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cekura-self-improving-agent

Use to close the loop on agent quality — turn a failure signal into a verified fix. Triggers: "improve my agent", "self-improving agent", "auto-tune / iterate on my prompt", "fix my agent from test results" — and production-call bug fixing: "fix this prod call issue", "debug and fix call ID", "reproduce this production bug", "regression test before raising PR". Works on any stack: provider-dashboard agents (VAPI, Retell, ElevenLabs, Bland) AND agents whose config lives in the customer's own repo, database, or prompt registry with the provider agent created at deploy time, or with custom mock servers. Fixed safety invariants (must-fail-first reproduction, attestation, no-prod-in-loop) + a per-project capability manifest declaring where config lives and how to read/render/apply/deploy/verify it.

72

Quality

88%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

77%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a well-sequenced, validation-rich overview with strong workflow clarity and concrete actionable orchestration guidance, but it is somewhat dense for an overview and its progressive-disclosure structure is undermined by many missing referenced bundle files (phases/, recipes/, hooks/ all absent). Fixing the bundle so referenced paths resolve would raise the progressive_disclosure score.

Suggestions

Add the referenced phase files (phases/setup.md, phases/loop.md, phases/promote.md, phases/collect.md, phases/debug.md, phases/reproduce.md, phases/regression.md), recipe files (recipes/provider-managed.md, recipes/runtime-created.md, recipes/custom-mocks.md), and hooks/repro-gate.sh so every path in the body resolves — currently every phase link is a dead reference.

Move inline reference-grade detail out of the overview and into the phase files — the full repro.json field list, the gate-override JSON structure, and the N = clamp(⌈2/p̂⌉, 4, 10) formula belong in phases/reproduce.md, leaving the overview with the invariant summary and a pointer.

Either reference references/phase-2-failure-collection.md and references/phase-3-diagnosis.md from the body (they exist but are orphaned) or remove them, so the in-bundle references and the body's referenced paths agree.

DimensionReasoningScore

Conciseness

The prose assumes Claude's competence (no generic concept explainers) and is dense rather than padded, but it inlines reference-grade detail in the overview — the full repro.json field schema, the gate-override JSON blob, and the N = clamp(⌈2/p̂⌉, 4, 10) formula — that the progressive-disclosure model places in referenced phase files, so it could be trimmed. It sits above the midpoint but not at fully lean.

4 / 5

Actionability

Concrete, executable guidance is pervasive — the repro.json schema, the batch 'name' labeling convention with literal examples, exact tool names (mcp__cekura__cekura_skill_started, scenarios_run_*, results_retrieve), and file paths — with only minor gaps because the actual phase mechanics are deferred to referenced files. It is an orchestration/instruction skill so the absence of code is not penalized.

4 / 5

Workflow Clarity

A clear 7-phase table with per-phase files and purposes is followed by explicit sequencing rules ('Announce every phase entry as Iteration N · <Phase>', 'Never parallelize across a phase boundary') and dense validation checkpoints (must-fail-first gate, verify ≥ M of N, readback attestation, regression sweep, revert on collateral damage, flake → eval invalid), with feedback loops for blocked reproduction and drift.

5 / 5

Progressive Disclosure

The overview is well designed as a one-level-deep reference model (phase table, recipes, reference files clearly signaled), but scored against the actual bundle most referenced paths are dangling: phases/setup.md, phases/loop.md, phases/promote.md (and collect/debug/reproduce/regression), recipes/*.md, and hooks/repro-gate.sh do not exist — only references/manifest.schema.json and references/manifest-guide.md are present, while references/phase-2-failure-collection.md and phase-3-diagnosis.md exist but are not referenced in the body. The broken navigation prevents scoring above 3.

3 / 5

Total

16

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is strong across all dimensions: it states concrete capabilities, includes numerous natural trigger phrases, explicitly covers both 'what' and 'when', and occupies a clear niche with low conflict risk. It uses third-person voice throughout and is comprehensive without padding.

DimensionReasoningScore

Specificity

Multiple concrete actions are named explicitly — 'turn a failure signal into a verified fix', 'regression test before raising PR', 'reproduce this production bug', and 'read/render/apply/deploy/verify it' — giving comprehensive coverage of what the skill does rather than vague language.

5 / 5

Completeness

It explicitly answers both 'what' (close the loop on agent quality by turning a failure signal into a verified fix via fixed invariants + a capability manifest) and 'when' (an explicit 'Triggers:' clause listing concrete trigger phrases), matching the top anchor.

5 / 5

Trigger Term Quality

Includes eight quoted natural trigger phrases a user would actually say ('improve my agent', 'self-improving agent', 'auto-tune / iterate on my prompt', 'fix this prod call issue', 'debug and fix call ID', 'reproduce this production bug', 'regression test before raising PR'), covering the task with synonyms and variations.

5 / 5

Distinctiveness Conflict Risk

The niche is tightly scoped to Cekura self-improving-agent / production-call bug fixing with highly specific triggers, making it clearly distinguishable from unrelated skills with minimal conflict risk.

5 / 5

Total

20

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
cekura-ai/cekura-skills
Reviewed

Table of Contents

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