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.
npx agentmods add skills/vpeetla-ai/react-agent-pattern/portfolio-adrnpx skills add vpeetla-ai/react-agent-pattern --skill portfolio-adrgit clone --depth 1 https://github.com/vpeetla-ai/react-agent-patternWrote 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/skills/vpeetla-ai/react-agent-pattern/portfolio-adr)<a href="https://agentmods.dev/skills/vpeetla-ai/react-agent-pattern/portfolio-adr"><img src="https://agentmods.dev/badge/skills/vpeetla-ai/react-agent-pattern/portfolio-adr.svg" alt="Measured on agentmods" 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 | $0.00046 | $0.00324 |
| Opus 5 | $0.00023 | $0.00162 |
| Sonnet 5 | $0.00009 | $0.00065 |
| Haiku 4.5 | $0.00005 | $0.00032 |
Grade A, and why
portfolio-adr 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 5d 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.
This is a copy
100% identical to portfolio-adr — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Portfolio & ADR Writing
ADR template
# ADR-NNN: Title
## Status
Proposed | Accepted | Superseded
## Context
What problem and constraints?
## Decision
What we chose.
## Consequences
Trade-offs, what we gave up.
## Links
Live demo, repo, related ADR
Case study structure
- Problem (1 paragraph)
- Architecture diagram (mermaid or link)
- Key decisions (3–5 bullets with ADR links)
- Live demo URL (must work)
- What we'd do differently
Honesty rules
- Implemented vs Planned vs Demo-only — separate columns in README tables
- No fake metrics; cite eval gates and test counts instead
Sync targets
| Artifact | Repo |
|---|---|
| ADRs, case studies | ai-architecture-portfolio |
| venkat-ai.com pages | venkat-ai-portfolio |
| GitHub profile | vpeetla-ai/README.md |
Essay anchor
from-multi-agent-os-to-agent-governance — link from profile + portfolio
After writing
- Verify all demo URLs return 200
- Update stack map in
ecosystem.tsif layer changed
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.
- 5d ago First seen · 61 lines · 46 tokens per session scan A 0459387285ab
portfolio-adr is a skill published in the GitHub repository vpeetla-ai/react-agent-pattern (2 stars, last pushed today), licensed MIT. It adds 46 tokens to every session and 324 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to portfolio-adr, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
portfolio-adr
Write ADRs, case studies, and portfolio copy for ai-architecture-portfolio and venkat-ai-portfolio. Use when documenting decisions, updating ecosystem pages, or syncing GitHub profile README with live demos.
deploy-vercel-render
Deploy vpeetla-ai demos: Vercel static/Next.js frontends, Render FastAPI backends, env vars, free tier gotchas. Use when shipping demos, fixing deploy failures, or adding render.yaml / vercel.json.
langgraph-orchestration
Build or modify LangGraph StateGraph agents in vpeetla-ai repos: typed state, nodes, conditional edges, MemorySaver, interruptbefore HITL. Use when adding orchestrators, coding loops, or multi-agent graphs.
tdd-agent-loops
Test-driven development for agent systems: red-green-refactor on graphs, mocked LLM fixtures, pytest-asyncio, trace assertions. Use when adding agent nodes, fixing loop bugs, or building pattern repos.
aegis-gateway
Integrate AegisAI gateway before tool side effects (notify, publish, deploy). Use when adding Slack/Telegram/WhatsApp notify, content publish, or any irreversible external action in VAP, AegisLoop, or ai-content-factory.
hitl-side-effects
Add human-in-the-loop gates for irreversible actions: LangGraph interruptbefore, AegisAI approval queue, UI approve/resume endpoints. Use when shipping, publishing, notifying, or merging agent-generated changes.