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opsin_market_preview

Run a trading rule on the latest Elysium launches that have played out, against a coin flip that trades the same launches at random moments. Instant and never signed: a rule can be fitted to the past. Use opsin_market_propose to measure it on launches that do not exist yet.

Input Schema

NameRequiredDescriptionDefault
toSecYesLatest buy, seconds after launch
feePctNoLaunchpad fee each way, percent
fromSecNoEarliest buy, seconds after launch
minBuysNoAt least this many buys since launch
sizeHypeNoHYPE a trade (sets price impact)
stopLossNoSell at this × the entry price
launchpadNoOne launchpad (Montra, ElysPump, BOXA, Volta), or omit for any
maxHoldSecYesSell after this many seconds whatever happens
minBuyHypeNoAt least this much HYPE bought since launch
takeProfitNoSell at this × the entry price
maxMultipleNoPrice at most this × the launch price
minMultipleNoPrice at least this × the launch price

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose that execution is instant, requires no signing, and operates only on already-played-out launches. However it says nothing about the shape of the result or how the rule's performance is reported against the baseline, which is a meaningful gap for a 12-parameter backtest with no output schema.

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?

Three short sentences, front-loaded with the core action and ending with the routing instruction. The clause 'Instant and never signed' is dense but earns its place; the 'coin flip' metaphor is the only mildly ambiguous construction.

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

Completeness3/5

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

Given 12 parameters, no annotations, and no output schema, the definition is reasonably complete on the input side and on when to call it. What is missing is any indication of what a preview result contains or how the rule-versus-baseline comparison is presented, which an agent needs to interpret the response.

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 description coverage is 100%, so every parameter is already documented in the schema, establishing a baseline of 3. The description adds no parameter-level detail beyond noting that entry timing is part of the rule, leaving the schema to do all the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a concrete action -- running a trading rule against the latest completed Elysium launches and benchmarking it against a random-entry ('coin flip') baseline -- which identifies both verb and resource. The scope is clear enough to distinguish it from the live-measurement sibling, though the 'coin flip' phrasing is metaphorical rather than a named object.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly names the alternative, opsin_market_propose, and gives the condition that selects it: use this tool to fit a rule to past launches, use propose to measure it on launches that do not yet exist. The when-to-use boundary is stated without requiring inference.

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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