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Steel

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90/ 100
A
Score Breakdown90%

Lost points on 2 checks

  • time9/15
  • efficiency3/10
Eval Score (70% weight)87%
cost$0.01 (<$0.05, excellent)+10
time58s (30s–60s, great)+9
efficiency13 tool calls (≤15, good)+3
found docsTouched docs at docs.steel.dev: yes (4 matching tool calls)+10
zero errorsNo errors in tool outputs+5
syntax validCode compiles/parses correctly+5
created filesGenerated files: 2 (need ≥1)+10
full executionMethod: full_execution, Exit: 0+35
Checklist Score (30% weight)100%
Context7
Link+14
llms.txt
Link+14
MCP Server
Link+14
Typed SDK
Link+14
OpenAPI
Link+14
Agent Skills
Link+14
CLI
Link+14

Checklist determined by AI. If something looks wrong, .

Final Score
A: >=90%B: 75-89%C: 55-74%D: <55%
(87 × 0.7) + (100 × 0.3)= 90%
Replay
Using https://docs.steel.dev, complete the following task:

Using Steel, build me a Python script that:

1. Install the Steel Python package
2. Open a browser session
3. Navigate to "https://example.com"
4. Extract the page title and the main heading (h1) text
5. Take a screenshot and save as "screenshot.png" (if supported)
6. Close the session
7. Print results as JSON: {"url": "...", "title": "...", "heading_text": "...", "screenshot_saved": true/false}

Use the official Steel Python library — not raw HTTP calls.
opencode.json

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Run completed Oct 23, 2026, 7:10 AM