get_jsfingerprint_sourceGet JS fingerprint source.
| Name | Required | Description | Default |
|---|---|---|---|
| fingerprint_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds no behavioral context beyond what annotations already provide. Annotations declare readOnlyHint and idempotentHint, but the description fails to clarify what 'source' means (e.g., raw JavaScript, metadata) or any output format details, which is a gap given the tool's purpose.
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 one-sentence description is brief but under-specified. It provides no informative content beyond the tool's name, making it inefficient rather than concise. A good concise description still carries essential context.
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 tool's context among many similar siblings and a single parameter, the description is incomplete. It lacks usage context, differentiation, and parameter semantics, and does not leverage the output schema to enhance understanding. The agent cannot reliably infer when and how to use this tool.
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 input schema has one required integer fingerprint_id with 0% description coverage, and the tool description does not explain this parameter. The name 'fingerprint_id' is somewhat self-explanatory, but no additional meaning is provided, so the description does not compensate for the schema's lack of detail.
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 'Get JS fingerprint source.' is clear about the resource but is essentially a restatement of the title. It does not specify scope (e.g., by fingerprint_id) or differentiate from siblings like get_jsfingerprint or get_js_fingerprints, so it lacks the specificity needed for a 4 or 5.
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 guidance is given on when to use this tool versus the many similar fingerprint-related tools. There is no mention of prerequisites, typical use cases, or exclusions, leaving the agent without context to select it appropriately.
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.