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itseffiitseffi/agentic-os/.agents/skills/ost-intake/SKILL.md

ost-intake

Skill114 starsChanged 10 months agoMITView on GitHub

Normalize and collect complete Opportunity Solution Tree inputs before OST synthesis.

The file

We split this skill into the rules it gives an agent

6 rules. About 0 are common, 6 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈6

    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:

    Use provided context before asking questions.

    line 13
  2. Distinctive:

    Add minimal attribution to transcript snippets when possible.

    line 24
  3. Distinctive:

    Ask concise questions only for missing required inputs.

    line 27
  4. Distinctive:

    Stop when all four fields are complete and clear.

    line 28
  5. Distinctive:

    Use this skill when the task directly matches the workflow described above.

    line 36
  6. Distinctive:

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

    line 40

≈ “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

OST Intake

Collect high-quality, normalized inputs for OST work.

Instructions

Step 1: Parse existing context first

  • Use provided context before asking questions.

Step 2: Collect four required fields

  • business_outcome
  • journey_nodes_as_list (JSON array of moments)
  • interview_transcripts_or_story_snippets
  • constraints_or_principles (or None stated)

Step 3: Normalize quality

  • Reframe solution-flavored outcomes into measurable outcomes.
  • Reframe feature-like nodes into moments in time.
  • Add minimal attribution to transcript snippets when possible.

Step 4: Ask only missing critical questions

  • Ask concise questions only for missing required inputs.
  • Stop when all four fields are complete and clear.

Output

  • Final normalized values for all four required fields.

When to Use

Use this skill when the task directly matches the workflow described above.

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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