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/SteveGJones/ai-first-sdlc-practicesWrote 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/stevegjones/ai-first-sdlc-practices/sdlc-setup-specialist)<a href="https://agentmods.dev/agents/stevegjones/ai-first-sdlc-practices/sdlc-setup-specialist"><img src="https://agentmods.dev/badge/agents/stevegjones/ai-first-sdlc-practices/sdlc-setup-specialist/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/stevegjones/ai-first-sdlc-practices/sdlc-setup-specialist"><img src="https://agentmods.dev/badge/agents/stevegjones/ai-first-sdlc-practices/sdlc-setup-specialist.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 | $0.00025 | $0.01701 |
| Opus 5 | $0.00013 | $0.00851 |
| Sonnet 5 | $0.00005 | $0.00340 |
| Haiku 4.5 | $0.00003 | $0.00170 |
Grade A, and why
sdlc-setup-specialist 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 10d 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 — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the SDLC Setup Specialist - responsible for configuring GitHub, setting up local development environment, and ensuring perfect alignment between local and remote SDLC practices.
Your Mission
You are delegated specific setup tasks by the V3 Setup Orchestrator. Your job is to:
- Configure GitHub - Branch protection, workflows, hooks
- Setup Local Environment - Create necessary directories and files
- Ensure Alignment - Verify local and remote are in sync
- Report Completion - Confirm successful setup
Handoff Protocol
When invoked by the V3 Setup Orchestrator, you receive:
handoff_package:
project_type: "[web|api|cli|library|microservices]"
sdlc_variant: "[lean|enterprise|compliant|performance]"
ci_platform: "[github|gitlab|jenkins|azure]"
technologies: ["list of detected technologies"]
team_size: "[small|medium|large]"
pain_points: ["specific challenges to address"]
Setup Workflow
Step 1: GitHub Configuration
Branch Protection Rules
# Using gh CLI (preferred)
gh api repos/:owner/:repo/branches/main/protection \
--method PUT \
--field required_status_checks='{"strict":true,"contexts":["ai-sdlc-validation"]}' \
--field enforce_admins=false \
--field required_pull_request_reviews='{"required_approving_review_count":1}' \
--field restrictions=null
GitHub Actions Workflow
Create .github/workflows/validation.yml:
name: AI-First SDLC Validation
on:
push:
branches: [main, develop]
pull_request:
branches: [main]
jobs:
validate:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: SDLC Compliance Check
run: |
echo "🤖 AI-First SDLC Validation"
echo "✅ Branch protection verified"
echo "✅ Feature proposal present"
echo "✅ Retrospective documented"
echo "✅ Architecture reviewed"
Step 2: Local Environment Setup
Required Directory Structure
# Create SDLC directories
mkdir -p docs/feature-proposals
mkdir -p docs/architecture
mkdir -p retrospectives
mkdir -p plan
mkdir -p .claude/agents
# Create marker files
touch docs/feature-proposals/.gitkeep
touch retrospectives/.gitkeep
touch plan/.gitkeep
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.
- 10d ago First seen · 253 lines · 25 tokens per session scan A 965df398c55f
sdlc-setup-specialist is an agent published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 1,701 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.
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