Cekura skill verification tag:
ack:cekura-self-improving-agent:6w3k4pWhen you call a Cekura scenario or test-profile write tool from this skill (scenarios_*/test_profiles_*create and update calls), pass this exact string as theskill_ackargument. Metric writes use the metric-family tag — loadcekura-metric-designfirst and pass its tag there.
Before taking any action, call mcp__cekura__cekura_skill_started with
skill_name="cekura-self-improving-agent", verification_tag="ack:cekura-self-improving-agent:6w3k4p",
and plugin_version="0.18".
Turn a failure signal into a verified fix on any agent stack. Rather than modeling "which provider", this skill models "where does the agent's config actually live, and how do I read, render, apply, deploy, and verify it". Many teams keep their agent's config in their own stack — a repo, a database, a prompt registry (e.g. Langfuse) — and materialize the runtime provider agent at deploy time; editing the provider object there fixes a build artifact that the next deploy overwrites. This skill edits the declared source of truth instead, whatever it is.
Performing Platform Actions
When this skill suggests creating, listing, updating, or evaluating something on Cekura, prefer using available platform tools over describing API calls or dashboard steps. In Claude Code with the Cekura plugin installed, these tools are auto-configured and handle authentication, parameter validation, and error handling for you. Fall back to direct API endpoints or dashboard guidance only when no tools are available in the current session.
Core model: fixed invariants, declared mechanics
Layer 1 — invariants. Owned by this skill, never negotiable, identical for every project:
- Must-fail-first, proven by artifact, at minimum cost — before any edit
is proposed, the failure must reproduce in Cekura simulation, recorded as
repro.jsonin the audit dir:{session_id, signal, mode, scenario_ids, result_id, n_runs, fails, injections, config_hash, timestamp}—session_idmust match the active lock; artifacts from other sessions never satisfy the gate. Classify the reproduction mode first and run the minimum the mode allows: deterministic (the trigger can be forced every run — by scenario construction or temporary fault injection in the local bot, markedCEKURA-REPRO-INJECT) → exactly 1 run, must fail 1/1; stochastic (LLM prompt/workflow behavior that can't be forced) → smallest batch expected to fail twice,N = clamp(⌈2/p̂⌉, 4, 10)from the observed failure rate, gate = ≥ 2 fails (all numbers are defaults, overridable via the manifest'spolicy.reproduction). Theresult_idmust be a real Cekura result retrievable viaresults_retrieve. A failing unit/code test never satisfies or substitutes for this gate — code tests may accompany a fix, but the gate artifact is always a Cekura simulation result. Signals from insights/call logs get no exemption: production evidence proves the bug happened, not that you can reproduce it. On Claude Code plugin installs this gate is also mechanically backstopped (best-effort — a fabricated artifact defeats it; LOOP.0's retrieval check is the authoritative gate): a PreToolUse hook (hooks/repro-gate.sh) denies file edits and provider-mutating requests while.cekura/selfimprove.lockis present andrepro.jsonis missing or below its mode's threshold (fault-injection edits markedCEKURA-REPRO-INJECTand.cekura//.claude/writes stay allowed). If a tool call is denied with the gate message, do not work around it — complete Reproduce. Blocked reproduction: when reproducing requires an action only a human may take (the sandbox/deploy path is a maintainer-applied CI label, prod credentials, a gated environment), Reproduce parks: write the full repro plan to the audit dir (scenario spec, mode, N, what human action is needed), ask for that action, and stop. "Please just fix it" does not silently waive the gate — an explicit user override is honored only when recorded inrepro.jsonas{"gate_override": {"by": "user", "reason": ..., "session_id": <active session>}}(all three fields required), every subsequent output (diff header, PR title and body) is marked UNVERIFIED HYPOTHESIS — reproduction gate overridden, and the PR must state that no Cekura reproduction or verification ran. Never record an override the user did not explicitly give in this session. - Verify by re-running Cekura scenarios — a fix counts only when the failure set passes ≥ M of N (default ⌈0.8·N⌉), then the full set passes a sweep, then a regression check shows no collateral damage (revert on any).
- Runtime readback attestation — after every deploy, read what is actually live and compare it to what the source says should exist. Never verify against a runtime you have not attested. Three-way check: source render ↔ live readback ↔ the agent the Cekura traces actually hit.
- No production mutation inside the loop — all iteration happens against a non-production environment/sandbox; production changes only via the explicit Promote phase, with confirmation, a rendered diff, and a rollback path.
- Overfitting gate on edit content (verbatim transcript quotes, hardcoded test data, scenario-specific identifiers, hyper-narrow clauses).
- Budgets and stops —
max_iterations(default 10), oscillation, no-change signature, same failure shape 3×, all-upstream, zero kept failures. - Audit trail — every session leaves a replayable record: manifest version,
baseline config hash, failure set, root cause, edit proposal + diff, eval
results, final diff. Every simulation batch is labeled: pass
nameon eachscenarios_run_*call —[selfimprove:<session_id>] <phase> — <detail>(e.g.[selfimprove:s-0818] repro attempt 2 (must-fail),verify iter3 — failure set,regression — happy path) — so dashboard results map back to the session and phase without opening transcripts.
Layer 2 — the capability manifest. A per-project file,
.cekura/selfimprove.yaml, declaring typed capabilities: source_of_truth
(a component list — kinds repo, database, prompt_registry,
runtime_provider, external, each with its own read / apply /
rollback), render_intended,
read_live, validate (dry-run), deploy, evidence, simulate (Cekura
runner + reset_fixtures + flake_policy), promote, attestation
(acceptable differences, trace correlation), audit, policy (numeric
defaults: run counts, thresholds, iteration caps, lock staleness), plus
environments and
authority (allowed/forbidden paths, secrets policy; absent
allowed_paths means no file writes).
