specag 0.1.0

Run an AI engineering team with full cost control and traceability.

SpecAg

Run an AI-powered engineering team with full cost control and traceability.

SpecAg is an open-source, opinionated framework for running real software projects with AI agents doing the development work — using proper Agile ceremonies, spec-driven development, and hard budget guardrails. Built for solo founders and small teams who want AI leverage without AI chaos.

pip install specag
specag init

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What SpecAg Does

Most AI coding tools solve the typing problem. SpecAg solves the engineering process problem.

Without SpecAg	With SpecAg
AI burns $200 overnight on a feature you didn't ask for	Hard daily/weekly token caps with automatic pause
No spec, no tests, no review	Every line of code traces back to an approved spec
"What did the AI do while I was at work?"	Full audit trail: spec + prompt + output + cost
Blocked on a human decision? AI keeps burning tokens.	Cascading 1/3/7 day SLA — T+7 = hard pause, zero spend
One-size-fits-all process	Stakes-based tiers: Starter → Personal → Medium → Enterprise

The Team

SpecAg gives you a 4-role team. 1 human, 3 AI agents.

Role	Who	What they do
Advisor	You (human)	Vision, architecture, QA, final say. ~10 hrs/week.
Lead Dev	AI agent	Architecture, complex features, PR reviews
Associate	AI agent	Smaller features, tests, infra scripts
PO Agent	AI agent	Backlog, ceremonies, daily reports, process glue

All coordination happens over Slack. No meetings. No Jira.

Quick Start

# Install
pip install specag

# Initialize a new project (interactive tier picker)
specag init

# Prepare next sprint (Saturday)
specag sprint prepare

# Kick off sprint (Sunday)
specag sprint kickoff

# Check cost and token usage
specag stats

See Quick Start Guide for the full 10-minute walkthrough.

Stakes-Based Tiers

SpecAg tiers projects by stakes, not user count. A HIPAA app with 20 users needs more rigor than a meme app with 10M users.

Tier	When to use	Ceremonies	Spec required	Cost enforcement
T1 Starter	Learning, experiments, tutorials	Optional	Optional	Always on
T2 Personal	Real side project, solo owner	Recommended	Recommended	Always on
T3 Medium	Paying users, real revenue	Required	Required	Always on

Cost enforcement is strict at every tier. That's the point. Even a hello-world project gets token caps, because the point is to prevent runaway spend.

Set your tier in specag.config.yaml:

project:
  name: "my-project"
  tier: personal    # starter | personal | medium

See Tier Matrix for the full strictness breakdown.

Cost Enforcement (The Moat)

Every AI coding tool watches your spend. SpecAg stops it.

Pre-Call Hook Chain

Before any LLM API call, a chain of hooks runs. First non-ALLOW decision wins:

Hook	What it does
DailyCapHook	Reject if daily token cap reached
WeeklyCapHook	Reject if weekly cap reached
WorkWindowHook	Reject if outside work hours
PausedRegistryHook	Reject if epic is hard-paused (blocker T+7)
PCModeHook	Downgrade to cheaper model during discovery phases
BudgetGuardHook	Reject if estimated cost exceeds remaining budget

Hooks are pluggable. Swap, add, or remove by editing hooks.yaml — no code changes.

Cascading Blocker SLA

When work is blocked on a human decision:

Day	What happens
T+1	PO Agent nudges in Slack
T+3	Priority bumps. Downstream impact broadcast.
T+7	HARD PAUSE. Token tracker rejects ALL LLM calls on blocked paths. Zero spend until human responds.

Most tools observe. SpecAg enforces.

Spec-Driven Development

No code without a spec. No commit without a spec reference. No PR without a spec update.

Spec (business + technical + acceptance criteria)
  → AI implements against the spec
  → Commit references the spec (git hook enforces)
  → PR updates the spec changelog (CI enforces)
  → Demo proves the spec works
  → Human accepts

AI agents have no memory between conversations. The spec IS their memory.

Honest Comparison

SpecAg is inspired by and builds on ideas from BMAD-METHOD, GitHub Spec Kit, and MetaGPT. Here's what's different:

Feature	BMAD	Spec Kit	MetaGPT	SpecAg
Agent roles (PM, Dev, etc.)	Yes	No	Yes	Yes
Spec-driven development	Yes	Yes	Partial	Yes
Token cost enforcement (hard stop)	No	No	No	Yes
Cascading blocker SLA (T+7 hard pause)	No	No	No	Yes
Stakes-based tier system	No	No	No	Yes
Sustainable pace ceiling	No	No	No	Yes
Pluggable hook architecture	No	Partial	No	Yes
Solo-founder-with-day-job persona	No	No	No	Yes

We don't pretend to be unique in every dimension. We're unique where it matters: cost control + human-compatible pacing.

Documentation

Doc	What it covers
Quick Start	Zero to first spec in 10 minutes
Study Guide	Learning path for understanding the full framework
Project Bible	The complete methodology reference (~2000 lines)
Tier Matrix	What's strict/lenient at each tier
Architecture	How the pieces fit together
Roadmap	What's built, what's next

Who This Is For

• Solo founders with a day job who want AI leverage without full-time babysitting
• Small teams (2-5) adopting AI agents for real production work
• Anyone burned by "vibe coding" who wants the discipline layer back

Who This Is NOT For

• Teams that want fully autonomous AI (try Devin)
• Teams that just need code completion (try Cursor or Copilot)
• Enterprise teams that need Jira/Linear integration today (that's on the roadmap, not shipped)

Estimated Cost

Running a full SpecAg team (1 human + 3 AI agents) for a year:

Item	Annual cost
VPS (4 vCPU / 16GB)	~$144
AI APIs (primary + fallback)	~$280
Total	~$424/year ($35/month)

The framework is designed to stay under $500/year total. Cost enforcement makes this a ceiling, not a guess.

Contributing

See CONTRIBUTING.md. We welcome:

• Bug reports and feature requests
• Documentation improvements
• New hook implementations
• Tier profile contributions
• Example projects

License

MIT. Use it, fork it, sell products built with it. See LICENSE.

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Built by Dedeepya Sai Gondi in Dallas, TX. Dogfooded on real projects.