Extract one value from JSON using a simple dot path with array indexes, for example users[0].email.
| Name | Required | Description | Default |
|---|---|---|---|
| json | Yes | JSON text, up to 100 KB. | |
| path | Yes | Dot path such as user.profile.name or users[0].email. | |
| l402_proof | No | L402 payment proof "<macaroon>:<preimage>". Omit on the first call; an unpaid call returns a 0 sat Lightning invoice and the macaroon. Pay the invoice, then repeat the call with this argument set. |
Changes observed during successful MCP inspections.
Input schema / properties / l402_proof / descriptionPrevious value: -"L402 payment proof \"<macaroon>:<preimage>\". Omit on the first call; an unpaid call returns a 5 sat Lightning invoice and the macaroon. Pay the invoice, then repeat the call with this argument set."New value: +"L402 payment proof \"<macaroon>:<preimage>\". Omit on the first call; an unpaid call returns a 0 sat Lightning invoice and the macaroon. Pay the invoice, then repeat the call with this argument set."Input schema / properties / l402_proofAdded value: +{
+ "description": "L402 payment proof \"<macaroon>:<preimage>\". Omit on the first call; an unpaid call returns a 5 sat Lightning invoice and the macaroon. Pay the invoice, then repeat the call with this argument set.",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds the useful constraint that only a single value is returned, but says nothing about the L402 payment retry flow or failure behavior, which live only in the schema's l402_proof text.
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?
A single sentence that front-loads the operation, states the scope (one value), and ends with a concrete example. No wasted wording.
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 simple two-parameter read tool with full schema coverage and no output schema, the description conveys scope and return shape (one value) adequately. The only shortfall is that the non-obvious Lightning payment retry behavior is never surfaced outside the parameter 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 description coverage is 100%, so both required parameters and the payment proof are already documented, including path syntax examples. The description's example path duplicates the schema's "path" description and adds no format or edge-case detail beyond it; baseline 3 applies.
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 gives a specific verb and resource ("Extract one value from JSON") plus the mechanism (dot path with array indexes) and a concrete example. This clearly separates it from siblings like json_validate (validation) and csv_to_json (format conversion) without the agent needing to open any schema.
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?
The extraction use case is implied by the description and example, but there is no explicit when-to-use guidance, no mention of pairing with json_validate, and no statement of when this tool is the wrong choice (e.g. needing multiple values at once). Usage must be inferred.
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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