Production error → triaged, root-caused, repaired, and certified (tsc + rehearsal + reproduce-then-gone) fix PR for a human to merge — then confirm the error stops recurring. Never auto-merges.
SkillScore77Maintained
Automatic
◆DevOps & SRE pack
Last verified 8/28/2026
What it changes
Passed 15 of 20 test cases with the skill, and 10 of 20 without it.
Without skill50%
With skill77%
Checks it passed that the model alone missed
Run migrate-rehearse on the preview environment
Reopen the issue with the new recurrence evidence
Offer to install sentinel error capture when absent
and 6 more in the full report
7 fixed10 passed either way4 still failing1 broke
Pass-rate lift
+27 pp
Tokens
+25%
Agent turns
0%
Response time
-39%
Model gemini-3.6-flashMeasured 8/28/2026v117 of 22 cases passed with skill · 20 comparable
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 7
Prompt
After a self-healing pull request for a Convex backend is merged and deployed to production, what telemetry source must be monitored to verify that the runtime error signature has stopped occurring?
What was checked, without and with the skill
Checked
Without skill
With skill
Check the sentinel error capture table post-deployment
Missed
Passed
Avoid using insights performance metrics for verifying runtime error signature resolution
Passed
Passed
case-11 · gemini-3.6-flash · 8/28/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md33 linessingle file
Gated production self-healing loop
Sentry/Datadog/Vercel can go error→investigate→draft-PR, but they treat the backend as opaque and stop at the human merge gate with an unverified diff. Convex can do the step they can't: because the error rows live in the user's own deployment and the fix can be rehearsed on a preview of that deployment, the platform certifies the fix against real invariants before anyone reviews it. This capability is the composition capstone — it wires sentinel (capture) → the findings bus (diagnose) → the fixers (repair) → migrate-rehearse/tsc/probe (certify) → a human PR (decide) → deploy-guard (promote). The human keeps the merge button; the machine does everything up to and including proving the fix works.
Workflow
GUARD: deploy-guard — this loop reads prod and PROPOSES prod changes; classify + announce the deployment and get the standing consent for the loop's scope up front (what classes of fix it may auto-prepare vs must always defer). Never auto-merge; the human merge is the fixed boundary.
CAPTURE: require sentinel (prod errors in the user's own deployment, redacted at write time). If absent, offer to install it and stop — there is nothing to heal without capture.
TRIAGE a new/ recurring error: pull it via the official MCP (data/run-once-query over the sentinel table, or the monitor's prod_error event). Classify: transient (retry/ignore — do NOT open a PR for a one-off network blip), config (env/secret — hand to env, never guess a secret), or a code/schema defect (proceed).
ROOT-CAUSE on the findings bus: run the relevant audit pass on the implicated function — convex-insights (the failing requests + stacks), convex-advisor (if it's a read-limit/OCC cause), convex-reviewer/convex-authz (if it's a logic/authz defect). Produce a bus finding with evidence (the stack + the reproducing input) and a fixCapability. If root cause is unclear, STOP and report — a wrong fix is worse than an open error.
REPAIR via the finding's fixCapability (convex-authz, reviewer fixers, convex-expert for perf) on a branch — never on prod directly.
CERTIFY against the backend's own invariants BEFORE proposing (this is the differentiator — do not skip any that apply):
(a) tsc --noEmit clean;
(b) if the fix touches schema/data, run it through migrate-rehearse on a preview seeded with a prod snapshot — the schema-conformance gate must pass on real-shaped data;
(c) reproduce-then-confirm-gone: replay the error's triggering input against the fixed code (a convex-test case or an MCP run on the preview) and assert the failure no longer occurs;
(d) no-regression: the finding must be gone AND no new bus finding introduced on the touched function.
A fix that fails any applicable certification is NOT proposed — it's reported as 'attempted, could not certify' with what failed.
PROPOSE, never merge: open a PR (or a diff for review) containing the fix, the certification evidence (tsc result, rehearsal outcome, the reproduced-then-gone assertion), the original error + finding, and the reversibility note. Label the change class. The human reviews and merges.
PROMOTE on merge via deploy-guard's prod consent; after deploy, re-check the sentinel table + logs (failures) to confirm that error signature stops recurring (do NOT use insights for this — it tracks only OCC/read-limit perf events, not arbitrary error signatures) — the loop is only closed when the error stops recurring in prod. If it recurs, reopen with the new evidence.
BOUND it: only classes the user pre-approved in step 1 are auto-prepared (default-safe set: validator fixes, missing-index adds, ownership-check adds, non-destructive backfills); anything destructive, security-sensitive beyond an added check, or ambiguous is always deferred to explicit human direction. Log every action to an append-only record so the loop is auditable.
Rules
The human keeps the merge button — this loop prepares and certifies fixes, it NEVER auto-merges or auto-deploys to prod (matches the industry boundary: no credible system ships unattended prod auto-merge).
Certify before proposing: tsc + (schema→migrate-rehearse on a prod-snapshot preview) + reproduce-then-confirm-the-failure-is-gone + no new bus finding. An uncertified fix is reported as 'could not certify', never proposed as done.
Triage first: transient blips get retried/ignored, config errors go to env (never guess a secret), only real code/schema defects enter the repair loop.
Repair on a branch/preview, never on prod directly; promote only through deploy-guard's fresh prod consent.
Only pre-approved fix classes are auto-prepared (default-safe: validator/index/ownership/non-destructive backfill); destructive or ambiguous changes are always deferred to the human.
Close the loop for real: after merge+deploy, confirm the error signature stops recurring via the sentinel table + logs (not insights, which only sees perf events); reopen if it persists.
Every action is logged to an append-only, auditable record; data residency stays in the user's own deployment (sentinel discipline).
If root cause is unclear, STOP and report — an uncertain fix is worse than an open, visible error.
Prove a Convex feature works — seed, drive as multiple mocked users via convex-test, assert behavior including the negative authz cases (wrong user refused, data-scope enforced).