters and the schema coverage is effectively complete, so there is nothing for the description to add about parameter semantics. A baseline score of 4 is appropriate for a zero-parameter tool.

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

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

The description uses a specific verb ('List') and a clear resource ('supported chains'), so an agent can immediately understand the basic purpose. It does not explicitly distinguish itself from sibling tools like vulnhunt_decision or vulnhunt_payment_resources, so it misses the top score.

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

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

There is no guidance about when to use this tool versus alternatives, no mention of the sibling tools, and no context about what 'supported chains' means in the broader workflow. The intended usage is only implicit from the name and description.

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 of behavioral disclosure. It says 'Return' but does not explain whether the operation is read-only, whether it makes external requests, what 'bounded free' means, whether there are limits, or what side effects might occur.

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 with no wasted words, which is good for structure. However, the terseness comes at the cost of meaning: 'bounded free decision packet' is cryptic and would benefit from brief clarification.

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 annotations, no usage guidance, and zero parameter semantics, the description is too thin for an agent to confidently invoke the tool. An output schema exists, so return values need not be explained, but the meaning of 'bounded free decision packet' and the role of the parameters remain unexplained.

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 0%, so the description must compensate for the lack of parameter documentation. It implies address and chain_id identify an EVM contract, but it does not explain address format, chain_id semantics, or any constraints or defaults. This is insufficient for a tool with two required parameters.

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

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

States a specific verb ('Return') and resource ('bounded free decision packet' for an EVM contract), which distinguishes it from sibling tools about chains and payment resources. However, 'bounded free decision packet' is domain jargon and not fully explained, so it is clear at a high level but not precise.

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 versus vulnhunt_chains or vulnhunt_payment_resources. The intended use is only implied by the sibling names and the phrase 'for an EVM contract'; there are no explicit alternatives, exclusions, or preconditions.

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

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

Annotations are entirely absent, so the description must carry the full burden. 'Return' implies a read operation, but the description doesn't disclose authentication or payment prerequisites (relevant given the 'paid' and 'x402 terms' hints), any rate limits, or what side effects exist. The 'paid' qualifier hints at cost but is not made explicit 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?

A single efficient sentence with zero filler, front-loaded with the primary purpose ('Return the catalog'). It could arguably earn a 5, but it omits any usage or qualification details that might matter, so 4 is fair.

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 query tool with an output schema present, the description is nearly adequate. It names the catalog and x402 terms but leaves the payment/auth dimension ('paid', 'x402') unexplained, which is material for a resource that may require credentials or payment before 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?

With zero parameters and schema coverage at 100%, the baseline is 4. No parameter documentation is needed since the schema defines an empty object; the description adds no param info but none is required.

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

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

States a specific verb ('Return') and a clear resource ('machine-readable paid resource catalog and x402 terms'). The name 'vulnhunt_payment_resources' is expanded by the description, and 'chains'/'decision' siblings suggest distinct purposes, though the description doesn't explicitly contrast 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?

No guidance on when to call this tool versus vulnhunt_chains or vulnhunt_decision. Usage context is only implied by the name ('payment resources'), leaving the agent to infer when this is the right sibling.

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