x402-bson
x402-bson: 手写 BSON(MongoDB 二进制 JSON)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 | ||
| json | No | ||
| text | No | ||
| base64 | No |
x402-bson: 手写 BSON(MongoDB 二进制 JSON)编码/解码(无外部依赖)。encode 输出 base64,decode 输入 base64 → JSON。
| Name | Required | Description | Default |
|---|---|---|---|
| op | No | ||
| json | No | ||
| text | No | ||
| base64 | No |
Changes observed during successful MCP inspections.
Input schema / properties / base64 / descriptionRemoved value: -"Base64 to process"Input schema / properties / json / descriptionRemoved value: -"Json to process"Input schema / properties / op / descriptionRemoved value: -"Op to process"Input schema / properties / text / descriptionRemoved value: -"Text to process"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 burden. It usefully discloses the input/output encodings (encode emits base64; decode consumes base64 and returns JSON) and the no-dependency trait, but says nothing about error behavior, payload limits, or exactly how 'op' drives the operation.
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?
Two tight sentences that front-load the format and the operation, then add the encoding details. No filler, though the leading tool-name prefix and parenthetical could be trimmed.
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?
With no annotations and no output schema, the description must be fairly self-contained. It covers the format and the encode/decode data flow but omits the meaning of 'op'/'text' and any return-value or error detail, leaving the agent unable to invoke the tool unambiguously.
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 0% with 4 undocumented string params. The description partially maps semantics for 'base64' and 'json', but leaves 'op' (the encode/decode selector) and 'text' completely unexplained, which is a significant gap given the schema provides no help.
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?
States a specific verb+resource: BSON (MongoDB binary JSON) encode/decode, and notes the no-external-dependency implementation. The format is named, which distinguishes it from generic encoders, but it never differentiates from close siblings such as x402-cbor, x402-msgpack, or x402-base64, so an agent gets no routing help between similar binary-format tools.
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 description implies the encode vs decode split and the data flow (encode → base64, base64 → JSON), which functions as light usage guidance. However it never states when to choose BSON over CBOR/MessagePack/base64 alternatives, nor that 'op' selects the direction, so 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.
Add one secure layer between your agents and this server.