x402-cbor
x402-cbor: 手写 CBOR(RFC 8949)编码/解码(无外部依赖)。encode 输出 base64,decode 输入 base64 → JSON。
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| op | No | Op to process | |
| json | No | Json to process | |
| text | No | Text to process | |
| base64 | No | Base64 to process |
x402-cbor: 手写 CBOR(RFC 8949)编码/解码(无外部依赖)。encode 输出 base64,decode 输入 base64 → JSON。
| Name | Required | Description | Default |
|---|---|---|---|
| op | No | Op to process | |
| json | No | Json to process | |
| text | No | Text to process | |
| base64 | No | Base64 to process |
Changes observed during successful MCP inspections.
Input schema / properties / base64Added value: +{
+ "description": "Base64 to process",
+ "type": "string"
+}Input schema / properties / jsonAdded value: +{
+ "description": "Json to process",
+ "type": "string"
+}Input schema / properties / textAdded value: +{
+ "description": "Text to process",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It does note dependency-free implementation and input/output encoding formats, but it says nothing about error behavior, size/rate limits, determinism, or what happens with malformed base64/CBOR. The input schema also lacks required flags or enum constraints, leaving significant operational ambiguity.
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 compact sentence with no filler, front-loading the core purpose and format contract. The leading 'x402-cbor:' token is mildly redundant but the remainder is efficient.
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?
Despite the tool having 4 parameters with no required/enum constraints and no output schema, the description is extremely terse. It omits how to invoke encode vs decode, what the required parameters are, and what the return shape looks like, which is inadequate for an agent to reliably call this tool from description alone.
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 descriptions exist but are generic placeholders ('Op to process', 'Json to process', etc.) that provide no real meaning. The description partially compensates by specifying base64 for encode output and base64→JSON for decode, but it never explains how the 'op' parameter selects encode vs decode or how 'json'/'text'/'base64' map to the operations.
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 states a specific resource and verb: hand-written CBOR (RFC 8949) encoding/decoding with no external dependencies, plus the output/input formats (base64 for encode output, base64→JSON for decode). This clearly distinguishes it from siblings like x402-msgpack, x402-bson, or x402-base64, though the 'x402-cbor:' prefix merely echoes the tool name.
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?
There is no explicit guidance about when to use this tool versus alternatives (e.g., other serialization tools), no mention of the 'op' parameter values needed to trigger encode vs decode, and no preconditions or exclusions. The agent is left to infer usage from the terse format notes.
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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