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Onvexia — Crypto Fundamentals, Sentiment & Onchain Tracking

by com.onvexia
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Narrative · Rotation

get_narrative_rotation
Read-onlyIdempotent

Which crypto narrative is GAINING or LOSING attention share, with a liquidity confirmation leg.

    Compares the last `days` against the equally long window immediately
    before. Covers the 2026 narrative set — RWA, tokenized equities and
    treasuries, stablecoins, DePIN, perp DEXs, prediction markets, AI agents
    — as well as DeFi, NFT, Gaming and the L1/L2 split.

    READ `vocabulary_stale` BEFORE QUOTING ANY DELTA. When true, the corpus
    spans two keyword vocabularies and a narrative whose keywords were just
    added will appear to be rising purely because only recent posts were
    ever tested against them. That is a rotation signal manufactured by a
    deploy, not by the market.

    A narrative with `unconfirmed: true` has measured attention and NO
    liquidity confirmation — the confirmation is absent, not zero, and the
    row states why.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
include_legacyNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior5/5

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

Beyond the read-only annotations, the description discloses two important behaviors: the `vocabulary_stale` artifact that can manufacture false rotation signals, and the semantics of `unconfirmed: true` where confirmation is absent rather than zero. These interpretive caveats are exactly the kind of context annotations cannot express.

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 front-loaded with the core purpose, then organized into focused paragraphs for scope, the vocabulary caveat, and the unconfirmed-confirmation caveat. There is no filler, repetition, or restating of annotations.

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?

For a read-only tool with two optional parameters, the description covers windowing logic, coverage scope, and critical output-field caveats, while annotations cover safety. The main gap is the unexplained `include_legacy` parameter and the lack of any response envelope detail, but the core invocation contract is sufficiently clear.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must explain parameters. It clarifies `days` by defining the equal-length prior window comparison, but `include_legacy` is never tied to a concrete meaning, leaving the agent to guess what legacy narratives are included or excluded.

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 opening sentence states a specific, measurable purpose: identifying which crypto narratives are gaining or losing attention share with a liquidity confirmation leg. It further defines the comparison-window method and the covered narrative set, making it clearly distinct from siblings like get_narrative_clusters or get_social_dominance.

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

Usage Guidelines2/5

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

No guidance is given on when to choose this tool over related narrative, sentiment, or social-dominance tools. The only strong usage advice, reading `vocabulary_stale` before quoting deltas, affects interpretation of results rather than tool selection.

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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