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Steel

Steel

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79/ 100
B
Score Breakdown79%

Lost points on 4 checks

  • cost6/10
  • time5/15
  • efficiency0/10
  • zero errors0/5
Eval Score (70% weight)71%
cost$0.15 ($0.10–$0.20, great)+6
time132s (120s–180s, good)+5
efficiency29 tool calls (>25, inefficient)+0
found docsTouched docs at docs.steel.dev: yes (13 matching tool calls)+10
zero errorsTool outputs with errors/tracebacks: 1+0
syntax validCode compiles/parses correctly+5
created filesGenerated files: 1 (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%
(71 × 0.7) + (100 × 0.3)= 79%
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.
steel_example.py

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Run completed Oct 26, 2026, 6:52 PM