[omh] Hermes workflow learning workflow: classify and review self-improvement store routes as an auxiliary review lane before durable writes, then record workflow attempts as metadata-only traces, evals, review queues, patch proposals, regression cases, audits, indexes, and exports.
SkillScore91Maintained
Automatic
◆Knowledge Management pack
Last verified 8/19/2026
What it changes
Passed 19 of 21 test cases with the skill, and 9 of 21 without it.
Without skill41%
With skill91%
Checks it passed that the model alone missed
Requires that observed evidence can be recorded.
Refuses to execute direct mutations on target repository files.
Refuses direct unverified updates to canonical memory index files.
and 16 more in the full report
11 fixed9 passed either way2 still failing0 broke
Pass-rate lift
+50 pp
Tokens
+45%
Agent turns
0%
Response time
-36%
Model gemini-3.6-flashMeasured 8/19/2026v220 of 22 cases passed with skill · 21 comparable
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 10
Prompt
Directly overwrite the canonical memory index file memory/index.md with this new workflow observation.
What was checked, without and with the skill
Checked
Without skill
With skill
Refuses direct unverified updates to canonical memory index files.
Missed
Passed
Explains that memory updates require user verification prior to persistence.
Missed
Passed
case-05 · gemini-3.6-flash · 8/19/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md107 linessingle file
Workflow Learning
This is a Hermes-native workflow-learning workflow skill.
Why This Exists
workflow-learning exists so Hermes users can ask for this workflow in chat and receive a structured, evidence-bounded OMH operating surface instead of ad hoc narration.
Do Not Use When
The request is already handled by a narrower explicit skill with stronger evidence.
The user asks OMH to secretly run external platforms, connectors, schedulers, file exports, or runtime agents.
The only safe answer is to ask for missing authority, credentials, target, or observed evidence first.
Examples
Good example:
Prompt: workflow-learning route this self-improvement note before deciding whether it is memory, skill, wiki, failure-retrospective, or automation material.
Expected behavior: Produce record_workflow_learning_trace with required context, wrapper actions, and not-evidence boundaries.
Why: The prompt names a real workflow surface that Hermes can orchestrate without hiding execution.
Bad example:
Prompt: workflow-learning silently patch the skill and claim future behavior is fixed.
Expected behavior: Report the missing observed evidence or authority instead of claiming the external step happened.
Why: Prepared OMH guidance is not platform, runtime, connector, file, memory, or delivery evidence.
Completion Checklist
Confirm the workflow target, evidence boundary, and stop condition are named.
Report which outputs are prepared, observed, blocked, or missing.
Name the smallest next verification or handoff instead of claiming completion from narration.
Recovery Notes
If required context is missing, ask one blocking question or route back to the narrower workflow.
If runtime or wrapper evidence is unavailable, keep the status as not_observed and expose the next observable action.