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Agent skill

Django Query Profiling

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

Find the Django ORM code and request path responsible for slow SQL by using APM traces, slow query logs, Django Debug Toolbar, query logging, and local reproduction.

MITAuto-check passedBackend & APIs

Install Django Query Profiling

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

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

GitHub CLI
$ gh skill install hashgraph-online/awesome-codex-plugins django-query-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-query-profiling .claude/skills/django-query-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-query-profiling
GitHub stars
1.2k
Token cost
~644 tokens
SKILL.md length
260 words
Files
2 (incl. references)
Skills in repo
686
Repo updated
First seen
Licence
MIT

At a glance

Find the Django ORM code and request path responsible for slow SQL by using APM traces, slow query logs, Django Debug Toolbar, query logging, and local reproduction.

  • Works in 5 steps: Start from the user-visible slow path. → Collect production or staging evidence. → Map SQL back to Django code. → …
  • A Django database performance issue is suspected but the exact queryset
  • SKILL.md covers Workflow, Good Evidence and Verification
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Django Query Profiling is an agent skill from hashgraph-online/awesome-codex-plugins. Find the Django ORM code and request path responsible for slow SQL by using APM traces, slow query logs, Django Debug Toolbar, query logging, and local reproduction. Use when a Django database performance issue is suspected but the exact queryset, view, serializer, template, or job causing it is not yet proven.

Its SKILL.md is about 640 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/tooling-and-reproduction.md`). Compatibility notes: Codex, Claude Code, and other Agent Skills-compatible clients.

It sits in Backend & APIs, covering Backend development, Query optimization and Monitoring and alerting. It works with Django and SQL. 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 database performance issue is suspected but the exact queryset
  • Job causing it is not yet proven

Example prompts

  • “/django-query-profiling”

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. Start from the user-visible slow path.
  2. Collect production or staging evidence.
  3. Map SQL back to Django code.
  4. Reproduce locally or in a safe shell.
  5. Route the fix.

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 Query Profiling loads about 644 tokens when it runs, and up to ~1.3k if it reads all its reference files. Until then it costs about 84 tokens; SKILL.md has 260 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~84
When it runs · the whole SKILL.md, loaded when a task matches
~644
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.3k

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). 260 words, ~644 tokens.

Download SKILL.mdSave it as .claude/skills/django-query-profiling/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
django-query-profiling
description
Find the Django ORM code and request path responsible for slow SQL by using APM traces, slow query logs, Django Debug Toolbar, query logging, and local reproduction. Use when a Django database performance issue is suspected but the exact queryset, view, serializer, template, or job causing it is not yet proven.
compatibility
Codex, Claude Code, and other Agent Skills-compatible clients.
license
MIT
metadata.version
0.1.0
metadata.displayName
Django Query Profiling
metadata.category
Django
metadata.tags
django,database,profiling,apm,debug-toolbar

Django Query Profiling

Use this skill to turn a vague slow-Django report into a specific queryset, SQL statement, and reproducible scenario.

Workflow

  1. Start from the user-visible slow path.

    • Record the URL, API action, background task, management command, or report.
    • Capture request parameters, user or tenant shape, pagination state, and data volume.

  2. Collect production or staging evidence.

    • Prefer APM transaction traces when available.
    • Use database slow-query logs for SQL that is slow independent of Python.
    • Use Django Debug Toolbar for server-rendered pages in local development.
    • For APIs or jobs, add targeted query logging around the suspicious block.

  3. Map SQL back to Django code.

    • Search model table names and column names.
    • Inspect view get_queryset(), serializer fields, template loops, managers, model properties, and signal handlers.
    • Check whether related-object access happens after the initial queryset was evaluated.

  4. Reproduce locally or in a safe shell.

    • Use production-like row counts when possible.
    • Disable unrelated instrumentation and debug-only middleware when measuring.
    • Keep a repeatable script, test, or shell snippet that exercises the slow path.

  5. Route the fix.

    • Query count issue: use django-orm-query-optimization.
    • One slow SQL statement: use django-query-plan-reading.
    • Large loops or writes: use django-queryset-batch-processing.

See tooling-and-reproduction.md for concrete profiling snippets and pitfalls.

Good Evidence

  • Query count before/after for the specific path.
  • The slow SQL or normalized SQL fingerprint.
  • Stack or code pointer that explains where the SQL originates.
  • Timing from the same environment and representative data shape.

Verification

Do not finish profiling with only a hunch. Finish with a named queryset, code path, and command or request that another agent can re-run.

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

  • SKILL.md
  • references/tooling-and-reproduction.md

Open the folder on GitHubat commit 78497e5

Compare with similar skills

Django Query 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 Query Profiling compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Django Query Profiling this skillhashgraph-online/awesome-codex-plugins1.2k—~644Automated safety check: PassMIT
Dsqlawslabs/agent-plugins915—~6.9kAutomated safety check: PassApache-2.0
Profiling Slow API EndpointsPostHog/posthog40k—~1kAutomated safety check: PassCustom licence
Arch Wikiahmedemad3/arch-wiki249—~5.1kAutomated safety check: PassNone
Silk Debugletsrevel/revel-backend109—~1.2kAutomated safety check: PassMIT
Migration CodegenAHS12/thoth-blueprint626—~425Automated safety check: PassGPL-3.0

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Works with

Categories

Questions about Django Query Profiling

What does Django Query Profiling do?

Find the Django ORM code and request path responsible for slow SQL by using APM traces, slow query logs, Django Debug Toolbar, query logging, and local reproduction. Django Query Profiling is an agent skill from hashgraph-online/awesome-codex-plugins. Find the Django ORM code and request path responsible for slow SQL by using APM traces, slow query logs, Django Debug Toolbar, query logging, and local reproduction.

When should I use Django Query Profiling?

Django Query Profiling fits situations like: A Django database performance issue is suspected but the exact queryset; job causing it is not yet proven.

How do I install Django Query Profiling in Claude Code?

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

How do I install Django Query Profiling in Codex?

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

Can I use Django Query 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-query-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-query-profiling, .gemini/skills/django-query-profiling, .github/skills/django-query-profiling and .opencode/skills/django-query-profiling in your project.

What does Django Query Profiling need to run?

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

Does Django Query 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 Query 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 Query Profiling use?

Django Query 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 Query Profiling use?

About 644 tokens (SKILL.md is roughly 2.6k 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 687 tokens, read only when the agent opens those files.

What are the alternatives to Django Query Profiling?

Skills that share tags, products or a category with Django Query Profiling: Dsql (awslabs/agent-plugins, 915 stars), Profiling Slow API Endpoints (PostHog/posthog, 40k stars), Arch Wiki (ahmedemad3/arch-wiki, 249 stars) and Silk Debug (letsrevel/revel-backend, 109 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Django Query 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.