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brain_account_statement

Generate a patron's account statement at this operator.

Returns the patron's purchase history, active credit tranches, per-tool usage breakdown, and recent daily usage logs. This is the patron's spending account — not the operator's Authority tax balance.

Free — no credits consumed. Proof of npub ownership is required to prevent statement-scraping of arbitrary patrons.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoNumber of days of daily usage history to include (default 30).
npubYesThe patron's Nostr public key (npub1...).
dpop_tokenYesRaw JSON of a kind-27235 Nostr event signed by npub — not base64, not NIP-98 'Authorization: Nostr <b64>' framing. Its `u` tag must hold THIS tool's exact name (from tools/list), not the endpoint URL; content:"", created_at within 60s of now, and a random `nonce` tag recommended. Or a cached dpop_token phrase.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations, the description carries full burden. It states that the tool is free ('no credits consumed'), requires proof of npub ownership, and explains the anti-scraping motive. It also clarifies data scope (purchase history, credit tranches, etc.) and what it is not (Authority tax balance), providing strong behavioral transparency.

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?

Three sentences, each serving a purpose: the first states the function and contents, the second clarifies scope vs Authority tax balance, the third covers cost and auth. No filler or repetition.

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?

Complexity is moderate with 3 params and an output schema present. Description covers return contents, cost, authentication requirement, and scope distinction. Given the output schema handles detailed return structure, no significant gaps remain.

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?

Schema coverage is 100%, so the schema already documents all three parameters (days, npub, dpop_token) thoroughly. The description adds only general mention that proof of npub ownership is required (matching dpop_token) and doesn't add per-parameter semantics beyond the schema's detailed dpop_token documentation.

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?

Description opens with 'Generate a patron's account statement at this operator' – a specific verb and resource. It enumerates contents (purchase history, credit tranches, per-tool usage breakdown, daily usage logs) and explicitly distinguishes from Authority tax balance, which differentiates it from sibling tools like brain_check_authority_balance.

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 provides context: it's for the patron's spending account, not the operator's Authority tax balance, and notes that proof of npub ownership is required. This implies when-not and a prerequisite, but it doesn't name alternative tools for the excluded case (e.g., brain_check_authority_balance) or state explicit 'use this when' scenarios.

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.