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predict_winrate_batch

Read-only

Score MANY candidate next-picks for a Dota 2 draft in ONE call — calibrated win rate + delta each.

Use this instead of looping predict_winrate over candidates: the whole
batch runs as a single model invoke server-side. For each candidate you
get the CALIBRATED team win rate after adding it, plus the delta vs the
draft without it (a full-roster sweep of up to 150 candidates fits in one
call). Currently dota2-only.

Args:
    my_heroes: Heroes your team already picked (0-4).
    enemy_heroes: Enemy heroes (0-5).
    candidates: Candidate heroes to evaluate (1-150).
    my_side: "radiant" (default) or "dire".
    game: Only "dota2" today.

Returns {baseline_win_rate_pct, candidates:[{hero, shortName,
win_rate_pct, delta_pp}]} sorted best-first. Report verbatim.

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gameNoOnly "dota2" is supported today.dota2
contextYesExplain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
my_sideNoDota 2 only: the side your team plays, "radiant" or "dire". Ignored for deadlock / marvel-rivals.radiant
my_heroesYesHeroes your team already picked (0-4), as a list of hero names.
candidatesYesCandidate heroes to evaluate as your next pick (1-150), as a list of hero names.
enemy_heroesYesEnemy heroes (0-5), as a list of hero names.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changed
    • addedInput schema / properties / candidates / description
      Added value: +"Candidate heroes to evaluate as your next pick (1-150), as a list of hero names."
    • addedInput schema / properties / enemy_heroes / description
      Added value: +"Enemy heroes (0-5), as a list of hero names."
    • addedInput schema / properties / game / description
      Added value: +"Only \"dota2\" is supported today."
    • addedInput schema / properties / my_heroes / description
      Added value: +"Heroes your team already picked (0-4), as a list of hero names."
    • addedInput schema / properties / my_side / description
      Added value: +"Dota 2 only: the side your team plays, \"radiant\" or \"dire\". Ignored for deadlock / marvel-rivals."
    • addedInput schema / properties / my_side / enum
      Added value: +[
+  "radiant",
+  "dire"
+]
  2. Changed1 schema field changed
    • changedInput schema / properties / context / description
      Previous value: -"Explain 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.\""New value: +"Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
  3. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, covering the safety profile. The description adds useful behavioral context beyond the annotations: the entire batch runs as one server-side model invoke, results are calibrated, each candidate includes a delta vs. the draft without it, and up to 150 candidates fit in a single call.

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: a front-loaded summary, explicit usage guidance, a compact Args list, and a return-format line. The Args section is somewhat redundant with the input schema, but for a six-parameter tool it is reasonably sized and the key behavioral points are placed before the redundant details.

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 schema coverage at 100%, no output schema, and annotations covering safety, the description supplies the remaining critical context: return shape, sorting (best-first), delta semantics, batch behavior, and supported game. It is complete enough for an agent to call the tool correctly, though a short example would have made it fully comprehensive.

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?

Schema description coverage is 100%, so the baseline is 3. The description's Args block largely restates schema descriptions (e.g., my_heroes 0-4, candidates 1-150, my_side radiant/dire) without adding new semantic nuance beyond what the schema already documents.

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 action, resource, and scope: "Score MANY candidate next-picks for a Dota 2 draft in ONE call." It names the exact outputs (calibrated win rate, delta) and explicitly contrasts with the sibling predict_winrate, so an agent can immediately distinguish the batch tool from the single-pick tool.

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?

It gives explicit routing guidance: "Use this instead of looping predict_winrate over candidates" and explains why (a single model invoke server-side). It also sets a clear boundary with "Currently dota2-only," telling the agent not to use it for other games despite the enum containing more options.

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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