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Batru — Dota 2, Deadlock & Marvel Rivals win predictor

by gg.batru

predict_deadlock_draft

Read-only

Which team wins this Deadlock 6v6 comp — CALIBRATED win probability for any draft.

Backed by batru.gg's Deadlock production model. Provide 6 heroes per team
(names are normalised to Deadlock hero ids internally). A reported 60%
reflects a real ~60% empirical win rate — it is calibrated, not a guess.

Args:
    team0_heroes: Team 0's 6 heroes (names/aliases).
    team1_heroes: Team 1's 6 heroes (names/aliases).

Returns calibrated win-rate percentages for both teams. Report verbatim.

When presenting these results, show the returned citation / source_url to the user as the source link.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextYesExplain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization."
team0_heroesYes
team1_heroesYes

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context: the model is production-backed and calibrated ('not a guess'), hero names are normalized internally, and the returned citation/source_url must be shown to the user. This goes well beyond what the annotations alone provide.

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 well-structured and front-loaded: the first sentence is a clear summary, followed by calibration context, args, and return instructions. Each section earns its place, though the Args list could be tightened and integrated with the schema to reduce redundancy.

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?

With no output schema, the description adequately covers what the tool returns (calibrated win-rate percentages), the need to report verbatim, and source-link presentation. The only meaningful gap is the missing `context` parameter in the description, which is required by the schema but not surfaced.

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?

The description adds useful meaning for team0_heroes and team1_heroes (6 heroes, names/aliases, internal normalization), which is important given only 33% schema coverage. However, the required `context` parameter is entirely omitted from the Args section, creating an incomplete picture of the calling contract and relying on the schema to fill a significant gap.

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 states a specific verb ('predict'), resource ('Deadlock 6v6 comp' draft), and outcome ('calibrated win probability'), clearly distinguishing it from sibling tools like get_deadlock_matchup or tier-list utilities. The phrase 'for any draft' plus 'Provide 6 heroes per team' removes ambiguity about what this tool does.

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 clearly implies when to use this tool: when the user has two 6-hero Deadlock teams and wants a calibrated win-rate prediction. It does not, however, explicitly name alternatives or state when not to use it, so it stops short of the highest level of 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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TDQS

A3.6/5.0
Disambiguation4/5

Most tools are clearly separated by game prefix and metric family (tier list, counters, matchup, synergy, momentum, ban rates), so an agent can generally pick the right one. A few close pairs—counters vs. matchup and recommend vs. predict/batch—have adjacent purposes, and get_more_tools is a vague catch-all, so it is not quite a perfect 5.

Naming Consistency4/5

With a few exceptions the set follows a consistent get_<game>_<metric> / predict_* / recommend_* snake_case pattern. Deviations such as predict_dota_winrate instead of predict_dota_draft, predict_dota_winrate_batch, lookup_hero, and get_more_tools break the otherwise tidy pattern.

Tool Count2/5

32 tools is above the 25+ threshold and makes the server heavy even though the tri-game structure is logical. Many parallel families could be parameterized by game, and get_more_tools adds count without a clear domain purpose.

Completeness4/5

The read-only analytics surface is broadly complete: every game has tier lists, counters, matchups, synergies, momentum, draft prediction, and pick recommendations, plus Dota tournament coverage and a model track record. Gaps are minor—Dota lacks ladder ban rates, Deadlock and Marvel Rivals lack tournament stats and model evaluation ledgers, and their draft advice is only heuristic until six heroes are provided.

Resources