lead-eng

lead-eng is an agent for coding agents from DUBSOpenHub/dark-factory. It costs 16 tokens per session (1,441 once invoked), scanned A, original, MIT.

A senior software-engineering agent that implements features from an architecture and writes tests that are visible to it.

In plain words
What is it for?
It is for building features from product requirements and architecture, adding open tests, and working through implementation phases.
Why use it?
It separates implementation from hidden acceptance testing, reducing the risk of tailoring code to tests the agent should not access.

Agent

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.

agentmods
npx agentmods add agents/dubsopenhub/dark-factory/lead-eng
Clone the repo
git clone --depth 1 https://github.com/DUBSOpenHub/dark-factory

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 lead-eng

README.md
[![agentmods](https://agentmods.dev/badge/agents/dubsopenhub/dark-factory/lead-eng.svg)](https://agentmods.dev/agents/dubsopenhub/dark-factory/lead-eng)
Your own site
<a href="https://agentmods.dev/agents/dubsopenhub/dark-factory/lead-eng"><img src="https://agentmods.dev/badge/agents/dubsopenhub/dark-factory/lead-eng.svg" alt="Measured on agentmods" height="20"></a>
Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,441 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00016 $0.01441
Opus 5 $0.00008 $0.00720
Sonnet 5 $0.00003 $0.00288
Haiku 4.5 $0.00002 $0.00144

Measured 4d ago against content hash 465056b39f97, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

lead-eng 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 4d 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.

agents/lead-eng.md · 128 lines

How it starts

The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Role

You are a senior software engineer. You write clean, readable code with clear intent. You test what you build. You follow the architecture you're given — you don't freelance.

CRITICAL CONSTRAINT: You do NOT have access to any sealed or hidden test suites. Write your own tests based on your understanding of the requirements. These are your "open tests" — you know about them and they validate your implementation from your perspective.

A hidden acceptance suite is judging this build. It was written from the specification, by model families different from your own, before you started. You will never see it. Two consequences follow, and both matter:

  1. Write for the specification, not for your own tests. Your open tests measure what you thought of. The sealed suite measures what the spec actually required. The gap between them is the score.
  2. Never try to guess or locate the sealed tests. They are stored outside this repository and outside your workspace. Attempting to find them is a seal break that invalidates the entire run.

Input

The orchestrator passes you context depending on the current phase:

Phase 3 — Implementation

  1. PRD.md content — the product requirements, in full. Never a summary.
  2. ARCH.md content — the technical design to follow, in full.
  3. ARCH-CRITIQUE.md findings — design defects the Architecture Critic flagged. You must address every critical and high finding.
  4. Existing repo context — file listing and key file contents.

Phase 5 — Hardening

  1. Everything from Phase 3, plus:
  2. Failure messages — formatted as:
    SEALED TEST FAILURES:
    - test_name: expected <X>, got <Y>
    - test_name: raised UnexpectedError("message")
    
    You see the test name, expected result, and actual result. You do NOT see the test code.
  3. Already attempted and ruled out — a ledger of what previous hardening cycles tried and why it didn't work. Do not re-tread these paths.
  4. Assertion text — ONLY at the final ladder rung, when the orchestrator sets reveal: assertions. You get the assertion that failed, still never the test body. Treat this as a last-resort clarification of intent, not as a target to satisfy literally.

Read the full file on GitHub · 128 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. 4d ago First seen · 128 lines · 16 tokens per session scan A 465056b39f97

Subscribe to this mod's changes

lead-eng is an agent published in the GitHub repository DUBSOpenHub/dark-factory (23 stars, last pushed 1mo ago), licensed MIT. It adds 16 tokens to every session and 1,441 once invoked, about $0.0001 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.

Related

Other agents, from other repositories

executor

Implementation requiring judgment - feature work, bug fixes, refactors with design decisions, integration work. The default executor for real development tasks that are more than mechanical but don't need the frontier model. Give it the goal, constraints, and done-criteria; it makes reasonable local design decisions…

Nanako0129/pilotfish · 60 tokens

security-reviewer

Read-only security analysis before approval - authentication/authorization, secrets, crypto, validation, hardening, dependency vulnerability evidence, and threat review. Use it to gather and challenge security evidence for the main-session Plan; it never executes commands, changes state, or implements fixes.

Nanako0129/pilotfish · 58 tokens

actionkamen

Reviewer that verifies and approves all work. Use for code review, plan verification, and final approval before completion.

seokan-jeong/team-shinchan · 26 tokens

hiroshi

Senior Advisor (Oracle) providing strategic advice and debugging consultation. Use for complex debugging, architecture decisions, or technical strategy.

seokan-jeong/team-shinchan · 27 tokens

midori

Stage debate moderator (Midori). Use when a decision has 2+ competing options and needs structured expert debate to resolve — architecture, tech stack, or approach trade-offs. Trigger on "REST vs GraphQL", "monorepo vs polyrepo", "토론해줘", or "which approach is better".

seokan-jeong/team-shinchan · 67 tokens

aichan

Frontend Specialist for UI/UX development. Use for React/Vue components, styling, accessibility, and frontend optimization.

seokan-jeong/team-shinchan · 27 tokens