List unconfirmed AI inferences awaiting human validation. Promote a candidate by ID to accept it as a confirmed note.
List unconfirmed notes (type='candidate') — inferences the agent made that a human has not validated. Pass promote= to accept one.
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | fact | |
| promote | No | candidate id to accept |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It mentions listing and promoting, but does not clarify what happens when 'promote' is used (e.g., does it also return a list? does it mutate state?), nor does it explain the 'to' parameter that appears in the schema but is absent from the description. This incomplete disclosure is a significant gap.
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 sentences with no wasted words. The primary purpose is front-loaded, and the promote action is clearly appended. The structure is efficient and easy to parse.
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?
The tool has no output schema, so the description must explain what the agent can expect from the call. It does not describe the return format, whether promote returns anything, or the behavior when 'to' is set. The unexplained 'to' parameter and lack of return value details make it incomplete for a tool with 2 parameters.
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 50% (only 'promote' has a description). The tool description adds meaning to 'promote' by explaining it accepts a candidate, but it completely ignores the 'to' parameter, leaving its purpose unexplained. The description does not compensate for the missing schema documentation of 'to'.
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 clearly states the verb 'list' and the specific resource 'unconfirmed notes (type='candidate')', with a clear purpose: to show inferences a human hasn't validated. It distinguishes itself from sibling tools by focusing on the candidate type and the promote action, making it unambiguous.
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 when to use it (to list candidates) and mentions the promote action, but does not explicitly state when not to use it or name alternatives. It lacks exclusions or comparisons to sibling tools like search or read, leaving the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.