Free. Ask this desk to allow your wallet on its bounties. Use when a call was refused AUTH_REQUIRED or WALLET_NOT_ALLOWED. The owner receives a ticket with your wallet record and decides; once allowed, pay from that wallet as usual, no key needed. [free]
| Name | Required | Description | Default |
|---|---|---|---|
| note | No | Why you want to work this desk (optional). | |
| wallet | Yes | The wallet you will pay from (0x… or base58). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the disclosure burden. It discloses the approval flow, the owner's decision role, and that subsequent payments need no key. It could also mention the immediate outcome of the request, but the provided behavior is otherwise transparent.
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 short and front-loaded with the most important trigger condition. Minor redundancy: 'Free' and '[free]' repeat the same information, so it is not perfectly waste-free.
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?
For a low-complexity tool with two simple parameters and no output schema, the description covers the trigger condition, the workflow, and the post-approval behavior. It does not describe the immediate response or how the caller learns about the owner's decision, but the core calling context is adequately specified.
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 description coverage is 100%, so the schema already documents the parameters. The description adds contextual meaning by clarifying that the wallet is the one used for bounties and that approval is wallet-based rather than key-based, which goes slightly beyond 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 a specific verb and resource: 'Ask this desk to allow your wallet on its bounties.' It clearly identifies what the tool does and is distinct from sibling tools like create_ticket or list_bounties.
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?
Explicitly tells the agent when to invoke this tool: 'Use when a call was refused AUTH_REQUIRED or WALLET_NOT_ALLOWED.' This is a precise trigger condition and leaves little room for mis-selection.
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.
Most tools have distinct purposes, but the presence of three drafting tools (draft_reply, draft_support_reply, propose_resolution) with overlapping functionality may cause confusion. Descriptions help differentiate them, but an agent could still misselect.
Tool names predominantly follow a verb_noun pattern in snake_case (e.g., create_ticket, list_issues). However, a few tools like 'assign' and 'triage' are single verbs, and 'draft_support_reply' breaks the pattern slightly. Overall consistent but not perfect.
16 tools is well-scoped for a customer support server covering ticket management, issue tracking, knowledge base, and changelog. Each tool serves a clear purpose without bloat.
The tool surface covers the core ticket lifecycle (creation, triage, assignment, context, drafting, sending, resolving) and supports issue linking and knowledge base search. Minor gaps like updating ticket details or bulk actions exist but are not critical.