search_js_fingerprinter2_similarSearch JS Fingerprinter2 similar scans.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| scan_id | Yes | ||
| include_self | No | ||
| min_similarity | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is known. The description adds no additional behavioral context, such as how similarity is computed, whether self is included by default, or the role of min_similarity.
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 or redundancy. It is concise, though it achieves this by omitting substantive details.
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 4-parameter search tool with many sibling alternatives, the description is operationally thin. It does not explain the similarity mechanism, expected output interpretation, or any edge cases, so an agent cannot confidently select or invoke it based solely on this text.
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 provides no parameter explanations. scan_id is inferable from the tool name, but limit, include_self, and min_similarity remain unexplained, forcing the agent to rely on parameter names and defaults.
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 ('Search') and resource ('JS Fingerprinter2 similar scans'), which distinguishes it from other fingerprint search tools. However, it does not explicitly state that the search is anchored by a scan_id, leaving some ambiguity about the input.
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 usage guidance is provided. The description does not explain when to use this tool versus siblings like search_js_fingerprinter2_composite_hash, search_js_fingerprinter2_signature, or get_jsfingerprint_similar, nor does it offer any conditions or exclusions.
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.