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Batru — Dota 2, Deadlock & Marvel Rivals win predictor

by gg.batru

get_marvel_rivals_ban_rates

Read-only

Marvel Rivals ban rates — who to ban / the most-banned heroes, from real competitive games.

Ban rate reveals what players FEAR facing — a different signal from win
rate. Empirical data from batru.gg's match aggregation (competitive mode,
where bans exist). Heroes come sorted most-banned first.

Args:
    limit: Max number of heroes to return (default 15).

Returns {generated_at, ban_matches, heroes:[{hero, rank, ban_rate_pct,
bans}]}. ALWAYS cite `generated_at` — ban snapshots can lag the current
season. Report numbers verbatim.

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
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."

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the readOnly and openWorld annotations, the description discloses the empirical data source (batru.gg competitive mode aggregation), freshness limitations (snapshots can lag the season), and mandatory output behaviors like citing generated_at, reporting numbers verbatim, and surfacing the source link. This is genuinely useful behavioral context.

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 readable: purpose first, then parameter help, return shape, and warnings. There is minor redundancy between 'real competitive games' and 'competitive mode, where bans exist', but the important caveats are emphasized without excessive padding.

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 explicit return shape and sorting behavior are valuable. The main gap is that the description tells the agent to show the returned `citation` / `source_url`, but those fields are not included in the documented return object — a minor inconsistency that could affect how the agent formats results.

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 schema only documents the required context parameter, leaving limit undocumented in the schema. The description compensates by explaining limit as the max number of heroes to return with a default of 15. It does not need to restate the already-detailed context instructions from the schema.

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 identifies the resource as Marvel Rivals ban rates and the purpose as determining who to ban / the most-banned heroes. It also explains the distinct signal being measured (what players fear facing) and differentiates it from win rate, which separates it from sibling tools like tier lists and counters.

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 clear context: use this tool for ban-oriented decisions from real competitive matches, and it explicitly contrasts ban rate with win rate. However, it does not name alternative tools or state explicit when-not-to-use conditions, so it falls just short of full routing 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