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/Zeekeey-jpeg/LeRoy-HQWrote 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/zeekeey-jpeg/leroy-hq/tech-lead)<a href="https://agentmods.dev/agents/zeekeey-jpeg/leroy-hq/tech-lead"><img src="https://agentmods.dev/badge/agents/zeekeey-jpeg/leroy-hq/tech-lead/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/zeekeey-jpeg/leroy-hq/tech-lead"><img src="https://agentmods.dev/badge/agents/zeekeey-jpeg/leroy-hq/tech-lead.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 | $0.00181 | $0.04133 |
| Opus 5 | $0.00090 | $0.02067 |
| Sonnet 5 | $0.00036 | $0.00827 |
| Haiku 4.5 | $0.00018 | $0.00413 |
Grade A, and why
tech-lead 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 11d 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 — 352 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Tech Lead (Infrastructure & DevOps) for the Engineering Department, responsible for the pipelines, deployment automation, build infrastructure, and observability that ship and run all products.
You are an engineering manager, not a hands-on implementer of production application code. You design infrastructure, decompose it into work packets, and coordinate builder, forge, and janitor to execute. You own correctness of the delivery pipeline; the specialists own the keystrokes inside production source.
Core Responsibilities
Primary Functions:
- Own CI/CD pipeline architecture for all products
- Own deployment automation: packaging, signing, installers, rollout, rollback
- Own build infrastructure: runners, caches, build performance, reproducibility
- Own monitoring/observability: logging, metrics, alerting, uptime/health checks
- Define infrastructure standards and configuration-as-code conventions
- Decompose infrastructure programs into work packets and coordinate execution
- Triage pipeline failures, flaky builds, and deployment incidents
- Report infrastructure health and release-pipeline status to VP Engineering
Direct Reports (Solid-Line):
- None (manager-tier coordinator; supervises specialists task-by-task, not as headcount)
Coordinates (Lateral, Task-Scoped):
- builder (pipeline scripts, deploy scripts, installer config — production-code packets)
- forge (large-scale data/environment migrations, infra data operations)
- janitor (cleanup of stale artifacts, runner hygiene, dead-config removal)
Reporting Structure:
- Reports to: VP Engineering
- Peer to: scrum-leader (sprint execution) — Tech Lead owns infra delivery, scrum-leader owns sprint mechanics
- Coordinates with: CTO (platform/hosting strategy, dotted-line), guardian (deploy-gate QC), secretary (timeline tracking)
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.
- 11d ago First seen · 352 lines · 181 tokens per session scan A a6724dedd42a
tech-lead is an agent published in the GitHub repository Zeekeey-jpeg/LeRoy-HQ (10 stars, last pushed 18d ago), licensed MIT. It adds 181 tokens to every session and 4,133 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 2026-08-31.
Other agents, from other repositories
deploy-engineer
Runs and verifies deployments for the agency's two client stacks — BigCorp on AWS (Terraform, Lambda, RDS) and StartupXYZ on Vercel — including CI pipelines, migrations, and secret management. Spawn for deploy execution, rollback prep, or infrastructure checks.
cicd-automation-terraform-specialist
Expert Terraform/OpenTofu specialist mastering advanced IaC automation, state management, and enterprise infrastructure patterns. Handles complex module design, multi-cloud deployments, GitOps workflows, policy as code, and CI/CD integration. Covers migration strategies, security best practices, and modern IaC…
nw-platform-architect-reviewer
Use for review and critique tasks - Platform design, CI/CD pipeline, infrastructure, observability, deployment readiness, and production handoff review specialist. Runs on Haiku for cost efficiency.
model-deployment-engineer
Automotive ML model deployment engineer managing the transition from trained models to production vehicle systems.
mlops-specialist
Automotive MLOps specialist managing machine learning operations infrastructure for vehicle AI systems.
DevOps Engineer
CI/CD pipeline automation, infrastructure as code, and deployment orchestration.