I work with an engineering team using Claude Code, Codex, and OpenCode daily. Early on, we created a custom fork of spec-kit to set up our team directives repository and distribute custom agent workflows.

While that fork got us started, maintaining a custom fork of a CLI just to ship prompt workflows created constant merge debt and maintenance headaches. Every session, agents would still drift or forget our architecture decisions, and prompt shortcuts alone couldn't enforce team-wide standards across different developer tools.

To eliminate the fork entirely, we decoupled our workflow skills into adlc-team-skills, built on the open Agent Skills standard (SKILL.md). You install them into any repo with npx skills add tikalk/adlc-team-skills.

The setup works across a few core layers:

On session start, team-boot auto-loads your team constitution from Git and dynamically fetches only the rules, PDRs, and ADRs relevant to the active task — zero prompt-wall bloat.

For product and architecture strategy, product decisions are captured as Product Decision Records (PDRs) and compiled into PRD.md, while architectural decisions use Rozanski and Woods viewpoints composed into AD.md.

For execution, mission-brief acts as an autonomous pipeline runner that derives a formal contract (Goal, Constraints, Non-Goals, Success Criteria) and walks a specify-plan-implement-converge loop. When an agent fails, you edit the spec, not just the code.

In v0.15.0, mission-brief auto-discovers installed skills at runtime. Whether you have spec-kit, OpenSpec, Matt Pocock's skills, Addy Osmani's checklists, or custom skills installed side-by-side, the LLM dynamically decides which skill fits each pipeline step — letting us run upstream spec-kit directly with zero custom fork code.

What doesn't work well yet: our evals suite holdout-split validation is still manual. The architecture skills work, but multi-view DAG orchestration can be slow on very large codebases.

Repos: - Skills: https://github.com/tikalk/adlc-team-skills - Methodology: https://github.com/tikalk/agentic-sdlc-12-factors - CLI: https://github.com/tikalk/adlc-skills-cli

I'm curious — for those of you managing AI coding agents across engineering teams, how are you balancing team standards with the maintenance overhead of custom agent tooling?

user:	kanfilior
created:	August 4, 2026
karma:	32