Get metadata about an attachment. Requires npub for credit billing.
| Name | Required | Description | Default |
|---|---|---|---|
| npub | No | Required. Your Nostr public key (npub1...) for credit billing. | |
| brain_id | No | The ID of the brain (uses active brain if not specified) | |
| dpop_token | No | ||
| attachment_id | Yes | The ID of the attachment |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for behavioral disclosure. It adds that credit billing applies and npub is required, which is a meaningful side-effect disclosure. However, it does not mention other behaviors such as whether the operation is strictly read-only, pagination, or error cases. The billing mention provides partial transparency.
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 two short sentences: the first gives the core purpose, the second adds a key requirement. It is front-loaded and every word contributes value. No redundancy or verbose phrasing.
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?
Given the tool's simplicity (get metadata) and the presence of a detailed schema (75% parameter coverage) and an output schema, the brief description adequately covers the essential context. It mentions the billing prerequisite and the action. It could be slightly more explicit about the distinction from content retrieval, but the name and sibling context make this inferable.
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 adds no new parameter semantics beyond what the schema already provides. Schema description coverage is 75% (three of four parameters are documented in the schema), and the only parameter it hints at, npub, is already described as required for credit billing. The description does not clarify the undocumented dpop_token, and brain_id and attachment_id are already well-described in the schema.
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 'Get metadata about an attachment' with a specific verb and resource, clearly distinguishing it from sibling brain_get_attachment_content, which likely retrieves content. This gives an immediate, unambiguous purpose.
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 notes 'Requires npub for credit billing,' implying a prerequisite and cost. However, it does not explicitly state when to use this tool versus alternatives like brain_get_attachment_content or brain_list_attachments. Usage context is implied but not made explicit.
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.
Multiple tools have overlapping purposes. For example, `brain_request_credential_channel` and `brain_request_patron_credentials` serve similar roles, and `brain_receive_credentials`, `brain_receive_npub_proof`, and `brain_receive_patron_credentials` all handle receiving data from a courier flow. While descriptions help, the sheer number of tools (83) with similar-sounding purposes (check_ vs get_ vs request_ vs receive_ prefixes) makes it hard to quickly distinguish which tool to use.
The tools mostly follow a `brain_verb_noun` pattern (e.g., `brain_create_thought`, `brain_delete_link`), which provides some consistency. However, there are inconsistencies with prefixes like `brain_oracle_` (e.g., `brain_oracle_about`, `brain_oracle_how_to_join`) which are more like static pages than actions. Additionally, 'check' and 'get' seem interchangeable (e.g., `brain_check_balance` vs `brain_get_thought`), and 'list' is used alongside 'get' in a way that sometimes means the same thing (e.g., `brain_list_brains` vs `brain_get_brain`).
83 tools is an extremely large and unwieldy surface area. While the server aims to be a comprehensive 'operating system' for a specific ecosystem (DPYC/Nostr), this many tools will lead to agent confusion and high latency. Tools like `brain_oracle_about`, `brain_oracle_how_to_join`, and `brain_oracle_network_advisory` could easily be combined into a single tool or served as function parameters.
For its stated domain (managing a 'brain' with credits, payments, and Nostr integration), the tool set is remarkably complete. It covers CRUD operations, payment flows (purchase, check, restore), coupon management, credential handling, and even notarization. Minor gaps are hard to identify, though some flows feel overly complex (e.g., the multiple `request_`/`receive_` patterns could arguably be simplified). The high number of tools is a result of this extreme specialization.