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Developer Content Filter False Positive Impact Assessment

Assess how content filter false positives affect developer productivity, workflow disruption, and tool adoption decisions. Designed for developer experience researchers and tooling teams seeking actionable improvement priorities from software practitioners.

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Template Overview

22

Questions

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This professionally designed survey template helps you gather valuable insights with intelligent question flow and automated analysis.

Sample Survey Items

Q1
Chat Message
Welcome! This survey explores your recent experiences with content filters and false positives in developer tools. Your participation is voluntary, and you may stop at any time. There are no right or wrong answers—we are interested in your honest opinions. All responses are confidential and will be reported in aggregate only. The survey takes approximately 5–7 minutes. Please answer based on the last 30 days and omit any sensitive or proprietary data.
Q2
Multiple Choice
In the last 30 days, have you used any developer tools that enforce content moderation or safety filters?
  • Yes, in the last 30 days
  • No, not in the last 30 days
Q3
Multiple Choice
Which types of developer tools with content filters have you used in the last 30 days? Select all that apply.
  • AI code assistants (e.g., coding copilots)
  • Code hosting/PR checks (e.g., repo content policies)
  • Package registries with policy checks (e.g., npm, PyPI)
  • Documentation portals or knowledge bases
  • Q&A forums or developer communities
  • CI/CD or security policy gates
  • Other (please specify)
Q4
Opinion Scale
How often did you encounter false positives from these content filters in the last 30 days?
Range: 1 – 5
Min: NeverMid: NeutralMax: Very often
Q5
Opinion Scale
Overall, how disruptive were the false positives you encountered in the last 30 days?
Range: 1 – 7
Min: Not at all disruptiveMid: NeutralMax: Extremely disruptive
Q6
Long Text
Briefly describe your most recent false positive from a content filter in the last 30 days. Please omit any sensitive or proprietary data.
Max chars
Q7
Dropdown
Approximately how long did it take to resolve your most recent false positive?
  • Less than 5 minutes
  • 5–15 minutes
  • 16–30 minutes
  • 31–60 minutes
  • 1–2 hours
  • More than 2 hours
  • It was never resolved
Q8
Multiple Choice
After encountering the false positive, what actions did you take? Select all that apply.
  • Submitted an appeal or requested a review
  • Reworded or reformatted content
  • Used a different tool or channel
  • Waited and retried later
  • Asked a teammate/admin with different access
  • Abandoned the task
  • Other (please specify)
Q9
Ranking
Rank the top 3 effects you experienced from false positives. Place the highest-impact effect first.
Drag to order (top = most important)
  1. Lost time
  2. Context switching
  3. Blocked release or review
  4. Lower code quality or shortcuts
  5. Frustration or stress
  6. Team coordination overhead
Q10
Multiple Choice
Why haven't you used developer tools with content filters in the last 30 days? Select all that apply.
  • None of my current tools apply content filters
  • I avoid tools that include filters
  • Company policy restricts such tools
  • I'm unsure which tools include filters
  • Other (please specify)
Q11
Opinion Scale
If developer tools you use introduced content filters, how disruptive do you expect false positives would be to your workflow?
Range: 1 – 7
Min: Not at all disruptiveMid: NeutralMax: Extremely disruptive
Q12
Multiple Choice
What informs your expectations about content filter false positives? Select all that apply.
  • Teammates' experiences
  • Industry news or reports
  • Past experiences in other tools
  • Social media or forums
  • Vendor documentation or release notes
  • Other (please specify)
Q13
Opinion Scale
When it comes to content filters in developer tools, which trade-off do you prefer?
Range: 1 – 7
Min: Minimize false negatives (stricter filtering)Mid: NeutralMax: Minimize false positives (more permissive filtering)
Q14
Multiple Choice
In your view, what most often causes false positives in developer tool content filters? Select all that apply.
  • Ambiguous or broad policy definitions
  • Overly sensitive detection models
  • Missing contextual signals (e.g., file type, repo trust)
  • Poor or unrepresentative training examples
  • Misclassifying code vs. natural language
  • Locale or language issues
  • Unclear UI messaging or guidance
  • Other (please specify)
Q15
Ranking
Rank the following improvements by how much they would reduce the impact of false positives. Place the most impactful improvement first.
Drag to order (top = most important)
  1. Clearer policy definitions in tools
  2. Better detection models (precision/recall tuning)
  3. Use more context (file type, repo trust, role)
  4. Faster and more transparent appeal or override process
  5. Granular admin and user controls
  6. Improved UI messaging and guidance
Q16
AI Interview
Based on your responses in this survey, please share any additional thoughts or experiences about false positives or content filter design in developer tools.
AI InterviewLength: 2Personality: [Object Object]Mode: Fast
Reference questions: 5
Q17
Dropdown
What is your primary role?
  • Backend developer
  • Frontend developer
  • Full-stack developer
  • DevOps/SRE
  • ML/AI engineer
  • Security engineer
  • Engineering manager
  • QA/Testing
  • Other
Q18
Dropdown
How many years of professional software development experience do you have?
  • Less than 1 year
  • 1–3 years
  • 4–6 years
  • 7–10 years
  • 11–15 years
  • 16–20 years
  • More than 20 years
Q19
Dropdown
What is your organization size?
  • 1 (just me)
  • 2–10
  • 11–50
  • 51–200
  • 201–1,000
  • 1,001–5,000
  • 5,001+
Q20
Dropdown
Where are you primarily located?
  • North America
  • Europe
  • Latin America
  • Asia
  • Africa
  • Oceania
  • Prefer not to say
Q21
Multiple Choice
Which programming languages do you use most often? Select all that apply.
  • JavaScript/TypeScript
  • Python
  • Java/Kotlin
  • C/C++
  • C#/.NET
  • Go
  • Ruby
  • Rust
  • Swift/Objective-C
  • PHP
  • SQL
  • Other
Q22
Chat Message
Thank you for your time. Your feedback will help improve content filter design in developer tools and reduce the impact of false positives on developer workflows.

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