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aibtcdev
by aibtcdev

tenero_top_losers

Lists top losing tokens by 24-hour price change on Stacks to identify underperforming assets or potential reversal candidates.

Instructions

List top losing tokens by 24h price change percentage on the Stacks ecosystem. Useful for identifying underperforming assets or potential reversal candidates. Powered by the Tenero API (api.tenero.io). No authentication required.

Tip: call earning_opportunities to see how to put your assets to work.

Input Schema

NameRequiredDescriptionDefault
chainNoChain to query: stacks, spark, or sportsfun (default: stacks)stacks
limitNoMaximum number of tokens to return (default: 10, max: 50)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.77.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations present, the description carries the full burden. It usefully discloses 'No authentication required' and the upstream provider (api.tenero.io), which is real added context, but says nothing about result ordering, pagination, rate limits, or data freshness/staleness of the 24h window.

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 core sentence is tight and front-loaded, but the promotional 'Tip: call earning_opportunities...' is off-topic for a market-listing tool and does not earn its place in the definition.

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?

For a simple two-optional-parameter read tool with no output schema, the description is adequate on inputs but never sketches what comes back (token identifiers, price change values, ordering). Without an output schema, one clause on the return shape would materially help an agent decide whether to call it.

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 chain and limit are fully documented in the schema and the baseline of 3 applies. The description adds nothing about parameter behavior, and its 'Stacks ecosystem' framing mildly undersells the chain parameter, which also accepts spark and sportsfun.

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?

States a specific verb and resource ('List top losing tokens by 24h price change percentage') with an explicit scope ('Stacks ecosystem'). It is inherently distinguishable from tenero_top_gainers by direction, though it never names that sibling to make the contrast explicit.

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

Usage Guidelines3/5

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

'Useful for identifying underperforming assets or potential reversal candidates' implies a use case but gives no when-not conditions, no alternative tools, and no guidance on choosing between this and market_summary/gainers/trending_pools. The closing tip points to an unrelated earnings tool rather than a true alternative for this task.

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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