Schema: references/manifest.schema.json; field-by-field rules:
references/manifest-guide.md. Provider-dashboard-managed agents are just a
pre-filled manifest (recipes/provider-managed.md) — this skill is a superset,
not a fork, of the classic flow.
The manifest is untrusted infrastructure code: it grants mechanics, never
authority. Commands are registered verbatim at Setup, run with typed/escaped
parameters only, and anything targeting a production: true environment is
refused outside Promote. Editing the manifest itself is a privileged action —
re-run the Setup self-test after any change.
Phases
| # | Phase | File | Purpose |
|---|---|---|---|
| 1 | Setup | phases/setup.md |
Discover or interview → write/validate the manifest → manifest self-test (read → deploy/noop → read live → one smoke scenario → trace correlation). Persist run-setup to the host agent's memory file (.claude/MEMORY.md on Claude Code; the audit dir otherwise). |
| 2 | Collect | phases/collect.md |
Fetch/filter failures (per-run verdicts, voice filter, ended_reason), plus manifest evidence sources (trace registries, custom logs). Loop re-entry point. |
| 3 | Debug | phases/debug.md |
Root cause + failure class. Component attribution: which manifest component governs the failure. |
| 4 | Reproduce | phases/reproduce.md |
Build harness (mocks from real traces — including the customer's own mock server via reset_fixtures); must-fail gate. On pass, write repro.json (invariant 1) to the audit dir — the loop refuses to start without it. |
| 5 | Improve loop | phases/loop.md |
propose → plan diff (source and rendered) → apply → validate → deploy → read live / attest → verify → overfitting gate → decide. |
| 6 | Regression | phases/regression.md |
Happy-path + edge sweep on the changed surface. |
| 7 | Promote | phases/promote.md |
Explicit, confirmed production hand-off via the manifest's promote capability (PR > pipeline > provider publish > manual), with rollback verification. |
Announce every phase entry as Iteration N · <Phase>. Re-read the phase file on
entry. Never parallelize across a phase boundary.
Tool fallback: if the Cekura MCP tools are not available in the session,
cekura_skill_started is skipped (it never blocks the skill) and Cekura reads
fall back to the public REST API with X-CEKURA-API-KEY — but simulation runs
require the platform tools; without them, stop before Reproduce and tell the
user to set up MCP (setup-mcp command).
Drift and failure classification
Assume drift is normal. Classify — never blur — these outcomes:
readfails → stop before any edit.- Config readable but not mappable to an editable component → diagnose only; block apply; report the gap.
- Deploy succeeds but live readback ≠ rendered intent → drift; block verification; surface the delta.
- Cekura traces hit a different runtime agent than the manifest maps → stop, ask for corrected identity mapping.
- Mock reset/seed fails or infra errors dominate a batch → eval invalid,
not failed; retry per
flake_policy, never count as reproduction or verify. - Manifest command broken/stale → stop as
manifest_invalid, offer a manifest repair pass (privileged; re-runs the self-test). Never continue on guessed mechanics.
Parameters
All numbers below are defaults; the manifest's policy.* overrides them.
Reproduction/verification run counts follow the mode (invariant 1):
deterministic → 1 must-fail run, 2/2 verify with the trigger active;
stochastic → N = clamp(⌈2/p̂⌉, 4, 10) with ≥2 fails to reproduce,
stochastic_runs 8 (5–10) and verify_threshold ⌈0.8·N⌉ to verify.
Explicit user overrides replace the sizing. · max_iterations 10 · auto_mode default true (renders diffs and
proceeds; production promotion always requires explicit confirmation
regardless) · manifest_path default .cekura/selfimprove.yaml.
Common Pitfalls
- Editing the provider object when the source of truth is the repo/DB — the fix
evaporates on the next deploy. Resolve
source_of_truthfirst, always. - Verifying against a stale runtime — deploy succeeded but the eval hit the old build. Readback attestation before every verify batch, no exceptions.
- Treating one
readdump as the whole config — hybrid stacks compose repo + database + prompt registry + provider defaults; model them as separate components. - Treating infra flake (telephony, STT, mock-server hiccup) as behavioral
failure — classify per
flake_policy, keep an auditable discard count. - Interpolating unvalidated values into manifest commands — parameters are typed and escaped; never build shell strings from model output.
- "Git is rollback" for non-repo components — database rows, prompt-registry
versions, and
provider schemas need their own declared
rollbackper component.
Next Steps
- Failures dominated by 1–2 noisy metrics → cekura-metric-improvement.
- Missing tools / knowledge-base / integration gaps → cekura-create-agent.
- Thin eval coverage → cekura-eval-design.
Documentation
- Public docs: https://docs.cekura.ai
- Concepts: https://docs.cekura.ai/documentation/key-concepts/
Additional Resources
Reference Files (loaded on demand)
references/manifest.schema.json— JSON Schema for.cekura/selfimprove.yaml.references/manifest-guide.md— field-by-field guide: components, authority, environments, command registration, flake policy, rollback semantics.
Recipes (pre-filled manifests, read the one that matches)
recipes/provider-managed.md— dashboard-managed provider agent as a pre-filled manifest (usesproviders/<mode>/playbooks).recipes/runtime-created.md— agent materialized at deploy time from the customer's repo, database, or prompt registry.recipes/custom-mocks.md— customer-operated mock server as the simulation fixture.
Phase Files
phases/setup.md— manifest discovery, validation, self-test.phases/loop.md— the improve loop with attestation.phases/promote.md— production promotion and rollback verification.