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set_watch

Register a standing server-side watch (FREE, needs a key; idempotent upsert by client_key — re-registering replaces the watch and resets arming). kind='price': advisory µUSD threshold (asset_id, op gte/lte, threshold_usd_micro). kind='target': size-aware surrogate — would swapping amount_in of asset_in→asset_out deliver ≥ min_out? (margin_bps haircut, default 30; NO quote is run). Edge-triggered one-shot; re-arms after rearm_bps retreat + cooldown_s; ttl_s auto-expiry (default 86400) — refresh by re-upserting. Fires are numbers-only HINTS: re-quote with get_quote. Events push over SSE at GET /watches/stream (outside MCP); from MCP, poll list_watches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
opNo
kindYes
ttl_sNo
api_keyNo
min_outNo
asset_idNo
asset_inNo
amount_inNo
asset_outNo
rearm_bpsNo
client_keyYes
cooldown_sNo
margin_bpsNo
threshold_usd_microNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.6/5.0
Behavior5/5

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

Without annotations, the description carries the full burden and succeeds: it discloses idempotent upsert behavior, edge-triggered one-shot, re-arm conditions, TTL auto-expiry, and that no quote is run for the target kind. It also notes the FREE key requirement and SSE streaming endpoint outside MCP.

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

Conciseness4/5

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

The description is dense but each clause adds necessary detail for a complex 14-parameter tool. It is front-loaded with the core action and then elaborates. While long, it avoids redundancy and stays structured.

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?

For a tool with no annotations and many parameters, the description covers the operation, both kinds, parameters, lifecycle (re-arm, TTL), and how to consume events (SSE vs polling). This is sufficient for an agent to invoke it correctly, especially with an output schema present.

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

Parameters4/5

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

Schema coverage is 0%, so the description must compensate. It names most relevant parameters grouped by kind: asset_id, op, threshold_usd_micro for price; amount_in, asset_in, asset_out, min_out, margin_bps for target; plus client_key, rearm_bps, cooldown_s, ttl_s. It omits explicit mapping of api_key (though 'needs a key' implies it) and doesn't enumerate default values for all params, but the coverage is strong.

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 opens with 'Register a standing server-side watch' and then details two kinds (price/target), making the operation clear. It distinguishes from siblings by stating that fires are hints and that get_quote should be used for re-quoting, and list_watches for MCP polling. This is a specific verb+resource with clear scope.

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 explains when to use the tool (to set up standing watches) and contrasts with get_quote ('Fires are numbers-only HINTS: re-quote with get_quote') and list_watches ('from MCP, poll list_watches'). It does not explicitly state exclusions (e.g., 'use get_quote for immediate quotes') but implies them through the hint/re-quote guidance.

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

A3.9/5.0
Disambiguation5/5

Each tool has a clear, distinct purpose: quoting vs building swaps, managing watches, handling payments, registration steps, and LP valuation. Even related tools like get_credit_offer and pay_x402_invoice are clearly separated as 'create offer' vs 'pay invoice'. No two tools appear to duplicate functionality.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case, using verbs like get, list, build, set, delete, pay, register, verify, value. Read operations are consistently divided into get_ (single item) and list_ (collections), and the rest are action-oriented. This makes the API predictable and easy to navigate.

Tool Count5/5

With 12 tools, the server covers its main domains—swap quoting/building, payment, credit management, watch management, agent registration, and LP valuation—without unnecessary bloat. Each tool earns its place, and the count fits comfortably within the typical 3-15 tool range for a well-scoped server.

Completeness4/5

The tool set covers core workflows end-to-end: quote to swap, credit top-up to payment, watch registration to listing/deletion, and two-step agent registration. Minor gaps exist, such as no dedicated get_watch (though list_watches covers it) and no way to inspect past transactions or offers, but agents can work around these without major friction.