Silk Debug
letsrevel/revel-backend
Analyze Django Silk profiling data to debug slow requests, detect N+1 queries, and optimize database performance.
Diagnose and improve slow Django database-backed endpoints with evidence-first profiling, query-plan review, index selection, ORM loading fixes, batching, database-side computation, materialized…
Install Django DB Performance
$ npx skills add hashgraph-online/awesome-codex-plugins --skill django-db-performance -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins django-db-performance --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-db-performance .claude/skills/django-db-performance && rm -rf skills-srcUse ~/.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/
Install the "django-db-performance" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/LVTD-LLC/skills/skills/django-db-performance into .claude/skills/django-db-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "django-db-performance", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/LVTD-LLC/skills/skills/django-db-performanceType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill django-db-performance -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins django-db-performance --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/LVTD-LLC/skills/skills/django-db-performance .agents/skills/django-db-performance && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "django-db-performance" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/LVTD-LLC/skills/skills/django-db-performance into .agents/skills/django-db-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "django-db-performance", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill django-db-performance -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins django-db-performance --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/LVTD-LLC/skills/skills/django-db-performance .cursor/skills/django-db-performance && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "django-db-performance" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/LVTD-LLC/skills/skills/django-db-performance into .cursor/skills/django-db-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "django-db-performance", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/hashgraph-online/awesome-codex-plugins.git --path plugins/LVTD-LLC/skills/skills/django-db-performance--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill django-db-performance -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins django-db-performance --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/LVTD-LLC/skills/skills/django-db-performance .gemini/skills/django-db-performance && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "django-db-performance" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/LVTD-LLC/skills/skills/django-db-performance into .gemini/skills/django-db-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "django-db-performance", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install hashgraph-online/awesome-codex-plugins django-db-performanceInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add hashgraph-online/awesome-codex-plugins --skill django-db-performance -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/LVTD-LLC/skills/skills/django-db-performance .github/skills/django-db-performance && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "django-db-performance" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/LVTD-LLC/skills/skills/django-db-performance into .github/skills/django-db-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "django-db-performance", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill django-db-performance -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins django-db-performance --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/LVTD-LLC/skills/skills/django-db-performance .opencode/skills/django-db-performance && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "django-db-performance" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/LVTD-LLC/skills/skills/django-db-performance into .opencode/skills/django-db-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "django-db-performance", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
django-db-performance- GitHub stars
- 1.2k
- Token cost
- ~888 tokens
- SKILL.md length
- 364 words
- Files
- 2 (incl. references)
- Skills in repo
- 736
- Repo updated
- First seen
- Licence
- MIT
At a glance
Diagnose and improve slow Django database-backed endpoints with evidence-first profiling, query-plan review, index selection, ORM loading fixes, batching, database-side computation, materialized…
- Works in 5 steps: Capture the symptom. → Profile before changing code. → Classify the dominant problem. → …
- Database query is slow and the right optimization path is not obvious
- SKILL.md covers Core Workflow, Modern Django Notes and Verification
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Django DB Performance is an agent skill from hashgraph-online/awesome-codex-plugins. Diagnose and improve slow Django database-backed endpoints with evidence-first profiling, query-plan review, index selection, ORM loading fixes, batching, database-side computation, materialized views, and pagination choices. Use when a Django view, API, job, report, queryset, or database query is slow and the right optimization path is not obvious.
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/diagnostic-flow.md`). Compatibility notes: Codex, Claude Code, and other Agent Skills-compatible clients.
It sits in Backend & APIs, covering Backend development and Query optimization. It works with Django. 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
- Database query is slow and the right optimization path is not obvious
- Tasks that involve Backend development
- Tasks that involve Query optimization
Example prompts
- “/django-db-performance”
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.
- Capture the symptom.
- Profile before changing code.
- Classify the dominant problem.
- Apply one change at a time.
- Verify and document the result.
What it can do on your machine
Read from SKILL.md and the folder at commit 16b4156. 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 DB Performance loads about 888 tokens when it runs, and up to ~1.6k if it reads all its reference files. Until then it costs about 93 tokens; SKILL.md has 364 words of instructions outside code blocks.
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 16b4156, republished under its MIT licence (© hashgraph-online). 364 words, ~888 tokens.
Download SKILL.mdSave it as
.claude/skills/django-db-performance/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- django-db-performance
- description
- Diagnose and improve slow Django database-backed endpoints with evidence-first profiling, query-plan review, index selection, ORM loading fixes, batching, database-side computation, materialized views, and pagination choices. Use when a Django view, API, job, report, queryset, or database query is slow and the right optimization path is not obvious.
- compatibility
- Codex, Claude Code, and other Agent Skills-compatible clients.
- license
- MIT
- metadata.version
- 0.1.0
- metadata.displayName
- Django DB Performance
- metadata.category
- Django
- metadata.tags
- django,database,performance,orm,profiling
Django DB Performance
Use this as the orchestration skill for Django database performance work. Start with measured evidence, reproduce the slow path, and route to the smallest optimization that changes the measured bottleneck.
Core Workflow
Capture the symptom.
- Identify the exact endpoint, command, task, report, or queryset.
- Record current wall-clock time, query count, slow SQL, database backend, data volume, and Django version.
- Keep the original request parameters or fixture that reproduces the issue.
Profile before changing code.
