task-success-metrics

v2026.09.25

Measuring whether the AI actually helped users accomplish their goals.

GitHub
Install command
npx skhub add owl-listener/task-success-metrics
Markdown
SKILL.md

Task Success Metrics

Output quality doesn't guarantee task success. The AI might produce a beautiful response that doesn't actually help the user do what they came to do. Task success metrics measure the end-to-end outcome.

Defining Task Success

For each user task, define:

  • What does success look like? The user completed their goal (sent the email, found the information, finished the design)
  • What are the success criteria? Specific, observable conditions that indicate the task is done
  • What's the time expectation? How long should this task take with AI assistance vs. without?
  • What's the quality bar? Not just done, but done well enough

Task Success Metrics

  • Task completion rate: Percentage of users who complete the task (not just get a response)
  • Time to completion: How long from first input to task done
  • Turns to completion: How many back-and-forth exchanges needed
  • First-attempt success rate: Did the AI's first response accomplish the task, or did it require iteration?
  • Intervention rate: How often did the user need to correct, redirect, or override the AI?
  • Abandonment rate: How often did users give up before completing the task?

Measuring Task Success

  • Direct measurement: Track task completion through product analytics (user clicked "done", saved the output, moved to next step)
  • Inferred measurement: Infer success from proxy signals (session length, return rate, output edits)
  • Self-reported measurement: Ask users whether the AI helped them accomplish their goal
  • Comparative measurement: Compare task success with AI vs. without AI, or with version A vs. version B

Task Success vs. Output Quality

These can diverge:

  • High output quality, low task success: The AI's answer is well-written but doesn't address the real need
  • Low output quality, high task success: The AI's answer is rough but gives the user exactly what they needed
  • Both matter: Track both and investigate when they diverge

Design Artefacts

  • Task success definitions per key user task
  • Metrics framework with measurement methods
  • Success criteria specifications
  • Baseline measurements (before AI, or current version)
  • Task success dashboard specifications
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Version
Latest version metadata

Version

v2026.09.25

Published

Sep 25, 2026

Category

Uncategorized

License

MIT

Source path

claude-plugin/evaluation/skills/task-success-metrics

Default branch

main

Latest commit

f41b650

Tree SHA

e9c55ee