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graphql_find_hidden

Discover undocumented GraphQL fields by analyzing suggestion errors and probing for sensitive field names. This tool sends read-only queries to reveal hidden type information for security testing.

Instructions

Find hidden/undocumented fields on a GraphQL type using field suggestion errors. Sends queries with intentionally misspelled field names to trigger GraphQL's field suggestion feature, which reveals valid field names. Also tries common sensitive field names directly. Returns: {discovered_fields: [str], suggestion_results: [...], direct_probe_results: [...]}. Side effects: Read-only POST requests. Sends ~25 requests.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesGraphQL endpoint URL
type_nameYesGraphQL type to probe for hidden fields, e.g. 'User', 'Post', 'BlogPost'
known_fieldNoA known field on this type to use in queries, e.g. 'id' or 'title'id
query_nameNoQuery name to use for fetching objects, e.g. 'getUser' or 'getBlogPost'
query_argNoQuery argument, e.g. 'id: 1' or 'slug: "test"'
auth_headerNoAuthorization header value
auth_cookieNoSession cookie
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden and does well by disclosing key behaviors: it's read-only (though POST requests), sends multiple requests (~25), and returns specific data structures. It also explains the probing technique (misspelled field names, common sensitive fields). However, it lacks details on error handling or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, starting with the core purpose. Each sentence adds value, but it could be slightly more structured, such as separating side effects into a distinct section for clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (security probing with multiple parameters) and lack of annotations or output schema, the description is fairly complete. It covers purpose, method, return values, and side effects, though it could benefit from more detail on error scenarios or usage context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional parameter semantics beyond what the schema provides, such as examples or constraints, meeting the baseline for high coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('find hidden/undocumented fields'), the method ('using field suggestion errors'), and the target ('on a GraphQL type'). It distinguishes itself from siblings like 'graphql_introspect' by focusing on probing for hidden fields rather than standard introspection.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for security testing or reconnaissance by mentioning 'sends ~25 requests' and 'read-only POST requests,' but it does not explicitly state when to use this tool versus alternatives like 'graphql_introspect' or other sibling tools. No explicit exclusions or prerequisites are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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