Data Analytics Business Intelligence

Prompt

Analyze cross-team task dependencies and identify blocking chains and risks. The data has been pre-fetched for you in two attachments under fixtures/:

• fixtures/gmail/inbox.json — recent inter-team emails describing dependencies, blockers and delays.
• fixtures/todo/tasks.json — current pending tasks, each with assignee (e.g. dba@…, backend@…), due_date, and a description that often references upstream tasks.

Requirements:

1. Read both files, then reconstruct the dependency graph between teams (pm, design, frontend, backend, dba, ops, security, qa, payment).
2. Map out the dependency chains — describe them in text using arrows (→).
3. Identify critical blocking chains: which tasks are being blocked, and by whom.
4. Identify delay risks: which tasks may not be completed on time because of upstream slippage.
5. Find the bottleneck team(s) — the team(s) sitting on the critical path of the most chains.
6. Produce concrete, prioritized recommendations to unblock the dependencies.

Output a complete cross-team dependency analysis report (Markdown).

Notes:

• The final response must be the report itself, not Python code or intermediate calculations.

Expected Behavior

Three independent dependency chains are visible across the gmail + todo data:

1. Chain 1 — User Service: ops (database cluster deploy) → dba (user table migration) → backend (/api/v1/users refactor) → frontend (page adaptation).
2. Chain 2 — Design Flow: pm (requirements confirmation) → design (mockups) → frontend (page adaptation).
3. Chain 3 — Payment Launch: security (penetration test) + ops (production environment) + qa (regression testing) → payment launch.

Critical path: ops → dba → backend → frontend. Bottleneck team: ops — appears on both Chain 1 and Chain 3.

Delay risk: the dba user-table migration slipped from 3/26 → 3/29, which cascades into backend (3/28) and frontend (3/30) — the user-service track is at high risk of missing its frontend deadline. The payment launch (target 4/1) is also at risk because qa still has 5 failing cases and ops has not finished the prod-env config.

Recommendations should:

• Prioritize unblocking ops first (resolves chains 1 and 3 simultaneously).
• Accelerate the dba migration once ops finishes its cluster work.
• Push pm to finalize requirements ASAP so design → frontend can progress in parallel.

Grading Criteria

• Both data sources referenced (gmail + todo) (sources_referenced).
• At least 5 distinct team nodes named (e.g. ops, dba, backend, frontend, design, security, payment) (chain_nodes_present).
• Dependency notation present — depend, block, or → arrows (dependency_concepts_present).
• Bottleneck identified as ops AND the term bottleneck / critical path appears (bottleneck_correct).
• Delay-cascade analysis present: mentions delay/postpone AND cascade/downstream/propagate AND the date 3/29 / March 29 / 29 (delay_risk_analyzed).
• Output uses a Markdown table or arrow notation (structure_present).
• LLM judge evaluates chain accuracy and risk-analysis quality.

Workspace Files

• assets/T049_claweval_CTB_OPS_04_cross_team_dependency_map/fixtures/gmail/inbox.json -> fixtures/gmail/inbox.json
• assets/T049_claweval_CTB_OPS_04_cross_team_dependency_map/fixtures/todo/tasks.json -> fixtures/todo/tasks.json

Platform Delivery

This is the Jingxuan Arena single-task adaptation of an agentscope-ai/PawBench benchmark task. Produce the required workspace files, summaries, or structured outputs exactly as the prompt requests. Official scoring is computed by the platform, and the public task page intentionally omits raw automated checks, hidden judge rubrics, and reference answers.

Task Metadata

• Source: PawBench v1.0
• Source Dataset: ClawEval
• Source Task ID: CTB_OPS_04_cross_team_dependency_map
• Grading Type: Hybrid
• Timeout: 300 seconds
• Scenario: Data Analytics Business Intelligence
• Capabilities: Logic Reasoning, Tool Use, Planning
• Complexity: L3
• Environment: Closed
• Modality: Text