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place_trailing_order

Ask the user to approve a trailing stop: sell amount tokenIn for tokenOut when price drops trailPercent below its running high since placement. Keeper-executed after signing; always returns an approval link — trailing stops are never executed under an agent grant. For a fixed level use place_stop_order. HUMAN units.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNooptional one-line reason shown to the user (≤ 140 chars)
amountYesamount of tokenIn to sell, HUMAN units, decimal string
tokenInYesERC-20 address being protected / sold when the trail triggers (0x-hex)
tokenOutYesERC-20 address received (0x-hex), usually USDG
expiresInNooptional lifetime like 7d, 30d; default 7d
slippageBpsNoslippage tolerance for the fill in basis points (default 100)
trailPercentYesdistance below the running high that triggers the sell, in percent (e.g. 5 = 5%); 0.1–99

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Adds meaningfully beyond annotations: keeper execution after signing, the fact that it always returns an approval link, and the agent-grant prohibition. These are real operational constraints the annotations (readOnly=false, openWorld=true, idempotent=false) do not convey. Lacks detail on what happens if the user rejects the approval or whether placement can be cancelled later.

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 tight sentences, front-loaded with trigger semantics before the alternative and the approval-link caveat. Every clause adds decision-relevant information, with no restatement of the tool name or filler.

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

Completeness4/5

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

No output schema exists, and the description compensates by stating the tool always returns an approval link. Combined with the agent-grant caveat and sibling routing, an agent has enough to place the order correctly; only post-approval lifecycle details are absent.

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 all seven parameters are already documented in the schema; the description only reinforces the 'HUMAN units' convention and restates the trailPercent meaning. Baseline 3 is appropriate since the schema carries the parameter burden.

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?

States a specific verb (place) and resource (trailing order), then defines the trigger semantics precisely: sell tokenIn for tokenOut when price drops trailPercent below its running high. It also names the sibling it is not (place_stop_order for a fixed level), so the agent can route correctly without opening either schema.

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?

Explicitly routes fixed-level stops to place_stop_order and states a clear limitation: trailing stops are never executed under an agent grant. What is missing is the inverse condition — no guidance on when a trailing stop is preferred over limit/market/DCA siblings beyond the single alternative named.

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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