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jtbd-clustering

Skill114 starsChanged 10 months agoMITView on GitHub

Cluster forces from multiple JTBD interviews to identify patterns. Use after extracting from multiple interviews.

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 5 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    When you have JTBD extractions from multiple interviews and need to identify patterns across them.

    line 12
  2. Distinctive:

    Start with first story's forces as initial columns

    line 21
  3. Distinctive:

    If force matches existing column: mark "1"

    line 23
  4. Distinctive:

    If force is novel: add new column

    line 24
  5. Distinctive:

    Do not use this skill when the request is unrelated, low-stakes, or better handled by a simpler direct response.

    line 45

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

JTBD Forces Clustering

Cluster and categorize forces from multiple interviews for pattern analysis.

When to Use

When you have JTBD extractions from multiple interviews and need to identify patterns across them.

The Process

  1. Create a matrix:
    • Rows = interview stories
    • Columns = distinct forces
  2. Code each interview:
    • Start with first story's forces as initial columns
    • For each new story:
      • If force matches existing column: mark "1"
      • If force is novel: add new column
  3. Abstraction pass:
    • Review columns for grouping opportunities
    • Rename with overarching descriptors
    • Merge similar forces
  4. Analysis questions:
    • Which forces appear most frequently?
    • Which stories introduced unique forces?
    • What patterns emerge across segments?

Output

  1. Spreadsheet summary: Number of stories and forces identified
  2. Force categories: Abstract labels for each column
  3. Unique contributors: Stories that introduced novel forces
  4. Patterns and insights: Notable observations

When Not to Use

Do not use this skill when the request is unrelated, low-stakes, or better handled by a simpler direct response.

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