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LamboPoewert

MadeOnSol — Solana memecoin intelligence

madeonsol_kol_first_touches

Read-onlyIdempotent

Retrieve first-KOL-touch events to identify token mints where top scouts buy first, enabling early trading signals with high follow-on probability.

Instructions

Recent first-KOL-touch events — every time a tracked KOL was the first to buy a token mint. Filterable by scout tier (S/A/B/C from mv_kol_scout_score), KOL winrate, token age, etc. Backtest: top scouts attract ≥3 follow-on KOLs within 4h ~50% of the time vs ~14% baseline. Median lead time before second KOL is 12s — for trading this signal, use the WebSocket channel rather than polling.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of events to return (1-100, default 50)
sinceNoISO timestamp — events strictly newer than this. Polling cursor.
beforeNoISO timestamp — events strictly older than this. Pagination cursor.
kolNoFilter to a single KOL wallet address (base58)
min_kol_winrate_7dNoMinimum 7d winrate of the first-touch KOL (0-100)
min_scout_tierNoRestrict to first-touch KOLs of this scout tier or better. Requires n_first_touches_30d >= 30.
min_n_touchesNoLower the minimum sample size for scout scoring (default 30)
strategyNoFilter by first-touch KOL's auto-tagged strategy
token_age_max_minNoOnly events on tokens younger than N minutes (uses token_first_seen)
min_first_buy_solNoMinimum size of the first KOL buy in SOL
mint_suffixNoSuffix-filter the token mint (e.g. 'pump', 'bonk')
presetNoShortcut filter: 'scout' = min_scout_tier=B + min_n_touches=30 + token_age_max_min=60. 'fresh_launch' = token_age_max_min=15.
includeNoComma-separated includes — currently 'followers_4h' (computed for events >=4h old)
Behavior5/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds valuable behavioral context: events are recent, includes backtest stats about follow-on KOLs, and advises against polling for trading. No contradiction with annotations.

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?

Four sentences: purpose, filters, backtest stat, usage warning. Front-loaded and concise, every sentence adds value.

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?

Description explains purpose, filters, and provides usage guidance and a backtest stat. However, it lacks details about the structure of returned events (e.g., fields per event) since there is no output schema. This omission reduces completeness for an agent.

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 has 100% parameter descriptions. The description lists some filters in prose but does not add significant meaning beyond schema. With full coverage, baseline 3 is appropriate.

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?

Description clearly states it returns 'recent first-KOL-touch events' with a specific verb (get events) and resource (first touches by KOLs). The name and description make it distinct from siblings like 'kol_feed' by focusing exclusively on first touch events.

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?

Description provides good context: lists filters, gives backtest statistic to indicate usefulness, and advises to use WebSocket rather than polling for trading signals. However, it does not explicitly compare to sibling tools or state when not to use it aside from the polling caveat.

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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