agentleFS
ibahgatibahgat/oh-my-iflow/skills/reasoning/SKILL.md

reasoning

Skill2 starsChanged 8 months agoMITView on GitHub

Control omi reasoning effort level to balance depth, rigor, latency, and token cost.

We split this skill into the rules it gives an agent

1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 4 edited versions we read keep these.

  • 1

    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:

    Use this skill to set an explicit reasoning posture before planning, execution, or verification-heavy turns.

    line 8

“Common” is measured: kept by at least 6 in 10 of the 4 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

Purpose

Use this skill to set an explicit reasoning posture before planning, execution, or verification-heavy turns.

Trigger

  • User asks for faster vs deeper reasoning
  • Session needs tighter quality gates or lower latency
  • Team wants predictable planning/verification effort across stages

Supported Effort Levels

  • low
  • medium
  • high
  • xhigh

Workflow

  1. Identify requested effort or infer medium as default.
  2. Explain impact on planning depth, verification strictness, and cost/latency.
  3. Persist/update .iflow/state/reasoning.json when filesystem tools are available.
  4. Recommend a next command (/omi:mode, /omi:team, or /omi:loop) based on posture.

Output Template

## Reasoning
- requested:
- applied:

## Profile
| Dimension | Value |
| --- | --- |

## Next Command
- ...

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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.