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Agent skill

Django CI Test Optimization

by hashgraph-online in hashgraph-online/awesome-codex-plugins

Optimize Django and pytest-django test execution in CI with cache configuration, slow-test splitting, database reuse strategy, parallel workers, pytest-xdist, CircleCI/GitHub Actions/Jenkins/Travis…

MITAuto-check passedBackend & APIs

Install Django CI Test Optimization

skills CLI
$ npx skills add hashgraph-online/awesome-codex-plugins --skill django-ci-test-optimization -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install hashgraph-online/awesome-codex-plugins django-ci-test-optimization --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/LVTD-LLC/skills/skills/django-ci-test-optimization .claude/skills/django-ci-test-optimization && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
django-ci-test-optimization
GitHub stars
1.2k
Token cost
~812 tokens
SKILL.md length
360 words
Files
2 (incl. references)
Skills in repo
686
Repo updated
First seen
Licence
MIT

At a glance

Optimize Django and pytest-django test execution in CI with cache configuration, slow-test splitting, database reuse strategy, parallel workers, pytest-xdist, CircleCI/GitHub Actions/Jenkins/Travis…

  • Works in 5 steps: Capture current CI timing. → Cache dependencies first. → Keep local shortcuts honest. → …
  • CI test jobs are slow
  • SKILL.md covers CI Workflow, Decision Rules, Common Mistakes and Verification
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Django CI Test Optimization is an agent skill from hashgraph-online/awesome-codex-plugins. Optimize Django and pytest-django test execution in CI with cache configuration, slow-test splitting, database reuse strategy, parallel workers, pytest-xdist, CircleCI/GitHub Actions/Jenkins/Travis patterns, and full-coverage safeguards. Use when CI test jobs are slow, flaky under parallelism, missing slow-test coverage, or need a local-vs-CI test command design.

Its SKILL.md is about 810 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/ci-patterns.md`). Compatibility notes: Codex, Claude Code, and other Agent Skills-compatible clients.

It sits in Backend & APIs, covering Backend development, CI/CD and Unit testing. It works with Django, pytest, GitHub Actions and Jenkins. The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is MIT.

When your agent uses it

  • CI test jobs are slow
  • Flaky under parallelism
  • Missing slow-test coverage
  • Need a local-vs-CI test command design

Example prompts

  • “/django-ci-test-optimization”

Requirements

  • Compatibility (from SKILL.md): Codex, Claude Code, and other Agent Skills-compatible clients.

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Capture current CI timing.
  2. Cache dependencies first.
  3. Keep local shortcuts honest.
  4. Split tests deliberately.
  5. Scale hardware only after obvious waste is removed.

What it can do on your machine

Read from SKILL.md and the folder at commit 78497e5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Codex, Claude Code, and other Agent Skills-compatible clients.

    From compatibility in the SKILL.md frontmatter.

Context cost

Django CI Test Optimization loads about 812 tokens when it runs, and up to ~1.2k if it reads all its reference files. Until then it costs about 98 tokens; SKILL.md has 360 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~98
When it runs · the whole SKILL.md, loaded when a task matches
~812
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from hashgraph-online/awesome-codex-plugins at commit 78497e5, republished under its MIT licence (© hashgraph-online). 360 words, ~812 tokens.

Download SKILL.mdSave it as .claude/skills/django-ci-test-optimization/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
django-ci-test-optimization
description
Optimize Django and pytest-django test execution in CI with cache configuration, slow-test splitting, database reuse strategy, parallel workers, pytest-xdist, CircleCI/GitHub Actions/Jenkins/Travis patterns, and full-coverage safeguards. Use when CI test jobs are slow, flaky under parallelism, missing slow-test coverage, or need a local-vs-CI test command design.
compatibility
Codex, Claude Code, and other Agent Skills-compatible clients.
license
MIT
metadata.version
0.1.0
metadata.displayName
Django CI Test Optimization
metadata.category
Django
metadata.tags
django,testing,ci,pytest,github-actions

Django CI Test Optimization

CI optimization should reduce feedback time without reducing confidence. Keep fast local commands and full CI coverage distinct, then make the CI path faster with caching, parallelism, and sensible split points.

CI Workflow

  1. Capture current CI timing.

    • Separate dependency install, test database setup, test execution, and artifact upload.
    • Compare CI time with local wall-clock time to spot environment-only overhead.

  2. Cache dependencies first.

    • Use CI-native cache primitives for pip or package-manager caches.
    • Cache the package download cache, not an unsafe mutable virtualenv unless the project already supports that pattern.

  3. Keep local shortcuts honest.

    • Local runs may skip slow tests or reuse databases.
    • CI should run slow tests and at least one migration-realistic database setup path.

  4. Split tests deliberately.

    • Split slow vs normal tests when slow markers are meaningful.
    • Use parallel workers after the suite is safe under django-test-parallelization.
    • Avoid duplicating expensive setup across too many shards.

