Moby

KOL transaction feed

get_whalewatch_kol_feed

Read-only

Same feed as get_whalewatch_feed but pre-filtered to KOLs — public, named crypto influencers — rather than anonymous whales. The list filter is applied server-side, so there is no list_ids argument. Use this when the user asks what influencers or 'the callers' are buying. For one KOL's trades, use get_whalewatch_feed with its wallet_address. include_context=true adds a per-row context block: pnl_pct_vs_entry (the trade price vs the wallet's own average entry, as a fraction), tags (what the trade looked like, e.g. profit taking), hold_days_at_trade, share_sold_of_position, position_before_usd, entry_vwap_before, days_since_prev_trade + prev_trade_at (how long the WALLET was quiet before this trade, any token) and wallet_win_rate + wallet_realized_pnl_30d_usd (the wallet's 30-day quality). Unknown values are null — pnl_pct_vs_entry is null whenever the wallet's entry was never seen, days_since_prev_trade when Moby has no earlier trade for the wallet. Wallet quality: use get_whale_wallet_track_record(wallet_address) for a wallet's win rate and PnL. This is public market data about the whole market — it is NOT about the user's own wallet or holdings. Tools whose names start with get_my_ are the ones that return the user's own data.

Input Schema

Name	Required	Description	Default
`page`	No	1-based page number.
`limit`	No	Trades per page, 1-100. Keep it small.
`network`	No		solana
`token_address`	No	Restrict to KOL trades in this one token.
`after_timestamp`	No	Only trades after this instant. ISO 8601 UTC, e.g. `2026-08-11T14:30:00Z`.
`include_context`	No	Add the per-row `context` block (position/PnL facts for each trade).
`before_timestamp`	No	Only trades before this instant. ISO 8601 UTC, e.g. `2026-08-11T14:30:00Z`.
`transaction_types`	No	`buy` and/or `sell`. Omit for both. Anything else is rejected rather than ignored — an unrecognised value used to drop the filter and return every row.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 2, 2026

TDQS

A4.9/5.0

Behavior5/5

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

The description goes far beyond the annotations by detailing exactly what the `context` block entails when `include_context=true` (listing fields like pnl_pct_vs_entry, tags, and wallet quality metrics). It also clarifies the behavior of null values and provides external tool references for deeper metrics.

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?

While the definition is very long, it is highly structured and necessary to convey all the complex constraints (usage, data source, contextual fields, and boundary rules). It prioritizes maximum information delivery over brevity.

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?

It provides full context on the data source (public market data), the scope (KOLs vs. whales), and the limitations (not about user holdings), ensuring the agent understands the data constraints of the feed.

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

Parameters5/5

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

Although schema coverage is high (88%), the description adds essential meaning: it defines the purpose of `include_context` as adding a specific, complex per-row block, and clarifies that omitting `transaction_types` returns all rows rather than being ignored.

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 immediately and clearly differentiates this tool from its main sibling, `get_whalewatch_feed`, by specifying it is pre-filtered to KOLs (public, named influencers) rather than anonymous whales.

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

Usage Guidelines5/5

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

It provides explicit guidance on when to use it ('when the user asks what influencers or 'the callers' are buying') and when not to (when seeking a single KOL's trades, use `get_whalewatch_feed` with `wallet_address`). It also draws a critical line between public market data and the user's own private data.

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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