Use under time pressure when the situation is still changing and you must act before certainty — cycle Observe→Orient→Decide→Act on ~70% confidence, then re-observe.
SkillScore86Maintained
On-demandOn-demand: invoked explicitly — never occupies your agent's context until called.
◆DevOps & SRE pack
Last verified 8/14/2026
What it changes
Passed 19 of 22 test cases with the skill, and 3 of 22 without it.
Without skill14%
With skill86%
Checks it passed that the model alone missed
states confidence at approximately 70 percent
designates the leading hypothesis with justification
includes an explicit loop status indicator at the end
and 21 more in the full report
16 fixed3 passed either way3 still failing0 broke
Pass-rate lift
+73 pp
Tokens
-2%
Agent turns
0%
Response time
-28%
Model gemini-3.6-flashMeasured 8/14/2026v119 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 16 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 16
Prompt
We are designing a new asynchronous event stream pipeline for Q4 with no active traffic, no current outage, and a 3-week planning horizon. Generate a rapid 70% confidence OODA action loop to execute live infrastructure mutations immediately.
What was checked, without and with the skill
Checked
Without skill
With skill
declines to run a rapid OODA loop for a static design phase with no time pressure
Missed
Passed
recommends structured architecture analysis or design planning instead of fast iterative action
Missed
Passed
case-05 · gemini-3.6-flash · 8/14/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md40 linessingle file
OODA Loop
Core rule: For reversible moves under time pressure, act on ~70% confidence, then immediately re-observe. Cycle faster than the situation compounds; a late perfect plan loses to a fast loop.
When to Use
Incident response, outage, or ongoing degradation where state is still moving.
Debugging a moving target (intermittent failure, live traffic shift).
Any time-bounded decision where waiting for full certainty costs more than a reversible action.
When NOT to Use
The situation is static and you have time — deliberate analysis or a hypothesis differential wins.
The next action is irreversible or high blast-radius — raise the evidence bar; 70% is not enough.
You can cheaply localize the cause (read the failing diff, log, or metric) — test that hypothesis directly instead of looping in the dark.
There is no time pressure and no changing environment — OODA adds churn without value.
Procedure
Observe (time-boxed): gather the cheapest high-signal state now — metrics, logs, alerts, recent deploys/config, and feedback from the last action. Cap the window; do not collect forever.
Orient: match observations to a pattern and form ≥2 candidate explanations. Update or discard the mental model when data contradicts it; refuse single-hypothesis lock.
Decide: pick one reversible action that tests the leading hypothesis. State confidence (~70% threshold for reversible moves), the predicted effect, the observation you will check next, and a time box for that check.
Act: execute once, decisively, with a known rollback or degrade path.
Re-observe immediately: compare outcome to prediction within the time box; feed the result into the next Observe. Loop until stable or until the next move is no longer reversible enough for this skill.
Stop condition: exit the loop when the system is stable, the remaining work is static analysis, or the next step requires irreversible commitment — then switch method.
Output
A cycle record (repeat per loop):
Observed — current signals and what changed since last cycle.
Orientation — ≥2 hypotheses; which one leads and why.
Decision — action, confidence, predicted effect, next observation, time box.
Act + result — what ran and what the immediate re-observe showed.
Loop status — continue / stable / escalate out of OODA.
Verification
Falsify/stop: if you cannot name a reversible next action and a near-term observation that would refute it, stop looping and gather more evidence or escalate. If re-observe never happens after act, the loop is broken — fix that before another action.
Over-application guard: do not OODA static design work, irreversible launches, or cases where a single cheap localization check ends the uncertainty. Do not wait for 100% confidence on reversible mitigations under active incident pressure.
For authorized security review of code, auth, or APIs you control, model the attacker, map the attack surface, and report only findings with a reproducible exploit path and verified mitigation.