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CASE STUDY

03/Work, selected

06 / 08

VCT Scout

Ask in plain English, get a Valorant roster. Second place worldwide.

What I ownedOwnership: Core contributor on a team build

One of four on a hackathon team. I designed the agent’s tool calling and wrote the system prompt that orchestrates it, plus the tools that save and load a team composition; teammates built the chat backend, the player-data tools and the map tools.

2ndPlace overall

Year
2024
Role
Generative AI layer: system prompt and tool design
With
AWS x Riot Games hackathon
Category
Hackathon

01/The problem

Scouting a pro roster means drowning in match data.

Esports managers cannot read 4,700+ raw match files to build a roster. The insight is in there, but nobody has the time to dig it out.

02/What I built

An agent that turns one sentence into a five-player roster.

  1. 01

    Four of us built it in a hackathon sprint on Amazon Bedrock.

  2. 02

    Lambda and SQS convert match JSON to JSONL so Athena can query it. Claude’s tool API links those tables to a Bedrock Knowledge Base of agents, abilities and gameplay.

  3. 03

    The hardest bug was Athena’s 30 minute limit. We fixed it by splitting queries per tournament and building intermediate tables.

  4. 04

    A manager types something like a request for an aggressive duelist and gets a roster grounded in real stats.

  5. 05

    My layer sits on top: the system prompt that says when to call which tool and how to present a roster, and tools that save and fetch a versioned team composition, so a follow-up question edits the roster instead of rebuilding it.

03/Architecture

Plain English in, tool calls out, a roster back.

The manager asks a question, Claude picks tools, typed arguments become Athena queries over player tables built from 4,700+ match files, and the Knowledge Base supplies game context.

01Esports manager02React and Cognito03API Gateway04Claude tool-useloop on Bedrock05Knowledge Base06Athena07S3 game logs08Lambda and SQS ingest

04/Outcomes

Second out of 3,200+ participants.

  1. 2nd

    Place overall

    Among more than 3,200 participants. Prize pool was $61,000 across three teams.

    Third partySource: press.aboutamazon.com

  2. 1

    Best Cross‑Regional Team Submission

    A separate award the team also won.

    Third partySource: press.aboutamazon.com

  3. 4,700+

    Match files queried

    The size of the data the team restructured so Athena could answer in time, not a measure of accuracy.

    Self-reportedSource: devpost.com

Check these in the ledger

05/Production notes

Behind the numbers

All receipts for this project
What I wrote

I wrote the system prompt that orchestrates the agent and the tools that save and load a team composition. Rudra Sett built the chat backend and the player-data tools, and Aravind Dasarathy wrote the map tools.

Guardrails

The model never writes SQL. It fills typed arguments (region, tournament, agent) and a Lambda holds the Athena query. The save tool’s schema asks for exactly five players, no repeated player or agent, and one in-game leader. Those data tools are Rudra’s.

What broke
  • Athena’s 30-minute limit. Queries over 4,700 match files timed out. The team split them by tournament and built intermediate tables.
  • An unclosed tag. The agent’s visible steps are tags it writes into its reply. I added an explicit rule to the system prompt to close one before opening the next.
Evaluation

Not measured

A hackathon build: no test set, and no evaluation of whether a quoted stat matches the data.

06/Stack

Built with

  • Amazon Bedrock
  • Claude tool use
  • Knowledge Bases
  • Athena
  • Lambda
  • SQS
  • API Gateway
  • DynamoDB
  • React
  • Vite
  • Cognito