Roll-up of corpus activity for a single ASN — observation count, distinct source IPs, actor count, scanner count, high-confidence actor count, and per-protocol breakdown.
| Name | Required | Description | Default |
|---|---|---|---|
| asn | Yes | ||
| since_ms | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the output structure (e.g., observation count, per-protocol breakdown), providing behavioral context. However, it lacks details on authorization, rate limits, or potential side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the tool's purpose and output. It could be slightly more structured, but there is no wasted 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?
The description explains the output but omits how parameters like 'since_ms' affect the roll-up, leaving ambiguity about time filtering. Overall adequate but incomplete.
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%, so description must compensate. It explains the 'asn' parameter is for a single ASN but does not specify format (e.g., 'AS1234') and ignores 'since_ms' entirely, adding minimal 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?
The description clearly states the tool provides a 'roll-up of corpus activity for a single ASN' and lists specific aggregated counts, distinguishing it from sibling tools like scry_country or scry_campaigns.
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 ASN-level aggregation but does not explicitly state when to prefer this over siblings or provide any exclusions or context for alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a unique resource or operation: single IP lookup, bulk IP lookup, ASN roll-up, country roll-up, campaign detail, campaign list, recent observations, stats, timeseries, tool detail, tool list, and top sources. There is no overlap or ambiguity, and descriptions explicitly state when each tool should or should not be used.
All tool names follow the consistent pattern 'scry_' plus a descriptive noun (e.g., scry_asn, scry_check, scry_timeseries). The naming is uniform, lowercase with underscores, and logically reflects the tool's purpose.
With 12 tools, the set is well-scoped for a threat intelligence server. It provides sufficient granularity without being overly large or sparse, covering core functionality without redundancy.
The tool surface covers key operations for IP triage, campaign analysis, statistical overviews, time-series trends, and tool detection. There are no obvious gaps; all common use cases for network observation and threat intelligence are addressed.