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Batru — Dota 2, Deadlock & Marvel Rivals win predictor

by gg.batru

get_dota_tournament_stats

Read-only

TI / EWC pro tournament stats — actual most-picked, most-banned and win rates per hero.

Answers questions like "most picked / most banned / most contested heroes
at TI 2026", "first-pick or Radiant win rate at the event", "what does
team X pick", "group standings", "who won". Numbers are computed from the
official drafts of every recorded game (via OpenDota) and refresh
automatically while an event runs — these are REAL tournament results, not
model output, so win rates here are small-sample records, not calibrated
probabilities.

Covered events: The International 2026 ("ti-2026", completed Aug 23 —
won by Team Spirit, 3-2 over TEAM VISION in the grand final after a
lower-bracket run), Esports World Cup 2026 Dota 2
("esports-world-cup-2026", completed, won by PVISION), Esports Nations
Cup 2026 ("esports-nations-cup-2026", upcoming, Nov 2-8). Common aliases
(ti, ewc, enc, nations-cup) work.

Args:
    event: Tournament slug or alias (default "ti-2026").
    limit: Max hero rows returned, most contested first (default 15).

ALSO the bracket/tree view and the discovery entrypoint: every playoff
series carries a `stage` label ("Upper bracket final", "Lower bracket
semifinal", "Grand final", ...) plus both team names, the score and an
"in progress" status — so call THIS first to learn which teams exist and
who is playing the final/semifinals, then drill into a single game with
get_dota_tournament_game_stats (it accepts the same stage wording).
Bracket slots not yet played don't appear as rows; infer upcoming
pairings from the latest completed stages.

Returns {event, dates, location, status, as_of, coverage, aggregates:
{first_pick_win_rate_pct, radiant_win_rate_pct, heroes_contested},
hero_stats:[{hero, picks, bans, contests, contest_rate_pct, wins, losses,
win_rate_pct}], team_top_picks, standings_group_stage, playoff_results,
source_url, citation}. Include the citation when presenting results.

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eventNoti-2026
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

A4.8/5.0
Behavior5/5

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

The annotations already mark the tool as read-only, and the description enriches this by clarifying that numbers are computed from official drafts, are 'REAL tournament results, not model output', refresh automatically, and should be treated as small-sample records rather than calibrated probabilities. It also discloses that unplayed bracket slots do not appear as rows, guiding correct interpretation of results.

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 long, but every section earns its place: the opening states purpose, the second paragraph adds data provenance and caveats, the third defines event coverage and parameters, and the final paragraphs explain return shape and navigation guidance. The front-loaded first sentence gives immediate clarity, though the later sections could be more tightly compressed.

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?

With no output schema present, the description compensates by enumerating the full response shape, including `aggregates`, `hero_stats`, `team_top_picks`, `standings_group_stage`, and `playoff_results`, and by instructing the agent to include the citation. It also covers event statuses, bracket inference, and sibling-tool routing, making it complete for a complex tournament-stats tool.

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 description coverage is low at 33%, but the description compensates by explaining the `event` parameter in detail (valid slugs, covered events, aliases, default 'ti-2026') and `limit` (max hero rows, most contested first, default 15). The `context` parameter is not mentioned in the description, but the schema already provides a thorough explanation and example for it, so the gap is minor.

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 opens with a specific verb-resource pair: 'TI / EWC pro tournament stats — actual most-picked, most-banned and win rates per hero.' It clearly distinguishes this tool from the sibling get_dota_tournament_game_stats by naming that tool as the drill-down follow-up, so an agent can select between them without ambiguity.

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

Usage Guidelines5/5

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

The description explicitly states when to use this tool first ('call THIS first to learn which teams exist and who is playing the final/semifinals') and when to switch to the sibling tool ('then drill into a single game with get_dota_tournament_game_stats'). It also gives concrete event slug examples and aliases, making invocation decisions unambiguous.

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.

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