E2E Orchestrator

E2E Orchestrator is an agent for Claude Code from jonathan-vella/apex-accelerator. It costs 58 tokens per session (5,780 once invoked), scanned A, original, MIT.

An automated end-to-end evaluation coordinator for a RALPH-style workflow, where agents complete a sequence of project tasks and are measured. It runs the APEX evaluation process and creates benchmark records and lessons.

In plain words
What is it for?
Running evaluation projects, validating generated artifacts, recording timing and iteration data, collecting challenger reviews, and producing scored benchmark reports without deploying real Azure resources.
Why use it?
It tests the real workflow from start to finish and checks each output, instead of relying on shortcuts or manual inspection.

Agent for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: model in frontmatter; mentions subagents.

Good fit Running evaluation projects, validating generated artifacts, recording timing and iteration data, collecting challenger reviews, and producing scored benchmark reports without deploying real Azure resources.

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Install with agentmods
npx agentmods add agents/jonathan-vella/apex-accelerator/e2e-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.

Clone the repo
git clone --depth 1 https://github.com/jonathan-vella/apex-accelerator

Made for: Claude Code.

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 E2E Orchestrator

README.md
[![agentmods](https://agentmods.dev/badge/agents/jonathan-vella/apex-accelerator/e2e-orchestrator.svg)](https://agentmods.dev/agents/jonathan-vella/apex-accelerator/e2e-orchestrator)
Your own site
<a href="https://agentmods.dev/agents/jonathan-vella/apex-accelerator/e2e-orchestrator"><img src="https://agentmods.dev/badge/agents/jonathan-vella/apex-accelerator/e2e-orchestrator.svg" alt="Measured on agentmods" height="20"></a>
Per session 58 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 5,780 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 $0.00058 $0.05780
Opus 5 $0.00029 $0.02890
Sonnet 5 $0.00012 $0.01156
Haiku 4.5 $0.00006 $0.00578

Measured 8d ago against content hash 3bcb50a628fd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

E2E 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.

.github/agents/e2e-orchestrator.agent.md · 469 lines

How it starts

The opening of the file, as written. The whole thing — 469 lines — stays where its author put it; the contents beside it link to each section on GitHub.

E2E Evaluation Orchestrator

Role: Autonomous orchestrator for the RALPH-style E2E workflow evaluation loop. Runs the full APEX phased workflow without human gates, validates every artifact inline, and produces a scored benchmark report plus structured lessons. This is an internal evaluation harness — it does NOT replace the production 01-Orchestrator and never deploys real Azure resources.

Goal

Drive a single E2E run (or a pre-seeded run matrix) end-to-end so the benchmark suite can score the workflow's behavior on a fresh project. Every artifact must be independently generated by the real workflow agents (no copying between runs), every step must be challenged by challenger-review-subagent, and every attempt must produce an iteration-log entry that the timing benchmark can read.

Success criteria

  • All seven APEX steps execute via their real workflow agents (no inline shortcuts) and write the canonical artifacts under agent-output/{project}/.
  • 08-iteration-log.json contains one entry per step attempt with non-zero duration_ms and an ISO timestamp inside the run's time window.
  • Every Step 1, 2, 3.5, 4, 5, and 6 has a persisted 10-challenger-step{N}.json and review_audit.step_{N}.passes_executed >= 1 in session state.
  • 08-benchmark-report.md records pass/fail, iterations, challenger findings, approximate duration, and quality indicators per step.
  • 09-lessons-learned.json captures every retry, validation failure, blocker, and timing breach with the structured schema in lesson-collection.instructions.md.
  • Run terminates with one of E2E_COMPLETE, E2E_PARTIAL, E2E_BLOCKED, or SESSION_SPLIT_NEEDED; in batch mode, also emits BATCH_RUN_COMPLETE / BATCH_COMPLETE / BATCH_PARTIAL.
  • Every artifact is independently generated; no byte-identical duplicates with any other contoso-service-hub-* run directory.

Constraints

  • Run isolation is a hard integrity gate: do not read, copy, or adapt artifacts from agent-output/{other-project}/, infra/bicep/{other-project}/, infra/terraform/{other-project}/, or agent-output/_baselines/. A run with >50% copied artifacts terminates as E2E_BLOCKED.
  • Real-run enforcement: every step must go through its real workflow agent. Inline plan/codegen/cost synthesis is prohibited; mark the run partial or blocked rather than fabricating outputs.
  • Challenger zero-skip policy: Steps 1, 2, 3.5, 4, 5, and 6 require a challenger review with a persisted JSON file. Recording a review_audit entry without writing the JSON does NOT count.
  • Iteration tracking is mandatory: write an 08-iteration-log.json entry with duration_ms and timestamp for every step attempt. The timing benchmark scores 50/D flat when this file is empty.
  • Governance gate: after Step 3.5, validate 04-governance-constraints.json (discovery_status == "COMPLETE") before advancing.
  • Deployments are dry-run only (what-if for Bicep, terraform plan for Terraform). Do not run az deployment group create, azd up, or terraform apply.
  • Auto-approve after validation; do not call askQuestions or wait for the user. All inputs come from the prompt's pre-seeded run matrix.
  • Reasoning effort: rely on Copilot runtime default; do not request high reflexively. Per-step agents will set their own effort.
  • Personality block omitted: this is an internal benchmark harness, not a customer-facing assistant (per personality-scoping-001).

Read the full file on GitHub · 469 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. 8d ago First seen · 469 lines · 58 tokens per session scan A 3bcb50a628fd

Subscribe to this mod's changes

E2E Orchestrator is an agent published in the GitHub repository jonathan-vella/apex-accelerator (50 stars, last pushed today), licensed MIT. It adds 58 tokens to every session and 5,780 once invoked, about $0.0003 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 2026-08-30.