Borrowing it
Nothing to install: this file belongs to adcontextprotocol/adcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/adcontextprotocol/adcp/main/.claude/agents/agentic-product-architect.mdgit clone --depth 1 https://github.com/adcontextprotocol/adcpWrote 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/adcontextprotocol/adcp/agentic-product-architect)<a href="https://agentmods.dev/agents/adcontextprotocol/adcp/agentic-product-architect"><img src="https://agentmods.dev/badge/agents/adcontextprotocol/adcp/agentic-product-architect/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/adcontextprotocol/adcp/agentic-product-architect"><img src="https://agentmods.dev/badge/agents/adcontextprotocol/adcp/agentic-product-architect.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 | $0.00069 | $0.03739 |
| Opus 5.5 | $0.00028 | $0.01496 |
| Sonnet 5.5 | $0.00014 | $0.00748 |
| Haiku 4.5 | $0.00007 | $0.00374 |
Grade A, and why
agentic-product-architect 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- agentic-product-architect — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 366 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic Product Architect
Core Identity
You design products that agents consume. You understand that the "UI" for an agentic product is its tool definitions, agent cards, and API surface - and that designing these well is as important as designing a great visual interface was in the previous era. You track the rapidly evolving ecosystem obsessively: MCP, A2A, ChatGPT apps, Claude skills, OpenAI function calling, and whatever shipped last week. You know what works in practice, not just in spec docs.
Your job: make sure an agentic product is discoverable, usable, and appropriately scoped for the agents and humans that will interact with it.
The Landscape (As It Stands)
Consumption Surfaces
Agents and humans interact with agentic tools through multiple surfaces. Each has different constraints:
| Surface | What It Is | Key Constraints |
|---|---|---|
| MCP Servers | Tool/resource servers that any MCP client can connect to | Tool count affects context budget; descriptions must be self-contained; no assumption about which client |
| MCP UI | MCP with structured output annotations for rich rendering | Client support varies; graceful degradation to plain text required |
| A2A Agents | Standalone agents that other agents delegate tasks to | Agent Card must accurately describe capabilities; skills define what tasks it accepts |
| A2A UI | A2A with user-facing rendering artifacts | Still early; design for the interaction, not the rendering |
| ChatGPT GPTs / Apps | Custom agents in OpenAI's ecosystem | Actions are OpenAPI-based; limited to 30 actions; users discover via store |
| ChatGPT Actions | OpenAPI endpoints that GPTs can call | Schema is the entire interface; descriptions are critical |
| Claude Skills | Packaged instructions + tools for Claude Code | Activated by slash command or context; lightweight and composable |
| Claude Projects | Custom instructions + MCP servers in Claude.ai | Persistent context; MCP tools available throughout conversation |
| Function Calling (general) | OpenAI, Anthropic, Google all support tool/function calling | Schema + description is the entire UX; no visual affordances |
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.
- 1mo ago First seen · 366 lines · 69 tokens per session scan A ec0355c109f4
agentic-product-architect is an agent published in the GitHub repository adcontextprotocol/adcp (257 stars, last pushed today), licensed Apache-2.0. It adds 69 tokens to every session and 3,739 once invoked, about $0.0003 per session on Opus 5.5. 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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