phoenix-orchestrator

phoenix-orchestrator is a skill for Claude Code from Security-Phoenix-demo/security-skills-claude-code. It costs 170 tokens per session (1,419 once invoked), scanned A, original, MIT.

A workflow coordinator that runs the ten-step Phoenix Security specification process in order, from raw context through requirements, security design, verification, planning, and final review.

In plain words
What is it for?
Use it to create a ship-ready product requirements document, a Cursor implementation plan, and a Confluence page from Phoenix feature input.
Why use it?
It removes the need to manually manage handoffs between specialist steps and helps produce consistent project documents.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the phoenix-prd-pipeline plugin — 13 skills shipped together

Good fit Use it to create a ship-ready product requirements document, a Cursor implementation plan, and a Confluence page from Phoenix feature input.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/security-phoenix-demo/security-skills-claude-code/phoenix-orchestrator
Install

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.

Any agent
npx skills add Security-Phoenix-demo/security-skills-claude-code --skill phoenix-orchestrator
Clone the repo
git clone --depth 1 https://github.com/Security-Phoenix-demo/security-skills-claude-code

Made for: Claude Code.

Or install phoenix-prd-pipeline, the plugin that ships this one along with the rest of its 13 skills.

Wrote 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.

agentmods badge for phoenix-orchestrator

README.md
[![agentmods](https://agentmods.dev/badge/skills/security-phoenix-demo/security-skills-claude-code/phoenix-orchestrator/github.svg)](https://agentmods.dev/skills/security-phoenix-demo/security-skills-claude-code/phoenix-orchestrator)
Your own site
<a href="https://agentmods.dev/skills/security-phoenix-demo/security-skills-claude-code/phoenix-orchestrator"><img src="https://agentmods.dev/badge/skills/security-phoenix-demo/security-skills-claude-code/phoenix-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.

agentmods 80×15 button for phoenix-orchestrator

Your own site · 80×15
<a href="https://agentmods.dev/skills/security-phoenix-demo/security-skills-claude-code/phoenix-orchestrator"><img src="https://agentmods.dev/badge/skills/security-phoenix-demo/security-skills-claude-code/phoenix-orchestrator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 170 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,419 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00170 $0.01419
Opus 5 $0.00085 $0.00709
Sonnet 5 $0.00034 $0.00284
Haiku 4.5 $0.00017 $0.00142

Measured yesterday against content hash bf642ca8e47b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

phoenix-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 yesterday.

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.

plugins/phoenix-prd-pipeline/skills/phoenix-orchestrator/SKILL.md · 146 lines

How it starts

The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Phoenix Security — Pipeline Orchestrator

What This Does

Runs roles 01–10 sequentially, validates each output, manages the 04↔05 iteration loop, and produces a ship-ready Phoenix PRD + Cursor plan + Confluence page.


Phoenix Domain Context (carry through every role)

Product Pillars

ASPM · CTEM · Container Lineage · Reachability Analysis · Supply Chain / SCA · DevSecOps · LLM Security · Board-Level Reporting

Active Integrations

GitHub Advanced Security, Snyk (SCA eval), Qualys, Prisma (being displaced), Wiz (replacing Prisma at Anaplan), Azure Security Center, Backstage, Jenkins, AWS (core), GCP (CTI + AI)

Key Stakeholders

Role Name
CEO / Product Owner Francesco Cipollone
CTO Alfonso Eusebio
CRO Philip Moroni

Active Enterprise Accounts

  • Mimecast — replacing Prisma, Snyk SCA eval, multi-cloud + on-prem, container lineage
  • Johnson Matthey — OT/manufacturing, GitHub AS + Azure SC + Qualys, reachability + maturity model
  • Anaplan — Prisma → Wiz, Jenkins gating, board-level risk reporting (10 categories)

Case Study Benchmarks

  • ClearBank: 98% container vuln reduction, $15M dev time saved
  • Bazaarvoice: 94% container reduction, $6.3M saved, 32K rules via Backstage
  • IAS: 78% false positive reduction, $1.7M+ saved

Competitors (handle carefully in external content)

Prisma · Wiz · ArmorCode · Snyk


Pipeline Execution Flow

Phase 1 — Foundation (Roles 01–03)

Raw Context
  → [01] Context Curator      → CLEAN_CONTEXT (≤900 tokens)
  → [02] Scope Cutter         → SCOPE_DEFINITION (≤800 tokens)
  → [03] Constraint Distiller → ACTIVE_SET (≤700 tokens)

Phase 2 — Requirements Loop (Roles 04–05, max 3 iterations)

  → [04] Requirements Engineer → NORMATIVE_REQUIREMENTS (≤1500 tokens)
  → [05] Ambiguity Hunter      → CLARIFICATIONS
       If critical > 0 → back to [04] (max 3 iterations)
       If critical = 0 → Phase 3

Phase 3 — Security & Contracts (Roles 06–07)

  → [06] Security Engineer    → SECURITY_REQUIREMENTS (≤1200 tokens)
  → [07] Contract Architect   → CONTRACTS (≤1200 tokens)

Read the full file on GitHub · 146 lines

Changes

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.

  1. yesterday First seen · 146 lines · 170 tokens per session scan A bf642ca8e47b

Subscribe to this mod's changes

phoenix-orchestrator is a skill published in the GitHub repository Security-Phoenix-demo/security-skills-claude-code (70 stars, last pushed yesterday), licensed MIT. It adds 170 tokens to every session and 1,419 once invoked, about $0.0009 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 2026-09-11.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens