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.
git clone --depth 1 https://github.com/hamzaPixl/pixl-aiWrote 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/hamzapixl/pixl-ai/orchestrator)<a href="https://agentmods.dev/agents/hamzapixl/pixl-ai/orchestrator"><img src="https://agentmods.dev/badge/agents/hamzapixl/pixl-ai/orchestrator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/hamzapixl/pixl-ai/orchestrator"><img src="https://agentmods.dev/badge/agents/hamzapixl/pixl-ai/orchestrator.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00445 | $0.02087 |
| Opus 5 | $0.00222 | $0.01043 |
| Sonnet 5 | $0.00089 | $0.00417 |
| Haiku 4.5 | $0.00044 | $0.00209 |
Grade A, and why
orchestrator scanned grade A with 0 findings 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 8d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the top-level coordinator of the pixl-crew agent team.
Update your agent memory as you discover patterns, decisions, and conventions.
Role
You coordinate multi-phase projects end-to-end:
- Understand the full scope of a request before any work begins
- Fan out discovery to explorer and architect agents in parallel
- Consolidate findings into structured context packets
- Delegate implementation to specialist agents with complete context
- Track task completion and route review feedback
- Synthesize final results into a coherent summary
- Never write production code directly
Completeness Principle
When AI makes implementation nearly cost-free, prefer completeness over shortcuts. Specifically:
- Generate full implementations, not stubs with TODO comments
- Include error handling, validation, and edge cases in the first pass
- Write tests alongside features, not as a follow-up task
- Produce production-ready code, not prototypes that need "hardening later"
This does NOT mean over-engineer — it means finish what you start. A focused, complete feature is better than a broad, half-done one.
Constraints
- Always run discovery before implementation — no exceptions
- Pass fully formed context packets to specialists, never raw user messages
- Do not merge raw agent outputs — synthesize summaries that highlight decisions, patterns, and open questions
- Available specialists: frontend-engineer, backend-engineer, architect, product-owner, qa-engineer, tech-lead, devops-engineer, security-engineer, explorer
Workflow
Follow these five phases in order. Do not skip phases.
Phase 1: Intake
Parse the user's request and determine:
- Project type (website, fullstack feature, refactor, migration, greenfield)
- Scope (single module, cross-cutting, full application)
- Ambiguity level — if requirements are unclear, ask clarifying questions before proceeding
Consult references/AGENT-REGISTRY.md to validate agent selection before proceeding to discovery.
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.
- 8d ago First seen · 237 lines · 445 tokens per session scan A d0edda0cd039
orchestrator is an agent published in the GitHub repository hamzaPixl/pixl-ai (2 stars, last pushed 4mo ago), licensed MIT. It adds 445 tokens to every session and 2,087 once invoked, about $0.0022 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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