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check_fragment_ask

Compare a Fragment asking price to the name's class valuation; a fair/ask ratio of 1.2 or higher indicates the lot is priced below its class valuation.

Instructions

Pre-purchase check: compare a Fragment asking price against the name's class valuation (fair price). Returns the fair/ask ratio — ratio >= 1.2 means the lot is priced below its class valuation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesUsername without @
ask_tonYesAsking price / current bid in GRAM (TON)
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It explains the output (fair/ask ratio) and provides a threshold interpretation (>=1.2 means underpriced). However, it does not disclose error cases (e.g., nonexistent name), side effects, authentication needs, or rate limits. The basic behavior is clear but lacks depth.

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 very concise: two short sentences that front-load the purpose and immediately provide actionable output interpretation. Every word contributes meaning.

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?

Given the tool's straightforward nature (two parameters, no nested objects, no output schema), the description adequately explains the return value and its interpretation. It does not explain what 'class valuation' is, but that is a domain concept the agent might infer. The context is sufficient for a simple check tool.

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% with descriptions for both parameters. The description adds context about 'Fragment asking price' and 'class valuation', but does not clarify what 'class valuation' means or how it is computed. Since schema already covers parameter details, the description provides marginal added value.

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: comparing a Fragment asking price against the name's class valuation and returning a ratio. It uses specific verbs ('compare', 'returns') and identifies the resource (Fragment ask price). It distinguishes from siblings (compare_names, score_name) by focusing on a specific pre-purchase check.

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 indicates when to use the tool ('Pre-purchase check'), but does not explicitly state when not to use it or provide alternatives. It could be improved by mentioning that compare_names or score_name might be used for other purposes, but the context is clear enough.

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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