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Jambozx

OnlineCyberTools MCP (280+ filterable tools)

data_json_path_evaluator

Read-onlyIdempotent

Evaluate a JSONPath expression against a JSON document to retrieve all matched values with their paths.

Instructions

JSON Path Evaluator (RFC 9535 / Goessner JSONPath Query). Evaluate one JSONPath expression against a JSON document and return every matched value with its path. Supports child/recursive-descent ($..), wildcards (* / [*]), numeric and negative indices, array slices ([start:end:step]), key unions, and filter expressions with comparison/boolean operators and length(); both dot and bracket notation, RFC 9535 and classic Goessner syntax. Use this to extract or query values from a JSON document you already have; use data_json_schema_validator instead to check a document against a schema, format_json to pretty-print or minify, or webdev_xml_to_json to convert XML first. Hand-rolled parser, no eval. Runs locally on the input you provide: read-only, non-destructive, contacts no external service, and is rate-limited. Returns the matches array (each with path, normalisedPath, value), a matchCount, the echoed expression, and the parsed document.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
documentYesJSON document to query. Pass either a JSON value (object, array, string, number, boolean, null) or a string of raw JSON, which is parsed before evaluation.
expressionYesJSONPath query expression. Must be non-empty and start with the root token $ (for example $..book[?(@.price<10)].title).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
successNoWhether evaluation succeeded.
operationNoAlways evaluate.
resultNoThe evaluation payload.
Behavior5/5

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

Description adds significant context beyond annotations: hand-rolled parser (no eval), local execution, read-only/non-destructive, no external service, rate-limited. Annotations already indicated readOnlyHint=true and destructiveHint=false, but the description enriches with implementation details.

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?

Description is well-structured with clear sections: purpose, returns, syntax support, usage guidance, implementation. It's informative but somewhat verbose; could be slightly more concise without losing clarity. Still efficient.

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

Completeness5/5

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

Given the complexity of JSONPath evaluation and the existence of an output schema, the description covers all necessary aspects: input, expression rules, output structure (matches array, path, value, count), and contextual comparisons. It is complete for effective use.

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 baseline is 3. The description does not add much beyond what's in the schema for the parameters. It mentions non-empty and root token $ for expression, but that's already in the schema description.

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 it evaluates a JSONPath expression against a JSON document and returns matched values with paths. It specifies supported syntax (child/recursive-descent, wildcards, slices, filters) and distinguishes itself from siblings like data_json_schema_validator, format_json, and webdev_xml_to_json.

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

Usage Guidelines5/5

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

Explicitly states when to use this tool ('extract or query values from a JSON document you already have') and when not to, naming specific sibling tools for alternative tasks. This provides clear guidance for selection.

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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