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Minimal example Observe-phase domain skill. Checks disk usage and records it. Copy this as a starting point for your own domain.
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OODA Meta-Orchestrator. Observes all domain states, orients by learning from past outcomes, decides the highest-priority action, and executes it. Run with /evolve or /loop 4h /evolve.
Full implementation cycle pipeline. Takes the highest-RICE action from the action queue and implements it through a structured test → implement → verify workflow. Primary skill for the implementation domain — invoked by evolve when implementation is selected.
3-step project setup wizard. Auto-detects language, test framework, CI, and endpoints. Creates config.json from config.example.json.
Display OODA-loop status dashboard. Shows cycle count, domain states, confidence scores, action queue, and alerts in a single view.
View, modify, and validate config.json settings via slash commands.
Run test suite, track coverage trends, and detect regressions. Detect phase skill — uses config.test_command to execute tests and records results.
| name | scan-disk |
| description | Minimal example Observe-phase domain skill. Checks disk usage and records it. Copy this as a starting point for your own domain. |
| ooda_phase | observe |
| version | 1.0.0 |
| input | {"files":["config.json","agent/state/disk_usage/lens.json"],"config_keys":["domains.disk_usage"]} |
| output | {"files":["agent/state/disk_usage/state.json"],"prs":"none"} |
| safety | {"halt_check":true,"read_only":true} |
| domains | ["disk_usage"] |
| chain_triggers | [] |
The smallest useful Observe skill: it reads disk usage, records a baseline, and emits an alert when usage crosses a learned threshold. Use it as a 30-line template for your own domain. Every skill starts with a HALT check.
ls agent/safety/HALT 2>/dev/null && echo "HALT_ACTIVE" || echo "HALT_INACTIVE"
If HALT is active, print the reason and stop immediately.
df -P / | tail -1 | awk '{print $5}' | tr -d '%' # → integer percent used
Load the lens (agent/state/disk_usage/lens.json) if present. Use its
learned_thresholds for warn_pct if it has one; otherwise default warn_pct = 85.
Write agent/state/disk_usage/state.json:
{
"schema_version": "1.0.0",
"last_run": "<now ISO-8601>",
"status": "healthy", // healthy | degraded | critical
"metrics": { "used_pct": 73 },
"alerts": [] // e.g. ["disk 91% > warn_pct 85"] when crossed
}
Set status: "degraded" and add an alert when used_pct >= warn_pct;
"critical" at >= 95. The evolve engine reads status/alerts during Observe
and factors them into scoring.
evolve's Step 5-E initializes and updates agent/state/disk_usage/lens.json
automatically. To participate, just emit consistent metrics/alerts; the engine
learns a per-host warn_pct over time (raising it on repeated false positives,
lowering it after real incidents). You don't write the lens yourself.