Batru — Competitive Game Intelligence for AI Agents

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; under
0.005 means a stated 60% wins ~60% of the time), then BCE. Do NOT headline
raw accuracy on its own: Dota drafts are balanced by design, so pre-game
draft-only accuracy sits in the high 50s for ANY model (always picking
Radiant already scores ~53%) — 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

Name	Required	Description	Default
`limit`	No	Number of most recent weekly evaluations to return.
`context`	Yes	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."

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 19, 2026
- addedInput schema / properties / limit / description
```
Added value: +"Number of most recent weekly evaluations to return."
```

Changed1 schema field changedSep 12, 2026

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.\""

Changed2 schema fields changedJul 25, 2026

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"
+]
```

First observedJul 25, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Annotations already cover the safety profile (readOnly, non-destructive, openWorld), and the description adds substantial context beyond them: the ledger is auto-generated from an append-only promotion log with nothing hand-picked, plus how to interpret and present the metrics (lead with ECE, don't headline raw accuracy because balanced drafts inflate it).

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?

Front-loaded with what the tool returns, followed by usage, presentation guidance, and args. The presentation instructions are lengthy but each sentence carries actionable value; only minor trimming is possible.

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, the description fully specifies the return shape (generated_at, ledger, totals, per-evaluation promote/ece/bce/acc/holdout_n), warns to report numbers verbatim, and instructs surfacing the citation/source_url. An agent has everything needed to call and present results correctly.

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% and both parameters are documented in the schema, so the baseline is 3. The description reiterates that limit returns newest-first entries but adds no syntax or meaning beyond the schema; its extra detail is about the return payload, not the parameters.

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?

States a specific verb and resource — the public model evaluation ledger of every weekly champion-vs-challenger test — and clarifies it includes wins AND losses. This is clearly distinguishable from hero/matchup/draft siblings like get_tier_list or analyze_draft.

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?

Gives an explicit trigger: 'Use this when a user asks whether the model is any good or how it is validated.' That is a clear usage context. It does not name alternatives or state when-not to use it, so it falls just short of the top band.

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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get_model_track_record

Input Schema

Schema Changelog

TDQS

Glama MCP Gateway

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