get_analyzer_resultsGet analyzer results for a scan_id.
| Name | Required | Description | Default |
|---|---|---|---|
| scan_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds no behavioral details beyond the annotations, such as whether scan_id must correspond to an existing scan, what happens if no results exist, or how the output is structured. This is a missed opportunity to add value beyond the structured fields.
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, efficient sentence with no redundant words or fluff, which aligns with conciseness. However, the minimalism comes at the cost of useful context, so it is not a 5.
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 large number of sibling tools and the ambiguity of 'analyzer results', this description is incomplete. It does not explain what analyzer results are, how they relate to a scan, or when to prefer this tool over others like get_scan_result. The presence of an output schema doesn't mitigate the lack of decision-relevant context.
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 only the parameter name 'scan_id' with no description (0% schema description coverage). The description merely repeats 'scan_id' as part of the sentence but does not explain what a scan_id is, where to obtain it, or its format. The description should compensate for the schema's lack of detail but fails to do so.
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 clear verb ('Get') and a resource ('analyzer results for a scan_id'), which conveys the basic action. However, 'analyzer results' is ambiguous and does not distinguish this tool from siblings like get_scan_result or get_ai_analysis, which likely provide similar outputs.
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 simply states the function without any context about prerequisites (e.g., scan completion), expected use cases, or why an agent should choose this over similar get_* tools.
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.
Many tools overlap in purpose, particularly the JS fingerprint search functions (e.g., search_js_fingerprint_by_md5 and search_jsfingerprints_by_md5) which are nearly identical. The large number of get_* and search_* tools for various statistics also creates boundary ambiguity.
The verb_noun pattern is mostly followed, but there are significant inconsistencies: 'jsfingerprints' vs 'js_fingerprints' vs 'js_fingerprint', and the occasional use of 'find' instead of 'search' (e.g., find_js_fingerprint_similar_by_hash). This mixed style makes it hard to predict tool names.
With 128 tools, the server is severely over-scoped. Many tools could be combined (e.g., all search_jsfingerprints_by_* variants) or parameterized. The sheer number overwhelms an agent and suggests poor API design.
The core URL scanning workflow (submit, retrieve results, search, analyze) is well covered, including detailed sub-analyses like malware, YARA, and JS fingerprints. Minor gaps include no scan cancellation or user-specific scan listing, but overall coverage is strong.