Crawler IP Verifier

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

Annotations already mark the tool as read-only and idempotent. The description adds valuable behavioral details beyond the annotations: every export includes a provenance header with source URLs and mirror time, and reports rule cost. This informs the agent about the output's structure and guarantees without contradicting the annotations.

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 with no wasted words. The first sentence front-loads the core purpose and lists the formats; the second adds behavioral guarantees. It avoids repeating schema details and earns every piece of text.

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 read-only export tool with five parameters and no output schema, the description covers the essential context: output formats, provenance header, mirror time, and rule cost. It doesn't explain every nuance (e.g., what 'rule cost' means), but the annotations cover safety and the schema covers parameter defaults, so nothing critical 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 description coverage is 100%, so all parameters are already documented in the input schema. The description doesn't add parameter-level semantics beyond illustrating the available output formats, which the schema enum already lists. A baseline of 3 is appropriate given the schema's full coverage.

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: transforming a set of operators into a paste-ready configuration across multiple named formats. The title reinforces the allow/deny use case. It distinguishes itself from the sibling tools (lookup, stats, verification) by being the only export/formatting tool.

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 when to use the tool (whenever a paste-ready allowlist/denylist is needed in a specific format), but it doesn't explicitly mention alternatives or exclusions. Since the sibling tools serve clearly different purposes, the routing guidance is adequate but implicit rather than explicit.

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 already declare readOnlyHint=true and idempotentHint=true, so safety is covered. The description adds behavioral value by specifying the full match semantics — containing ranges, contained ranges, and partial overlaps — as well as the alternate lookup by operator/source slug, which goes beyond what annotations alone provide.

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 with no filler. The core operation is stated first, followed by concrete use cases and the alternative input mode. Every clause contributes useful 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?

The description covers both parameters, the core matching behavior, and practical use cases. It does leave minor gaps: both parameters are optional in the schema, and the description does not state what happens if neither or both are provided, nor does it describe the exact return structure. However, for a read-only lookup with simple inputs, this is nearly 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 coverage is 100% and each parameter has a descriptive schema entry, so the baseline is 3. The description adds further meaning by explaining how the cidr parameter is interpreted: every published operator prefix that contains, is contained by, or partially overlaps it. It also clarifies that the operator parameter returns everything published by that source, which is not stated in the schema.

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

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

The description names a specific verb and resource: 'get every published operator prefix' that contains, is contained by, or overlaps a CIDR. It also clearly distinguishes this from sibling tools by framing it around crawler-range collision checks and allowlist auditing, so an agent can tell it apart from range_stats or export_ip_acl.

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 concrete when-to-use context: 'the check for does my network collide with a crawler range' and 'auditing an allowlist somebody handed you.' It also explains the alternative operator/slug input mode, but it does not explicitly name sibling alternatives or state when not to use this tool.

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 already declare readOnlyHint and idempotentHint, so safety is covered. The description goes beyond annotations by revealing what data is returned, including freshness information and multi-operator overlap, which helps the agent understand the tool's output behavior. It does not mention pagination or exact response formatting, but for a zero-parameter read-only stats tool that is a minor 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 compact and front-loaded with concrete output details, followed by a single sentence explaining its practical relevance. Every sentence earns its place, and there is no wasted wording.

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 tool with no parameters, no output schema, and strong safety annotations, the description provides enough detail about the returned information and the decision context in which it is useful. An agent can understand what this tool offers and why it might be selected.

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 input schema is empty, so there are no parameter semantics to clarify. The description appropriately focuses on what the tool reports rather than on inputs, matching the baseline for a parameterless 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 clearly identifies what the tool provides: per-source prefix counts, addresses, /24-equivalents, smallest/largest prefix, publishing URL, and last-fetch time, plus multi-operator prefixes. It is distinct from siblings like lookup_prefix or verify_batch, but it lacks an explicit action verb such as 'returns' or 'computes'.

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 closing sentence gives practical usage context: this is the sizing and freshness information an allowlist decision needs. It implies when to use the tool, though it does not explicitly contrast it with sibling tools or state when not to use it.

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?

The description discloses a key non-obvious behavior beyond the readOnlyHint annotation: reverse DNS is never run, only the command is returned. It also reveals that freshness information is included, giving the agent useful context about the data's reliability.

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

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

Two dense sentences front-load the core purpose and the critical non-behavior. Every phrase contributes: what is returned, when to call it, and what it deliberately does not do.

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?

Even without an output schema, the description tells the agent exactly what to expect: per-crawler classification, source URLs or dig commands, and freshness. Combined with the readOnly and idempotent annotations, an agent has enough to invoke and interpret the result correctly.

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

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

Schema coverage is 100% for the single optional 'crawler' parameter, so the schema already documents the accepted substrings and omission behavior. The description adds only 'per crawler' framing, which doesn't materially extend parameter meaning beyond the schema.

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

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

The description clearly states the tool reports per-crawler verification methods: IP ranges, reverse DNS documentation, or none, along with source URLs or dig commands and freshness. It distinguishes itself from sibling tools by explicitly noting that reverse DNS is never executed here, clarifying its informational role.

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 gives an explicit trigger: 'Call it before reading anything into an address that matched nothing.' It does not name alternative tools directly, but the statement that reverse DNS commands are handed back rather than run implies when a real verification tool like verify_batch would be more appropriate.

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?

The description says 'a miss is not evidence of a fake', which implies open-world semantics: a non-match does not prove absence. This directly contradicts openWorldHint=false, which indicates closed-world/complete-result semantics. This is a serious annotation contradiction, so the behavioral guidance cannot be trusted.

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?

Three sentences with no filler: the scope and limit are front-loaded, the return shape is summarized, and the claim-verification caveat is stated plainly. Every sentence contributes distinct 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?

With no output schema, the description compensates by listing per-address return fields and the operator rollup, plus input formats, the batch cap, and the miss interpretation. It is nearly complete, but the openWorld contradiction and lack of explicit routing to a single-lookup sibling prevent a perfect score.

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 covers the address formats and the 500 cap with 100% coverage. The description adds value by explaining that object entries like {"ip": ..., "claim": ...} are meant to test a claimed identity against the ranges, giving semantic meaning beyond the schema's structural example.

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 a specific action (check), a concrete resource (addresses against mirrored operator prefix lists), and the return payload (matching prefix, source, mirror time, rollup by operator). It also distinguishes itself from siblings like lookup_prefix by emphasizing batch scope and 'in one call'.

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 clearly signals batch-oriented use through 'up to 500 addresses' and 'in one call', and it explains the {ip, claim} use case for testing claimed identities. However, it does not explicitly name an alternative such as lookup_prefix or state when a single lookup would be preferable, so it has clear context but no exclusions.

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