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LION - Trend Intent MCP + Marketplace Visibility Audit

lion_trend_intent_signal_csv

Hardware-wallet buyer-intent + self-custody onboarding-friction intelligence as flat CSV. Same column set as the JSON variant: Ledger vs Trezor comparison demand, Bitcoin-only wallet research, under-$100 wallet shopper queries, DeFi hardware-wallet intent, decision-stage crypto purchase research. Optimised for spreadsheet / pipeline ingestion and affiliate-routing or comparison-research workflows. Pay $0.01 USDC on Base mainnet via x402 at the paid route. tools/call returns payment-required metadata only; settle the invoice at the paid route to fetch the CSV.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full transparency burden. It clearly discloses the payment requirement ($0.01 USDC via x402), that tools/call returns only payment-required metadata, and that settling the invoice fetches the CSV. It does not mention potential rate limits or errors, but for this type of data tool the disclosed traits are sufficient.

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?

The description is moderately long but each sentence delivers useful information: purpose, content, use cases, payment, and call behavior. It is front-loaded with the core purpose and avoids fluff. Slight redundancy in mentioning 'flat CSV' twice, but overall efficient.

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 no output schema or annotations, the description is fairly complete. It covers what data is included, the CSV format, the intended workflows, and the exact payment/fetch flow. It does not provide an example of the CSV rows or headers, but the column names listed give a clear picture. This is adequate for invoking the tool.

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 has zero parameters, so the baseline is 4. The description adds detail about the column set (Ledger vs Trezor, Bitcoin-only wallet research, etc.), which informs what the returned data will contain, even though it is not about parameters per se. This adds value beyond the empty schema.

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 that the tool provides hardware-wallet buyer-intent and self-custody onboarding-friction intelligence as a flat CSV. It distinguishes from the sibling JSON variant by explicitly mentioning 'Same column set as the JSON variant' and the CSV format, leaving no ambiguity about the resource and output type.

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 gives context on when to use it: 'Optimised for spreadsheet / pipeline ingestion and affiliate-routing or comparison-research workflows.' It also references the JSON variant as an alternative, but does not explicitly say 'use JSON instead' or list exclusions, so it stops short of fully explicit when-not guidance.

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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TDQS

A3.9/5.0
Disambiguation2/5

The adaptive_data_query and base_dex_signals_json overlap heavily on DEX data, and the two trend_intent_signal tools are identical except for output format, making it unclear which to use for a given task.

Naming Consistency3/5

All tools share the 'lion_' prefix and use snake_case, but the suffix pattern is inconsistent (query, signals_json, audit, signal_csv, signal_json), so naming is only partially predictable.

Tool Count4/5

Five tools is within the reasonable range, but the redundant format variants (CSV/JSON) and overlapping query/signal tools make the effective scope smaller than the count suggests.

Completeness2/5

The server claims to cover trend intent and marketplace visibility audit, yet the tools only provide DEX data, buyer-intent signals, and payment-term checks. There are clear gaps for a dedicated visibility audit and no lifecycle coverage for any specific resource.

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