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tokenintel_match_event_replay

Event-by-event reaction tape for a single match: each goal/red card with its minute, running score, scoreline state, and the market-adjusted token reaction at +15/+30/+60m (plus pre-event drift). The non-reconstructable moat artifact. match_id selects that fixture; token (+ optional date) resolves ONE fixture (the date-selected or most recent) and returns its tape, match metadata, and an other_matches index. Events are never merged across fixtures.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoOptional YYYY-MM-DD; with token, selects that day's fixture instead of the most recent.
tokenNoToken symbol — resolves its most recent (or date-selected) measured fixture.
match_idNoThe matches.match_id (e.g. 'apifb_1391197').

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries full burden. It discloses that the tool returns a tape, match metadata, and an other_matches index, and states that events are never merged across fixtures. It implies read-only behavior (data retrieval), but could be more explicit about non-destructive nature. The description adds good behavioral context beyond a simple 'get data'.

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 four sentences long, front-loaded with the core purpose, and every sentence adds value. No fluff or repetition. It efficiently conveys the tool's function, input, and constraints.

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?

Given the tool has no output schema, the description adequately explains what is returned (tape with per-event details, match metadata, other_matches index). It also covers parameter options and constraints. For a specialized tool with three optional parameters, the description is complete.

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?

Schema coverage is 100%, so baseline is 3. The description adds meaning by explaining how parameters interact: match_id selects a specific fixture, while token+optional date resolves the most recent or date-selected fixture. This clarifies usage beyond the individual parameter descriptions.

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 'Event-by-event reaction tape for a single match,' specifying the verb (replay), resource (match events), and details like goals, red cards, running score, and token reactions. It distinguishes from siblings by labeling it a 'non-reconstructable moat artifact' and explaining its one-fixture resolution.

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

Usage Guidelines3/5

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

The description explains how to use parameters (match_id vs token+date) and that events are never merged across fixtures, but it does not explicitly state when to use this tool over siblings like tokenintel_event_reaction_profile or tokenintel_match_impact_history. The guidance is implicit, not directive.

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

A4.2/5.0
Disambiguation5/5

Every tool targets a distinct aspect of fan token intelligence (e.g., briefing, DEX depth, whale flows, event reactions). Detailed descriptions and usage notes (e.g., 'USE THIS for ...') clearly differentiate overlapping areas like token_context vs briefing.

Naming Consistency5/5

All tools follow a consistent 'tokenintel_<descriptive_name>' snake_case pattern. The prefix is uniform, and names like 'tokenintel_goal_direction_asymmetry' or 'tokenintel_dex_liquidity' are predictable and clear.

Tool Count4/5

22 tools is on the higher side but justifiable given the broad scope (market, sports, DEX, social, whale flows, meta-tools). The server covers many complementary functions without feeling bloated, though a few tools could potentially be merged.

Completeness5/5

The tool set covers the full lifecycle of fan token intelligence: overview (briefing), deep dive (token_context), prices, DEX analysis, whale flows, sports event reactions, social sentiment, health metrics, capital rotation, macro context, and even meta-tools (discover, describe, invoke). No obvious gaps for the stated purpose.

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