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Batru — Dota 2, Deadlock & Marvel Rivals win predictor

by gg.batru

get_deadlock_ban_rates

Read-only

Deadlock ban rates — who to ban / the most-banned heroes, from real ranked games.

Ban rate reveals what players FEAR facing — a different signal from win
rate. Empirical data from batru.gg's match aggregation. 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}]}. `ban_matches` is the sample of matches with ban data; cite
`generated_at` when freshness matters. 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

A4.1/5.0
Behavior5/5

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

Annotations already mark it read-only, and the description adds meaningful behavioral detail: data source (batru.gg), ranked-match provenance, sorted most-banned-first order, sample semantics of ban_matches, freshness/citation guidance, and instruction to report numbers verbatim and show the source link. 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?

The description is front-loaded with the purpose and uses compact Args/Returns sections. Every sentence adds value, including the presentation guidance for source attribution. No wasteful repetition.

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?

In the absence of an output schema, the description explains the return shape and key caveats such as freshness and sample size. It is slightly incomplete because it references returned citation/source_url fields that are not listed in the Returns shape, and it does not mention the required context parameter in prose.

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 limit ('Max number of heroes to return (default 15)'), which the schema does not describe. However, its Args section omits the required context parameter entirely, and with only 50% schema coverage the description only partially compensates for the missing parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the resource as Deadlock ban rates from real ranked games and explains the core use case: who to ban / most-banned heroes. It stops short of a crisp imperative verb, but it is specific enough to distinguish from the sibling stat tools.

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?

It gives clear usage context: use this when ban-related strategy matters and contrasts ban rate with win rate as a different signal. It does not explicitly name alternative tools or state when not to use this tool, so it does not fully reach the top score.

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