Get Open Graph
get_open_graphGet Open Graph data for a scan_id.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| scan_id | Yes |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
get_open_graphGet Open Graph data 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?
Annotations already declare the tool as read-only, idempotent, and non-destructive, so the safety profile is covered. However, the description adds no additional behavioral context beyond that, such as what happens with invalid scan_ids, whether it returns partial data, or any rate-limiting considerations. It fails to go beyond what annotations already 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 a single short sentence with no wasted words. It is front-loaded and efficiently states the core purpose. It could be slightly longer to add context, but as far as conciseness goes, it is well-structured and easy to parse.
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?
While the tool is simple (one parameter) and an output schema exists, the description is too minimal to be considered complete. It does not explain what Open Graph data entails, nor does it provide any guidance on valid scan_id formats or expected results. Given the low schema coverage and lack of parameter documentation, the description leaves significant gaps for an agent.
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 zero description coverage for the single parameter scan_id, and the description merely says 'for a scan_id' without adding any extra meaning, format, or constraints. The parameter semantics are essentially undocumented, leaving the agent to infer from the name alone.
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 retrieves Open Graph data for a given scan_id, using a specific verb and resource. It is unambiguous and distinguishable from the many sibling get_* tools, though it does not explicitly differentiate itself from them. The scope is somewhat generic, but the purpose is nevertheless clear.
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 provided on when to use this tool versus alternatives. It does not mention any prerequisites, exclusions, or situations where another tool might be more appropriate. The only implied context is that a scan_id is required, but this is not elaborated.
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.