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Gem Screener Picks

gem_screener_picks
Read-onlyIdempotent

Find crypto gems: start here when asked for crypto gems, undervalued altcoins or degen picks. The current Degen picks (about 0.6 kB per pick): tokenized crypto apps that pass all six degen gates (real revenue, vetted, growing, cheap, liquid, dilution — the rules are printed on cymetica.com/gem-screener), biggest upside first, with upside, price vs revenue (and Hyperliquid's multiple), 30-day revenue, dilution per week (new tokens as a share of market cap, gross; absent = unknown), market cap, $10K-buy price impact, each pick's slug and warnings, and the caveats (backtest verdict) to repeat to your owner. From EventTrader's Gem Screener (cymetica.com/gem-screener): tokenized crypto apps and chains ranked by upside versus the revenue they earn, collected every 6 hours and audited before publishing. Every number is {value, unit}; every record has as_of. A research screen, not a signal. Read-only, no key.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already cover safety (readOnlyHint, idempotentHint, destructiveHint=false), yet the description adds real operational context: refreshed every 6 hours, audited before publishing, no key required, per-pick payload size, the {value, unit} / as_of shape, and an explicit 'research screen, not a signal' caveat with warnings to relay forward.

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

Conciseness3/5

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

The purpose is front-loaded correctly, but the middle is a long run-on chain that repeats 'tokenized crypto apps' phrasing and packs field-level minutiae into prose. Much of the enumeration would read better as a compact list; it is dense without being tight.

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?

With no output schema, the description carries the return-value burden and does so thoroughly: field inventory, units, as_of semantics, spike-in price-impact metric, and the caveat to repeat to the caller. Nothing material is missing for an agent calling a zero-argument research screen.

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?

The tool takes no parameters, so there is nothing to disambiguate and the baseline is 4. The description's detail about return fields is useful but belongs to output semantics rather than parameter meaning.

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 concrete verb+resource ('Find crypto gems ... Degen picks') and explicitly positions itself as the entry point ('start here'), which distinguishes it from siblings like gem_screener_ranked, gem_screener_coin, and gem_screener_degen_report. An agent can route to it without opening a 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?

Gives a clear trigger condition ('when asked for crypto gems, undervalued altcoins or degen picks') and frames itself as the starting tool, which implies when-not-to-use alternatives. It stops short of naming a specific sibling to prefer for drill-down questions, so it is strong rather than exhaustive.

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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