self-improvement-ci

Original：🇺🇸 English

Translated

CI-only self-improvement workflow using gh-aw (GitHub Agentic Workflows). Captures recurring failure patterns and quality signals from pull request checks, emits structured learning candidates, and proposes durable prevention rules without interactive prompts. Use when: you want automated learning capture in CI/headless pipelines.

2installs

Sourcepskoett/pskoett-ai-skills

Added on2026-02-27

NPX Install

npx skill4agent add pskoett/pskoett-ai-skills self-improvement-ci

SKILL.md Content

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Self-Improvement CI

Install

bash

npx skills add pskoett/pskoett-ai-skills/self-improvement-ci

Purpose

Run self-improvement in CI without interactive chat loops:

Inspect PR check results and CI failures
Ingest learning candidates from
```
simplify-and-harden-ci
```
Deduplicate recurring patterns by stable
```
pattern_key
```
Emit promotion-ready suggestions for agent context/system prompts

Use

self-improvement

for interactive/local sessions.

Context Limitation (Important)

CI agents do not have peak task context from the original implementation session. Use this skill to aggregate recurring patterns across runs, not to infer nuanced one-off intent.

Implications:

Favor stable
```
pattern_key
```
recurrence signals over single-run conclusions
Require recurrence thresholds before promotion
Route uncertain or high-impact recommendations to interactive review

Prerequisites

GitHub Actions enabled for the repository
GitHub CLI authenticated (
```
gh auth status
```
)
```
gh-aw
```
installed for authoring/validation:

bash

gh extension install github/gh-aw

CI Contract

The CI skill must:

Read only PR-scoped data (checks, workflow outcomes, existing learning entries)
Avoid direct code modifications in CI
Emit machine-readable learning output
Recommend promotion only when recurrence thresholds are met

Output Schema

yaml

self_improvement_ci:
  source:
    pr_number: 123
    commit_sha: "abc123"
  candidates:
    - pattern_key: "harden.input_validation"
      source: "simplify-and-harden-ci"
      recurrence_count: 3
      first_seen: "2026-02-01"
      last_seen: "2026-02-20"
      severity: "high"
      suggested_rule: "Validate and bound-check external inputs before use."
      promotion_ready: true
  summary:
    candidates_total: 4
    promotion_ready_total: 1
    followup_required: true

Recurrence and Promotion Rules

Track recurrence by
```
pattern_key
```
Default threshold for promotion:
- ```
recurrence_count >= 3
```
- seen in
```
>= 2
```
  distinct tasks/runs
- within a 30-day window

Promotion targets:

```
CLAUDE.md
```
```
AGENTS.md
```
```
.github/copilot-instructions.md
```
```
SOUL.md
```
/
```
TOOLS.md
```
when using openclaw workspace memory

Authoring Workflow (gh-aw)

Example-only templates live in

references/workflow-example.md

. Keep examples outside

.github/workflows

until you explicitly decide to enable CI automation.

When ready:

Copy the template into

.github/workflows/self-improvement-ci.md

Customize tool access, outputs, and policy thresholds
Validate:

bash

gh aw compile --validate --strict

Trigger test run manually:

bash

gh aw run self-improvement-ci --push

Integration with Other Skills

Pair with

simplify-and-harden-ci

to ingest

simplify_and_harden.learning_loop.candidates

Feed promoted patterns back into
```
self-improvement
```
memory workflow for durable prevention rules

self-improvement-ci

NPX Install

Tags

SKILL.md Content

Self-Improvement CI

Install

Purpose

Context Limitation (Important)

Prerequisites

CI Contract

Output Schema

Recurrence and Promotion Rules

Authoring Workflow (gh-aw)

Integration with Other Skills