- Use APM traces, database slow-query logs, Django Debug Toolbar,
connection.queries, or targeted logging. - If the expensive query is known, use
QuerySet.explain()or databaseEXPLAIN. - For API endpoints, profile serializers and permission checks as well as querysets.
- Use APM traces, database slow-query logs, Django Debug Toolbar,
Classify the dominant problem.
- Many repeated similar queries: use
django-orm-query-optimization. - One or two expensive SQL statements: use
django-query-plan-readinganddjango-index-design. - Large memory use or long loops over querysets: use
django-queryset-batch-processing. - Python loops computing counts, totals, flags, or latest related rows: use
django-db-side-computation. - Slow aggregate/report query that is acceptable when stale: use
django-materialized-views. - Slow or inconsistent list pages: use
django-pagination-performance. - Unclear evidence: use
django-query-profiling.
- Many repeated similar queries: use
Apply one change at a time.
- Prefer the narrowest change with a clear expected effect.
- Avoid adding indexes, prefetches, or materialized views speculatively.
- Confirm that the optimization helps real production-like data, not only tiny fixtures.
Verify and document the result.
- Re-run the same request or command with the same parameters.
- Compare query count, total DB time, wall-clock time, memory, and query plan.
- Keep before/after evidence in the PR or final report.
See diagnostic-flow.md for routing checklists, common symptoms, and before/after evidence templates.
Show full SKILL.md (101 more words)Show less
Modern Django Notes
- Prefer
QuerySet.explain()for ORM query plans before dropping to rawEXPLAIN. - Prefer native Django/PostgreSQL migration operations such as
AddIndexConcurrentlyover hand-written concurrent index SQL when they fit. - Prefer ORM expressions,
Subquery,Exists,Window,GeneratedField, anddb_defaultwhen they make database work explicit and portable enough. - Treat every backend-specific optimization as conditional on the project database. PostgreSQL patterns do not automatically apply to MySQL, MariaDB, SQLite, or Oracle.
Verification
- Show the slow path is still functionally correct.
- Show the measured bottleneck improved.
- Show the optimization did not create a worse query, stale data bug, write-path regression, or memory spike.
© 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-db-performance of hashgraph-online/awesome-codex-plugins.
- SKILL.md
- references/diagnostic-flow.md
Open the folder on GitHubat commit 16b4156
Compare with similar skills
Django DB Performance 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Django DB Performance this skillhashgraph-online/awesome-codex-plugins | 1.2k | — | ~888 | Automated safety check: Pass | MIT | |
| Silk Debugletsrevel/revel-backend | 109 | — | ~1.2k | Automated safety check: Pass | MIT | |
| Dsqlawslabs/agent-plugins | 912 | — | ~6.9k | Automated safety check: Pass | Apache-2.0 | |
| Profiling Slow API EndpointsPostHog/posthog-foss | 721 | — | ~1k | Automated safety check: Pass | MIT | |
| Saleor Django Schema Migrationsaleor/saleor | 23k | — | ~1k | Automated safety check: Pass | BSD-3-Clause | |
| Lerdliberusoftware/real-estate-laravel | 112 | — | ~7.8k | Automated safety check: Warn | MIT |
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Related
Works with
Categories
Questions about Django DB Performance
What does Django DB Performance do?
Diagnose and improve slow Django database-backed endpoints with evidence-first profiling, query-plan review, index selection, ORM loading fixes, batching, database-side computation, materialized…. Django DB Performance is an agent skill from hashgraph-online/awesome-codex-plugins. Diagnose and improve slow Django database-backed endpoints with evidence-first profiling, query-plan review, index selection, ORM loading fixes, batching, database-side computation, materialized views, and pagination choices.
When should I use Django DB Performance?
Django DB Performance fits situations like: database query is slow and the right optimization path is not obvious; tasks that involve Backend development; tasks that involve Query optimization.
How do I install Django DB Performance in Claude Code?
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill django-db-performance -a claude-code`. Or copy the skill folder (plugins/LVTD-LLC/skills/skills/django-db-performance in hashgraph-online/awesome-codex-plugins) into .claude/skills/django-db-performance in your project. Claude Code loads it when a task matches its description.
How do I install Django DB Performance in Codex?
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill django-db-performance -a codex`. Or copy the skill folder (plugins/LVTD-LLC/skills/skills/django-db-performance in hashgraph-online/awesome-codex-plugins) into .agents/skills/django-db-performance in your project. Codex loads it when a task matches its description.
Can I use Django DB Performance 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-db-performance -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-db-performance, .gemini/skills/django-db-performance, .github/skills/django-db-performance and .opencode/skills/django-db-performance in your project.
What does Django DB Performance need to run?
SKILL.md names no scripts, command-line tools or credentials: Django DB Performance is instructions for the agent only. Our summary lists: Python 3. Compatibility (from SKILL.md): Codex, Claude Code, and other Agent Skills-compatible clients..
Does Django DB Performance 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 DB Performance 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 DB Performance use?
Django DB Performance 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 DB Performance use?
About 888 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 673 tokens, read only when the agent opens those files.
What are the alternatives to Django DB Performance?
Skills that share tags, products or a category with Django DB Performance: Silk Debug (letsrevel/revel-backend, 109 stars), Dsql (awslabs/agent-plugins, 912 stars), Profiling Slow API Endpoints (PostHog/posthog-foss, 721 stars) and Saleor Django Schema Migration (saleor/saleor, 23k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Django DB Performance?
hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,232 GitHub stars. The repository holds 736 skills in this directory. The repository was last updated on October 6, 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.