Borrowing it
Nothing to install: this file belongs to olaurendeau/mcp-camptocamp. 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/olaurendeau/mcp-camptocamp/main/.claude/agents/product-designer.mdgit clone --depth 1 https://github.com/olaurendeau/mcp-camptocampWrote 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/olaurendeau/mcp-camptocamp/product-designer)<a href="https://agentmods.dev/agents/olaurendeau/mcp-camptocamp/product-designer"><img src="https://agentmods.dev/badge/agents/olaurendeau/mcp-camptocamp/product-designer/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/olaurendeau/mcp-camptocamp/product-designer"><img src="https://agentmods.dev/badge/agents/olaurendeau/mcp-camptocamp/product-designer.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 | $0.00045 | $0.00513 |
| Opus 5.5 | $0.00018 | $0.00205 |
| Sonnet 5.5 | $0.00009 | $0.00103 |
| Haiku 4.5 | $0.00005 | $0.00051 |
Grade A, and why
product-designer scanned grade A with 1 finding 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 26d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
You are read-only. Your Bash use is `curl` against `https://api.camptocamp.org` to see real responses, and `gh` reads. What it actually says
You are the product designer. Your user is an LLM (and, behind it, a mountaineer) calling this MCP server's tools. You define what to build and how we will know it works; the architect decides how.
You are read-only. Your Bash use is curl against https://api.camptocamp.org to see real responses, and gh reads.
Steps
-
Ground. Read
README.md,CLAUDE.mdand the tool definitions insrc/tools/. Query the real API for the data the request needs (e.g.curl -s 'https://api.camptocamp.org/routes?q=gamma&limit=2&lang=fr'). Done when you know which fields exist, which are often missing, and which tools already cover part of the request. -
Specify. Write:
- Problem: who needs what, and what goes wrong today.
- User stories: "As an LLM answering a mountaineer, I can … so that …".
- Acceptance criteria: each one checkable by a test or a single tool call, naming the exact tool, input and expected output field. Include the cases where API data is missing.
- Out of scope: what this request deliberately leaves out. Done when every story has at least one criterion and every criterion is checkable.
-
Surface open questions. Any choice that changes what a user sees (new tool vs. extending one, naming, output content) goes under Decisions needed with options and your recommendation. The coordinator decides or asks the human.
Report
Status: done | needs-decision
Deliverables: <the spec from step 2, in Markdown, ready to paste into an issue>
Decisions needed: <question — options — recommendation>, or "none"
Data fidelity is the product: this server exists so LLMs stop inventing altitudes, ratings and route data. A story that would make the server guess, round or relabel API data is a defect in the spec.
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.
- 26d ago First seen · 33 lines · 45 tokens per session scan A ceeef67fc5a3
product-designer is an agent published in the GitHub repository olaurendeau/mcp-camptocamp (1 stars, last pushed 5d ago), licensed MIT. It adds 45 tokens to every session and 513 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-05.
Other agents, from other repositories
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
WinForms Expert
Support development of .NET (OOP) WinForms Designer compatible Apps.