claude

pm-agentnative

Build for the agent era: products are getting non-human users. Spec an MCP server properly, audit whether agents can actually use your product, migrate seat pricing before agents break it, design human-in-the-loop approval surfaces, and get voice agents right.

1,544 on GitHubby Mohit Aggarwalv1.0.0MITupdated yesterdayproductivity
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Plugin pm-agentnative from marketplace pm-claude-skills in mohitagw15856/pm-claude-skills. Commands read from the repo's manifest — yesterday.

What it installs

Skills (9)

  • agent-era-pricing

    Redesign seat-based pricing for the agent era — when one human runs ten agents, per-seat models collapse. Use when agents are eroding seat counts, when asked to migrate to usage- or outcome-based pricing, to price an agent/API tier, or to defend revenue as customers automate their own usage. Produce

  • agent-negotiation-brief

    Brief an AI agent that will negotiate for you with another party's agent or a person (a refund, a price, a meeting time, a contract term): your goal, your opening, your limits, your walk-away point, what it must never reveal, and when it must come back to you. Use when asked to let my agent negotiat

  • agent-project-file

    Set up the project file an AI agent keeps for work that runs over days or weeks: the goal, the definition of done, milestones, the current state, decisions made, open questions, and the exact point to resume from after an interruption. Use when asked to plan a long-running agent task, make my agent

  • agent-readiness-audit

    Audit whether AI agents can actually use your product — docs, APIs, onboarding, errors, and discoverability, evaluated from a non-human user's perspective. Use when asked if a product is agent-ready, to audit a site or API for AI usability, to prepare for agentic traffic, or when agents keep failing

  • agent-spending-mandate

    Write a spending mandate that lets an AI agent buy things for you within strict limits: what it may buy, from whom, up to how much per purchase and in total, until when, and what needs your yes. Use when asked to let my agent make purchases, set a budget for an AI shopping agent, allow agentic check

  • computer-use-runbook

    Write the step-by-step runbook a computer-use or browser agent follows to finish a real online task, such as cancelling a subscription or changing an energy supplier: what to look for on screen, one action per step, how to know it worked, and where to stop for a human. Use when asked to write instru

  • human-in-the-loop-design

    Design the human approval surface for an agent system — which actions gate, how approvals batch without becoming rubber stamps, and what the audit trail must hold. Use when asked to add human oversight to an agent, design approval workflows for AI actions, decide what an agent may do autonomously, o

  • mcp-server-spec

    Design an MCP server for a product — the tool surface, auth model, and safety boundaries that make it genuinely usable by AI agents. Use when asked to spec an MCP server, expose a product to agents, design tools for Claude or other MCP clients, or review why an existing MCP server performs badly. Pr

  • voice-agent-design

    Design a voice AI agent for phone or in-app conversations — call flows, interruption handling, escalation to humans, and the metrics that catch a bad voice experience. Use when asked to design a voice agent, automate a phone line, spec an IVR replacement, or review why callers hate an existing voice

View source on GitHub mohitagw15856.github.io

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