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

No annotations are provided, so the description carries the full burden, and it does substantial work: it discloses the POST-to-callbackUrl delivery model, subscription persistence, pre-API rejection of invalid blockchain/eventType combinations, the two-step preview-then-confirm flow with a one-time token, and a 30-credit cost with the caveat that actual credits come from response headers. It omits authentication requirements and does not describe the preview/token response shape beyond the token itself.

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?

Well front-loaded: purpose, delivery behavior, and persistence come first, then a scannable bullet list of event types, then confirmations and cost. The event-type bullets are the valuable payload; the credits disclaimer paragraph is boilerplate that partially duplicates the cost line above it.

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 an 11-parameter mutation tool with no annotations and no output schema, the description covers the critical unknowns: what triggers a callback, which inputs are conditionally required, the delayed-confirmation execution model, and cost. It would be complete with a brief note on auth requirements and on what the preview/confirmation responses contain, but nothing essential is missing.

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

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

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning the schema lacks: the per-event-type firing semantics (unconfirmed vs. confirmed vs. each-confirmation vs. block-mined) and the rule that all types except block-mined need an address. Cross-parameter constraints such as confirmationsCount being required for '-each-confirmation' and receiveCallbackOn applying only to certain types are also stated in the schema descriptions, so part of this is duplication rather than added value.

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 ('Create a webhook subscription for on-chain events') and enumerates exactly which event types can be subscribed to, so the agent knows precisely what the tool produces. It never names or contrasts with the sibling blockchain_events_manage, so sibling differentiation is left implicit rather than explicit.

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?

Gives clear conditions: this is for creating subscriptions, subscriptions persist until deleted (implying the manage sibling handles lifecycle), all event types except block-mined require an address, and create actions require confirmation. It does not explicitly say when to call this versus blockchain_events_manage, and no exclusions for duplicate subscriptions are framed as usage 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?

With no annotations, the description carries the full burden and does well: it discloses that delete-subscription stops webhook delivery and that delete/activate require confirmation via a preview + one-time token rather than executing immediately. It also reports per-action credit cost and points to response headers for actual credits. It does not mention auth/permission requirements or preview/token expiry nuances (the token TTL lives only in the schema).

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?

Purpose and action list are front-loaded and scannable as bullets, and the confirmation caveat is clearly flagged. The credits block is repetitive (four identical entries plus a boilerplate disclaimer), which costs some 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?

For a multi-action tool with no output schema and no annotations, the description covers the action surface, the destructive-action confirmation flow, and the cost model well. It is a bit thin on the actual return shape of list-subscriptions (only 'paginated'), but that is a minor 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?

Schema description coverage is 100% and the schema already documents every parameter, including limit/offset paging scope and the confirmationToken approval workflow. The description maps actions to referenceId usage ('get, delete, activate'), but adds little syntax or format detail beyond the schema, 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 states a specific verb+resource ('Manage existing webhook subscriptions for on-chain events') and enumerates the four supported actions with a one-line gloss each. It also distinguishes itself from the sibling blockchain_events_create by scoping management to subscriptions 'created via blockchain_events_create'.

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?

It explicitly says when to use this tool ('to view, delete, or re-activate event subscriptions') and points at the sibling blockchain_events_create for creation, giving a clear create-vs-manage split. There is no explicit 'when not to use' clause, but the action routing makes selection unambiguous.

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 and explicitly notes 'no API call, no credits consumed,' which is key behavioral information. It also discloses detailed content such as retry strategy, HMAC security, and rate-limit penalty multipliers, going well beyond a generic 'returns info' statement.

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 front-loaded with the critical 'no API call, no credits consumed' caveat and uses a compact bullet list. Each bullet covers a distinct action without wasted prose, making it highly scannable for an agent.

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 reference-documentation tool with no output schema and no annotations, this description is complete enough: it defines all five actions and gives sufficient detail about their content. It also clarifies side effects (none) and cost implications (none), covering the main contextual risks.

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?

Although schema coverage is 100%, the description adds significant meaning by explaining each allowed action enum value in detail (e.g., callbacks covers URL requirements, 5 retries, HMAC). This transforms enum names into actionable context and compensates fully beyond the schema's short parameter descriptions.

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

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

The description states this is CryptoAPIs reference documentation with no API call or credits consumed, and enumerates five specific topics (blockchains, errors, credits, callbacks, limits). This clearly identifies it as an informational tool distinct from domain siblings like aml.

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 bulleted actions give clear contexts for when to use the tool, such as looking up error codes, credit structures, callback mechanics, or rate limits. It does not explicitly name alternatives or exclusion conditions, so it stops short of a full when/when-not specification.

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