  5. Scale hardware only after obvious waste is removed.

    • Faster runners can be the pragmatic answer, but they hide inefficient setup when used too early.

Read ci-patterns.md for command and configuration patterns.

Show full SKILL.md (175 more words)Show less

Decision Rules

  • Cache dependency downloads before rewriting test code for CI-only speed.
  • Register pytest marks strictly so slow typos do not silently change coverage.
  • If local commands exclude slow tests, add a CI job that includes them.
  • If using no-migration local shortcuts, add a CI path that runs real migrations.
  • Split by tags when test categories are intentionally different; split by workers when the suite is homogeneous enough.
  • Use timing data to choose shard boundaries.

Common Mistakes

  • Caching the wrong path and seeing no improvement.
  • Letting slow tests disappear from CI after adding local skip defaults.
  • Running too many shards and paying database/setup cost repeatedly.
  • Using SQLite in CI for a PostgreSQL/MySQL production app.
  • Enabling parallel CI workers before fixing shared resources.
  • Treating larger runners as a substitute for profiling.

Verification

Before finishing:

  • CI still runs all required test categories.
  • Cache keys change when dependencies change.
  • Test split commands are documented and reproducible locally where possible.
  • Slow-test or worker split reduces wall-clock time in actual CI logs.
  • A debugging fallback command exists for serial reproduction.

© hashgraph-online, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in plugins/LVTD-LLC/skills/skills/django-ci-test-optimization of hashgraph-online/awesome-codex-plugins.

  • SKILL.md
  • references/ci-patterns.md

Open the folder on GitHubat commit 78497e5

Compare with similar skills

Django CI Test Optimization next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Django CI Test Optimization compared with similar skills
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Python Devdoccker/cc-use-exp1.1k—~790Automated safety check: PassCustom licence
Code PatternsAedelon/claude-code-blueprint120—~1.2kAutomated safety check: PassCustom licence
Django TDDaffaan-m/ECC275k7 repos~5.3kAutomated safety check: PassMIT
Dj Pytestdvf/opinionated-django109—~4.3kAutomated safety check: NotesMIT

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Works with

Categories

Questions about Django CI Test Optimization

What does Django CI Test Optimization do?

Optimize Django and pytest-django test execution in CI with cache configuration, slow-test splitting, database reuse strategy, parallel workers, pytest-xdist, CircleCI/GitHub Actions/Jenkins/Travis…. Django CI Test Optimization is an agent skill from hashgraph-online/awesome-codex-plugins. Optimize Django and pytest-django test execution in CI with cache configuration, slow-test splitting, database reuse strategy, parallel workers, pytest-xdist, CircleCI/GitHub Actions/Jenkins/Travis patterns, and full-coverage safeguards.

When should I use Django CI Test Optimization?

Django CI Test Optimization fits situations like: CI test jobs are slow; flaky under parallelism; missing slow-test coverage; need a local-vs-CI test command design.

How do I install Django CI Test Optimization in Claude Code?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill django-ci-test-optimization -a claude-code`. Or copy the skill folder (plugins/LVTD-LLC/skills/skills/django-ci-test-optimization in hashgraph-online/awesome-codex-plugins) into .claude/skills/django-ci-test-optimization in your project. Claude Code loads it when a task matches its description.

How do I install Django CI Test Optimization in Codex?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill django-ci-test-optimization -a codex`. Or copy the skill folder (plugins/LVTD-LLC/skills/skills/django-ci-test-optimization in hashgraph-online/awesome-codex-plugins) into .agents/skills/django-ci-test-optimization in your project. Codex loads it when a task matches its description.

Can I use Django CI Test Optimization in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add hashgraph-online/awesome-codex-plugins --skill django-ci-test-optimization -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/django-ci-test-optimization, .gemini/skills/django-ci-test-optimization, .github/skills/django-ci-test-optimization and .opencode/skills/django-ci-test-optimization in your project.

What does Django CI Test Optimization need to run?

SKILL.md names no scripts, command-line tools or credentials: Django CI Test Optimization is instructions for the agent only. Compatibility (from SKILL.md): Codex, Claude Code, and other Agent Skills-compatible clients..

Does Django CI Test Optimization access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Django CI Test Optimization safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Django CI Test Optimization use?

Django CI Test Optimization is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Django CI Test Optimization use?

About 812 tokens (SKILL.md is roughly 3.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 437 tokens, read only when the agent opens those files.

What are the alternatives to Django CI Test Optimization?

Skills that share tags, products or a category with Django CI Test Optimization: Run And Verify (aropan/clist, 439 stars), Python Dev (doccker/cc-use-exp, 1.1k stars), Code Patterns (Aedelon/claude-code-blueprint, 120 stars) and Django TDD (affaan-m/ECC, 275k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Django CI Test Optimization?

hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,242 GitHub stars. The repository holds 686 skills in this directory. The repository was last updated on October 8, 2026.

Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.