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brain_session_status

Check operator readiness. Returns the operator lifecycle state and clear guidance on what to do next. Free.

Lifecycle states:

  • ready: Operator is warm and fully operational — vault AND pricing model verified. Proceed with tool calls.

  • warming_up: Operator is initializing (cold start). Try a tool call — it will warm up on demand.

  • misconfigured: Persistence rejected a query with a permanent SQL error (permission denied, missing relation). Paid tools will fail until the operator repairs the database — retrying does not help.

  • quota_exceeded: The persistence provider (Neon) answered HTTP 402 — the operator's database has exhausted its compute/storage quota, so the books are locked for billing. Paid tools fail; retrying does NOT help. The operator's Authority must restore capacity (upgrade the plan or wait for the quota reset). Free tools remain available.

  • not_registered: Operator has no Authority relationship yet. Call register_operator first.

  • no_identity: Operator nsec is not configured. Deployment issue.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
patron_npubNoOptional. If supplied, the response includes an ``upstream_oauth`` block with the patron's stored OAuth token expiry (runtime-derived from vault state) so a client can refresh proactively rather than reactively after a stale-token failure.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure. It discloses that the tool is free, and each lifecycle state explicitly describes the implications for other tools (e.g., 'Paid tools will fail', 'retrying does NOT help', 'Free tools remain available'). This provides substantial behavioral context beyond the schema, though it does not cover rate limits or auth details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded, with a brief summary sentence followed by a clean bulleted list of lifecycle states. Each state is explained in a single, information-dense line, and there is no redundant or filler content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers all possible lifecycle states and provides actionable guidance for each, making it complete for an agent to decide whether to call this tool and what to do with its output. The presence of an output schema covers return format details, so the description focuses on the semantics of each state, which it does thoroughly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter (patron_npub) has a thorough description in the input schema, so the tool description's silence on it is acceptable. Since schema coverage is 100%, the baseline score of 3 applies; the description adds no additional parameter meaning but is not required to.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Check') and resource ('operator readiness'), and immediately explains what it returns: lifecycle state and guidance. The enumerated lifecycle states further differentiate it from sibling status tools by focusing specifically on operator readiness.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context on when to use this tool: as a readiness check before proceeding with tool calls. It provides per-state next actions (e.g., 'Call register_operator first' for not_registered, and notes that retrying does not help for misconfigured/quota_exceeded). However, it does not explicitly mention alternative sibling tools or state when not to use it, so a 4 is appropriate.

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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TDQS

B3.3/5.0
Disambiguation2/5

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.

Naming Consistency3/5

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`).

Tool Count2/5

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.

Completeness4/5

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.