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Agent skill

Django Test Profiling

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

Profile and measure slow Django test suites with Django's runner, pytest-django, shell timing, py-spy, cProfile, pytest durations, and profiler visualizations.

MITAuto-check passedBackend & APIs

Install Django Test Profiling

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

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

GitHub CLI
$ gh skill install hashgraph-online/awesome-codex-plugins django-test-profiling --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-test-profiling .claude/skills/django-test-profiling && 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-test-profiling
GitHub stars
1.2k
Token cost
~892 tokens
SKILL.md length
397 words
Files
2 (incl. references)
Skills in repo
686
Repo updated
First seen
Licence
MIT

At a glance

Profile and measure slow Django test suites with Django's runner, pytest-django, shell timing, py-spy, cProfile, pytest durations, and profiler visualizations.

  • Works in 5 steps: Capture a full wall-clock baseline. → Separate framework phases when possible. → Find the slowest tests. → …
  • A Django project has slow tests
  • SKILL.md covers Measurement Workflow, Commands, Decision Rules and Common Mistakes, plus 1 more section
  • Calls pytest and python

What it does

Django Test Profiling is an agent skill from hashgraph-online/awesome-codex-plugins. Profile and measure slow Django test suites with Django's runner, pytest-django, shell timing, py-spy, cProfile, pytest durations, and profiler visualizations. Use when a Django project has slow tests, unclear test-runtime bottlenecks, CI timing problems, startup overhead, database setup overhead, or a request to find the slowest tests before optimizing.

Its SKILL.md is about 890 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/profiler-commands.md`). Compatibility notes: Codex, Claude Code, and other Agent Skills-compatible clients.

It sits in Backend & APIs, covering Backend development, Performance optimization and Unit testing. It works with Django and pytest. 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

  • A Django project has slow tests
  • Unclear test-runtime bottlenecks
  • CI timing problems
  • Startup overhead

Example prompts

  • “/django-test-profiling”

Requirements

  • Python 3
  • 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 a full wall-clock baseline.
  2. Separate framework phases when possible.
  3. Find the slowest tests.
  4. Profile only after you know where the time goes.
  5. Convert the result into a ranked action list.

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

    Shell commands in SKILL.md call:

    • pytest
    • python

    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 Test Profiling loads about 892 tokens when it runs, and up to ~1.5k if it reads all its reference files. Until then it costs about 95 tokens; SKILL.md has 397 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~95
When it runs · the whole SKILL.md, loaded when a task matches
~892
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.5k

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). 397 words, ~892 tokens.

Download SKILL.mdSave it as .claude/skills/django-test-profiling/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
django-test-profiling
description
Profile and measure slow Django test suites with Django's runner, pytest-django, shell timing, py-spy, cProfile, pytest durations, and profiler visualizations. Use when a Django project has slow tests, unclear test-runtime bottlenecks, CI timing problems, startup overhead, database setup overhead, or a request to find the slowest tests before optimizing.
compatibility
Codex, Claude Code, and other Agent Skills-compatible clients.
license
MIT
metadata.version
0.1.0
metadata.displayName
Django Test Profiling
metadata.category
Django
metadata.tags
django,testing,profiling,pytest,performance

Django Test Profiling

Use this skill before changing a Django test suite for speed. Measurement decides which optimization is worth doing; otherwise it is easy to spend time on harmless settings while the real cost sits in startup, database setup, fixture construction, or a small set of slow tests.

Measurement Workflow

  1. Capture a full wall-clock baseline.

    • Prefer shell timing because it includes Python startup, Django import time, test discovery, database setup, and teardown.
    • Record the exact command, environment, and repeat count.

  2. Separate framework phases when possible.

    • For Django's runner, use --timing to see database setup and teardown.
    • For pytest, compare shell timing with pytest --durations.

  3. Find the slowest tests.

    • For pytest-django, start with pytest --durations 20.
    • For Django's runner, use an existing slow-test plugin or a small custom runner only when the project does not already have one.

