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Onvexia — Crypto Fundamentals, Sentiment & Onchain Tracking

Signal integrity · Bot detections

get_bot_detections
Read-onlyIdempotent

Accounts flagged as automated or coordinated, with the behavioural evidence. Volume from these should not be read as organic attention.

    READ `coverage` AND `note` BEFORE YOU READ THE LIST. No scorer is
    currently running, so `bot_probability` is NULL for every account and
    this list comes back EMPTY. An empty list here says nothing whatsoever
    about how clean the corpus is — it means nobody has been scored yet,
    and the response says so explicitly in `note`.

    `coverage.accounts_scored` vs `accounts_total` is the honest number:
    while the first is 0, treat this tool as reporting our coverage, not
    the market's cleanliness.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the annotations, the description discloses critical behavioral quirks: bot_probability is NULL, the list is currently empty, and an empty result is not evidence of a clean corpus. It also explains the semantic meaning of coverage fields, which is exactly the type of context that helps an agent avoid misinterpreting results.

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 longer than typical but each sentence adds important interpretative guidance. The warning about reading coverage and note first is front-loadedfake, and the repetition about empty lists reinforces a critical caveat, though it could be tightened slightly without losing meaning.

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?

For a parameterless tool with no output schema, the description covers the key output fields, the empty-list behavior, and the correct interpretation. There is no obvious missing context that would prevent an agent from invoking or understanding the tool correctly.

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, and the schema coverage is 100%, so there are no parameter semantics to describe. The description appropriately focuses on output interpretation instead of params, satisfying the baseline for parameterless tools.

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 opening sentence clearly identifies the resource and purpose: accounts flagged as automated or coordinated, with behavioral evidence. It is specific enough for an agent to understand the tool's function, but it does not explicitly differentiate from closely related siblings like get_signal_integrity or get_coordinated_campaigns.

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 provides strong contextual guidance: read coverage and note first, interpret empty lists as 'no scoring has run,' and treat coverage as the honest metric rather than market cleanliness. It does not explicitly name alternatives or exclusion conditions, so it stops a grade short of full 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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