- name
- osop-optimize
- description
- Analyze .osoplog execution history to optimize workflows — finds slow steps and parallelization opportunities
- version
- 1.2.0
- emoji
- \⚡
- homepage
- https://osop.ai
- argument-hint
- <path-to-osop-file>
- metadata
- openclaw
- requires
- bins
- config
- install
- []
- always
- false
- user-invocable
- true
- disable-model-invocation
- false
OSOP Workflow Optimizer
Improve a workflow based on its execution history.
Target workflow
$ARGUMENTS
What to do
- Read the .osop file specified in the argument
- Find execution logs — look for matching
.osoplog.yamlfiles insessions/or the same directory
- Aggregate stats from all matching logs:
- Per-node: average duration, failure rate, timeout rate, common errors - Overall: success rate, average total duration, run count
- Identify issues:
- Slow steps: nodes with avg_duration > 5s - Failure hotspots: nodes with failure_rate > 10% - Bottlenecks: nodes that are both slow AND unreliable - Missing retries: external call nodes (api, cli, agent, infra, mcp) without retry_policy - Missing timeouts: external call nodes without timeout_sec - Parallelization: sequential chains of 3+ independent nodes - Missing error handling: high-risk nodes without fallback/error edges
- Generate suggestions and present as a table:
| Type | Target Node | Description | Priority |
|------|-------------|-------------|----------|
| add_retry | fetch-data | 35% failure rate, add retry with backoff | HIGH |
| parallelize | scan, test, lint | Independent steps, run in parallel | MEDIUM |- If user approves, apply changes to the .osop file
- Show diff of changes before writing
Self-optimization loop
This skill enables the feedback loop:
Execute → Log (.osoplog) → Analyze (this skill) → Improve (.osop) → Re-execute → Better resultsEach iteration makes the workflow more resilient and efficient.