agentleFS
itseffiitseffi/agentic-os/.agents/skills/decision-journal/SKILL.md

decision-journal

Skill114 starsChanged 10 months agoMITView on GitHub

Create structured records of decisions with expected outcomes, probabilities, and quit conditions. Use for important decisions.

4 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

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

  • 0

    Common

    Most of the 3 edited versions we read keep these.

  • 6

    Distinctive

    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:

    Create structured records of decisions for learning and accountability.

    line 8
  2. Distinctive:

    When making important decisions that you want to track and learn from.

    line 12
  3. Distinctive:

    Consider short and long-term

    line 23
  4. Distinctive:

    Leave blank initially, fill in later:

    line 49
  5. Distinctive:

    After outcomes are known:

    line 56
  6. Distinctive:

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

    line 63

“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “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

Decision Journal

Create structured records of decisions for learning and accountability.

When to Use

When making important decisions that you want to track and learn from.

The Framework

Record these components for each decision:

1. Expected Outcomes

List 3-5 possible outcomes:

  • Best case scenario
  • Most likely scenario
  • Worst case scenario
  • Consider short and long-term

2. Probability Estimates

For each outcome, estimate likelihood (must sum to 100%):

  • Outcome A: X%
  • Outcome B: Y%
  • etc.

3. Key Assumptions

List 3-5 critical assumptions:

  • What beliefs underlie this decision?
  • Which, if wrong, would change the outcome?

4. Base Rates

Research relevant statistics:

  • What's typical for this type of decision?
  • Historical data or industry averages?
  • What do similar situations suggest?

5. Quit Conditions

Define 2-3 triggers to abandon or change course:

  • Clear, measurable indicators
  • Specific thresholds
  • Timeline checkpoints

6. Actual Results

Leave blank initially, fill in later:

  • What actually happened?
  • Which outcome occurred?
  • Were assumptions valid?

Review Process

After outcomes are known:

  1. Compare predictions to reality
  2. Identify where thinking was wrong
  3. Extract lessons for future decisions

When Not to Use

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

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.