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DeepBlueCoding

MCP Dota 2 Match Analysis Server

get_farming_pattern

Analyze a hero's farming pattern using match ID and hero name. Discover camp sequences, power spikes, and farming routes to improve strategy.

Instructions

Analyze a hero's farming pattern with camp sequences, power spikes, and routes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
heroYes
match_idYes
end_minuteNo
start_minuteNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
heroYesHero name analyzed
errorNo
minutesNoMinute-by-minute farming breakdown with camp sequences
successYes
summaryNoSummary statistics
match_idYes
end_minuteYesEnd of analysis range
transitionsNoKey transition points in farming pattern
item_timingsNoWhen items were purchased (for power spike analysis)
start_minuteYesStart of analysis range
level_timingsNoWhen hero reached each level (for power spike analysis)
deaths_in_windowNoNumber of hero deaths during the analysis window
coaching_analysisNoLLM-generated coaching analysis (requires MCP sampling support)
multi_camp_clearsNoEvents where hero farmed 2+ camps simultaneously (stacked/adjacent)
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the analytical nature and key output themes, but does not explain how the pattern is computed, the role of time range parameters, or any prerequisites like replay availability. It adds some context beyond 'analyze' but lacks depth.

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 a single concise sentence, efficiently packs the core purpose and key outputs. No fluff or redundancy. However, it may be too terse given the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With four parameters, zero schema descriptions, and many sibling tools, the description is insufficient. It lacks parameter meanings, usage differentiation, and behavioral details, though the existence of an output schema reduces some burden.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description mentions only 'hero' implicitly without explaining parameter formats or the meaning of start_minute/end_minute. The agent is left without crucial parameter semantics for correct invocation.

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 states the tool analyzes a hero's farming pattern, with specific aspects like camp sequences, power spikes, and routes. It distinguishes from siblings by mentioning these unique outputs, though it does not explicitly name alternative tools.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives. No exclusions or preferred scenarios are provided, leaving the agent to infer usage from the general description.

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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