Validate JSON, identify its root type, and return normalized JSON plus a SHA-256 content hash.
| Name | Required | Description | Default |
|---|---|---|---|
| json | Yes | JSON text to validate, up to 100 KB. | |
| 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 mark it read-only and non-destructive. The description adds useful output details: normalized JSON, root type and SHA-256 hash. It does not explain what happens with invalid JSON, what 'normalized' means (key sorting? whitespace?), or the L402 payment gating, which the schema documents but the description omits.
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?
It is a single front-loaded sentence with no wasted words. Every clause states an output or action.
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?
There is no output schema, and the description only partly covers returns. It omits error behavior for invalid input and the normalization rules. The payment flow lives only in the schema, a notable gap for a tool whose first call returns an invoice instead of a result.
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 coverage is 100% and well documented, including the 100 KB limit and the L402 flow. The description adds nothing about parameters beyond the schema, so the baseline of 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?
It gives specific verbs and outputs: validate, identify the root type, and return normalized JSON plus a SHA-256 hash. It does not separate itself from siblings like json_extract or hash_generate, though the purpose is distinct enough to infer.
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?
It gives no guidance on when to use this tool over json_extract (querying), hash_generate (hashing arbitrary text) or csv_to_json. It also says nothing about the two-step payment flow as a usage prerequisite; only the schema covers that.
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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