  4. Profile only after you know where the time goes.

    • Use py-spy first for a low-overhead whole-run view.
    • Use cProfile when you need exhaustive Python call data.

  5. Convert the result into a ranked action list.

    • Identify whether the expensive part is startup, database creation, repeated setup, test data, query count, I/O, cache/file/storage access, or a specific test body.
    • Hand off to django-test-performance, django-test-data, or django-test-parallelization when the next step fits those skills.

Commands

bash
time python manage.py test
python manage.py test --timing
pytest --durations 20

For profiling command variants and interpretation guidance, read profiler-commands.md.

Show full SKILL.md (173 more words)Show less

Decision Rules

  • Treat shell timing as the authoritative user-visible duration.
  • Use Django --timing when database setup or teardown may dominate.
  • Optimize the slowest measured tests first, not the tests that look suspicious.
  • Put noisy duration reports in CI logs when they distract from normal local runs.
  • Use py-spy --subprocesses when the test runner uses child processes.
  • Sort cProfile by cumulative time first; inspect self-time only after you understand the caller chain.

Common Mistakes

  • Trusting a framework's final "ran in X seconds" line as the complete runtime.
  • Comparing Django runner timing and pytest timing as if they measure identical phases.
  • Profiling everything before finding slow tests.
  • Reading unsorted cProfile output and chasing import internals.
  • Expecting sampling profiles to catch every short hot path.
  • Optimizing a helper without checking how often it is reached by tests.

Verification

Before reporting findings, include:

  • The exact baseline command and measured wall-clock time.
  • The slowest tests or slowest phases.
  • The profiler used, if any, and why it was appropriate.
  • The top 3 practical next actions, ordered by expected impact.

© 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-test-profiling of hashgraph-online/awesome-codex-plugins.

  • SKILL.md
  • references/profiler-commands.md

Open the folder on GitHubat commit 78497e5

Compare with similar skills

Django Test Profiling 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 Test Profiling compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Django Test Profiling this skillhashgraph-online/awesome-codex-plugins1.2k—~892Automated safety check: PassMIT
Maintaining Python TestsPostHog/posthog40k—~2.5kAutomated safety check: PassCustom licence
Run And Verifyaropan/clist439—~461Automated safety check: PassApache-2.0
Python Devdoccker/cc-use-exp1.1k—~790Automated 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 Test Profiling

What does Django Test Profiling do?

Profile and measure slow Django test suites with Django's runner, pytest-django, shell timing, py-spy, cProfile, pytest durations, and profiler visualizations. Django Test Profiling is an agent skill from hashgraph-online/awesome-codex-plugins. Profile and measure slow Django test suites with Django's runner, pytest-django, shell timing, py-spy, cProfile, pytest durations, and profiler visualizations.

When should I use Django Test Profiling?

Django Test Profiling fits situations like: A Django project has slow tests; unclear test-runtime bottlenecks; CI timing problems; startup overhead.

How do I install Django Test Profiling in Claude Code?

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

How do I install Django Test Profiling in Codex?

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

Can I use Django Test Profiling 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-test-profiling -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-test-profiling, .gemini/skills/django-test-profiling, .github/skills/django-test-profiling and .opencode/skills/django-test-profiling in your project.

What does Django Test Profiling need to run?

Going by SKILL.md and its folder, Django Test Profiling needs the command-line tools its instructions call (pytest and python). Our summary lists: Python 3. Compatibility (from SKILL.md): Codex, Claude Code, and other Agent Skills-compatible clients..

Does Django Test Profiling 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 Test Profiling 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 Test Profiling use?

Django Test Profiling 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 Test Profiling use?

About 892 tokens (SKILL.md is roughly 3.6k 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 572 tokens, read only when the agent opens those files.

What are the alternatives to Django Test Profiling?

Skills that share tags, products or a category with Django Test Profiling: Maintaining Python Tests (PostHog/posthog, 40k stars), Run And Verify (aropan/clist, 439 stars), Python Dev (doccker/cc-use-exp, 1.1k 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 Test Profiling?

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.