brain_oracle_lookup_member
Look up a DPYC community member by npub. Free.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| npub | Yes |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Look up a DPYC community member by npub. Free.
| Name | Required | Description | Default |
|---|---|---|---|
| npub | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
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 only notes 'Free' and the lookup action, but does not disclose whether it is read-only, rate limits, authentication needs, or any other behavioral traits that could affect the agent's decision.
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 extremely concise: two short sentences with zero fluff. It delivers the core purpose and a notable benefit ('Free') efficiently.
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 is simple with one parameter and an output schema that presumably covers returns. However, given no annotations, the description is relatively thin on behavioral context and usage alternatives. It is adequate but leaves gaps in when/how to use it.
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?
The description clarifies that the 'npub' parameter is the identifier used to look up the member, which adds meaning beyond the bare schema. However, it does not explain the format (e.g., bech32) or acceptable values, given the schema description coverage is 0%.
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 action ('Look up') and the specific resource ('DPYC community member'), with the key identifier ('by npub'). It distinguishes this tool from siblings by scoping to DPYC community members, and the addition of 'Free' provides extra clarity.
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 usage context is implied: use this tool when you need to look up a DPYC community member by npub. However, there is no explicit guidance on when to use this over alternatives, nor any exclusions or alternative tool references.
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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