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Batru — Competitive Game Intelligence for AI Agents

by gg.batru
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get_model_track_record

Read-only

Get batru.gg's public model evaluation ledger — every weekly test, wins AND losses.

batru.gg publishes EVERY champion-vs-challenger evaluation of its Dota 2
model (promoted or rejected), auto-generated from the promotion gate's
append-only log — nothing is hand-picked. Use this when a user asks whether
the model is any good or how it is validated.

HOW TO PRESENT IT: lead with CALIBRATION (ECE — lower is better; ~0.006
means a stated 60% wins ~60% of the time), then BCE. Do NOT headline raw
accuracy: Dota drafts are balanced by design, so ~55% is near the
game-imposed ceiling for ANY model — calibration is the meaningful claim.

Args:
    limit: Max evaluations to return, newest first (default 10).

Returns {generated_at, ledger, total_evaluations, total_promotions,
evaluations:[{decided_at, promote, challenger:{ece,bce,acc},
champion:{ece,bce,acc}, holdout_n}]}. 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
limitNoNumber of most recent weekly evaluations to return.
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."

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / limit / description
      Added value: +"Number of most recent weekly evaluations to return."
  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. Changed2 schema fields changed
    • addedInput schema / properties / context
      Added value: +{
+  "description": "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.\"",
+  "type": "string"
+}
    • addedInput schema / required
      Added value: +[
+  "context"
+]
  4. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and destructiveHint, so the safety profile is covered. The description adds that the ledger is auto-generated from an append-only log and nothing is hand-picked, plus presentation rules like reporting numbers verbatim and showing the citation/source_url. 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is longer than average, yet each segment serves a purpose: core action, when-to-use, presentation guidance, argument semantics, return shape, and source-link instruction. It is front-loaded with the core purpose before diving into presentation details.

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?

Despite no output schema, the description enumerates the exact return structure and instructs verbain reporting and source attribution. Together with annotations and full schema coverage for parameters, an agent has everything needed to invoke the tool and interpret results correctly.

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 coverage is 100%, so the baseline is 3. The description clarifies that limit is 'newest first' and defaults to 10, a detail not in the schema, adding a bit of extra meaning. It does not elaborate on the required context parameter, which the schema already defines thoroughly.

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 'Get batru.gg's public model evatility ledger' — a specific verb, resource, and scope. It explicitly states the tool's role: returning every weekly test (wins and losses) and when to use it for model validation queries, distinguishing it from gameplay-analysis siblings.

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 says 'Use this when a user asks whether the model is any good or how it is validated,'which gives a clear trigger condition. It does not name alternative sibling tools or state when not to use it, so it falls short of an exhaustive routing guide.

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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