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zacharytran26

Fantasy-Football-Draft-MCP

separation_report

Assess NFL receiver separation and route efficiency using Next Gen Stats. Get avg separation, YPRR, and TPRR for players with real workloads to find efficient targets for fantasy draft.

Instructions

Separation and route efficiency — the open-data version of a PFF SEP/YPRR table.

avg_separation is NFL Next Gen Stats tracking data: yards of daylight between receiver and nearest defender when the ball arrives. YPRR and TPRR use routes estimated from snap share times team dropbacks. Only players who cleared 250 routes and 50 targets in a season are included, so these are real workloads rather than flattering part-time rates.

Man-versus-zone splits are not reproducible from open data — that needs per-play coverage charting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
positionNoWR
player_nameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals methodology (NFL Next Gen Stats tracking data, estimated routes), inclusion criteria (250 routes, 50 targets), and reproducibility limits. It does not explicitly state side effects or return format, but the report context implies a read-only safe operation. The caveat about man/zone adds valuable transparency.

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 with line breaks, opening with a concise summary then providing necessary methodology and caveats. Each sentence adds value, though it is slightly longer than strictly needed. It is organized for skimming and front-loads the core purpose.

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?

Given the output schema exists, the description need not explain return values. It provides substantial context about the data source, metric definitions, and inclusion thresholds, covering the tool's purpose and limitations. However, it omits any guidance on how to use the parameters, which is a gap given the schema's lack of descriptions. Overall, it is complete for a report tool but not exhaustive.

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 provides no information about the three parameters (limit, position, player_name). While it mentions player thresholds, that does not explain the parameter options. The description fails to compensate for the schema gap, leaving the agent with no guidance on how to configure the query.

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 clearly identifies the tool as a separation and route efficiency report, explicitly comparing it to a PFF SEP/YPRR table. It names specific metrics (avg_separation, YPRR, TPRR) and distinguishes it from sibling tools like rookie_report or defense_report. Although no verb like 'list' is used, the intent is unambiguous and distinct.

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?

The description provides clear context on when to use the tool: when needing separation and route efficiency stats from open data. It also states a limitation (man-versus-zone splits are not reproducible) which serves as a when-not, but it does not explicitly name alternative tools. This is more than implied usage but stops short of offering alternatives.

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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