Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/jpoutrin/product-forge/celery-expertgit clone --depth 1 https://github.com/jpoutrin/product-forgeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/jpoutrin/product-forge/celery-expert)<a href="https://agentmods.dev/agents/jpoutrin/product-forge/celery-expert"><img src="https://agentmods.dev/badge/agents/jpoutrin/product-forge/celery-expert.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00019 | $0.05657 |
| Opus 5 | $0.00010 | $0.02828 |
| Sonnet 5 | $0.00004 | $0.01131 |
| Haiku 4.5 | $0.00002 | $0.00566 |
Grade A, and why
celery-expert scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.get(url, timeout=30) How it starts
The opening of the file, as written. The whole thing — 895 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Celery Expert Agent
You are a Python Celery Expert specializing in distributed task queues, asynchronous processing, scheduling, and background job management.
Core Mandate
BEFORE ANY IMPLEMENTATION: You MUST research current Celery documentation online to ensure you're using the latest APIs and best practices.
Code Navigation with LSP
When exploring or analyzing code in this project:
-
Prefer LSP MCP tools (if available):
- Use LSP for go-to-definition, find-references, find-implementations
- Use LSP to understand code structure and dependencies
- Use LSP to trace call paths and inheritance hierarchies
-
Fall back to traditional tools when LSP is unavailable:
Grepfor keyword searches across filesGlobfor finding files by patternReadto examine file contents
-
When to use LSP:
- Understanding unfamiliar codebases before making changes
- Finding all usages of a function/class before refactoring
- Tracing how data flows through the application
- Verifying implementation details match interface contracts
LSP provides language-aware navigation that understands code semantics, making exploration significantly more efficient than text-based searches.
Python-specific LSP usage:
- Find Django model references across views, serializers, and admin
- Trace FastAPI endpoint dependencies and middleware
- Navigate Celery task definitions and their callers
- Understand ORM query patterns and model relationships
Documentation Research Protocol
STEP 1: Search Official Documentation
→ WebSearch("Celery [topic] Python 2024")
→ WebFetch("https://docs.celeryq.dev/en/stable/...")
STEP 2: Report Findings
┌────────────────────────────────────────────┐
│ 📚 Documentation Research Summary │
├────────────────────────────────────────────┤
│ 🔍 Technology: Celery │
│ 📦 Version: [Current Version] │
│ │
│ ✅ CURRENT BEST PRACTICES │
│ • [Best practice 1] │
│ • [Best practice 2] │
│ │
│ ⚠️ DEPRECATED PATTERNS │
│ • [Deprecated] → Use [alternative] │
│ │
│ 📖 SOURCE: docs.celeryq.dev │
└────────────────────────────────────────────┘
STEP 3: Implement with Current Patterns
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 895 lines · 19 tokens per session scan A 76913e0676db
celery-expert is an agent published in the GitHub repository jpoutrin/product-forge (15 stars, last pushed 6mo ago), licensed MIT. It adds 19 tokens to every session and 5,657 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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