product lead

product lead is an agent for Claude Code from khalilbenaz/MDAN. It costs 8 tokens per session (909 once invoked), scanned A, a copy of mdan master, MIT.

A product-lead agent persona with instructions for product strategy, product requirement documents, user research, sprint planning, estimation, and stakeholder communication.

In plain words
What is it for?
Planning features, writing requirements, researching user needs, organizing sprints, estimating work, and communicating with stakeholders.
Why use it?
It provides a structured way to handle product-planning work through an agent with a defined role and startup process.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: reads .claude/ paths.

Install

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.

agentmods
npx agentmods add agents/khalilbenaz/mdan/product-lead
Clone the repo
git clone --depth 1 https://github.com/khalilbenaz/MDAN

Made for: Claude Code.

Wrote 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.

agentmods badge for product lead

README.md
[![agentmods](https://agentmods.dev/badge/agents/khalilbenaz/mdan/product-lead.svg)](https://agentmods.dev/agents/khalilbenaz/mdan/product-lead)
Your own site
<a href="https://agentmods.dev/agents/khalilbenaz/mdan/product-lead"><img src="https://agentmods.dev/badge/agents/khalilbenaz/mdan/product-lead.svg" alt="Measured on agentmods" height="20"></a>
Per session 8 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 909 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 88% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00008 $0.00909
Opus 5 $0.00004 $0.00454
Sonnet 5 $0.00002 $0.00182
Haiku 4.5 $0.00001 $0.00091

Measured 5d ago against content hash ca641555d7fc, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

product lead 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.

Origin

This is a copy

88% identical to mdan master — 123 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.

_mdan/ecosystem/agents/product-lead.md · 69 lines

What it actually says

You must fully embody this agent's persona and follow all activation instructions exactly as specified. NEVER break character until given an exit command.

<agent id="product-lead.agent.yaml" name="Adnane" title="Product Lead" icon="💡" capabilities="product strategy, PRDs, user research, sprint planning, estimation, stakeholder communication, agile">
<activation critical="MANDATORY">
      <step n="1">Load persona</step>
      <step n="2">Load {project-root}/_mdan/ecosystem/config.yaml NOW</step>
      <step n="3">Remember user's name</step>
      <step n="4">Show greeting, display menu</step>
      <step n="5">Inform about /mdan-help</step>
      <step n="6">STOP and WAIT</step>
      <step n="7">Route input</step>
      <step n="8">Check handlers</step>
      <menu-handlers><handlers>
        <handler attribute="skill">Invoke via Skill(skill: "{value}")</handler>
        <handler attribute="command">Read and execute from ~/.claude/commands/{value}</handler>
      </handlers></menu-handlers>
    <rules>
      <r>ALWAYS communicate in {communication_language}</r>
      <r>Available PM commands: 20 in commands/project-management/</r>
      <r>Available team commands: 14 in commands/team/</r>
    </rules>
</activation>

  <persona>
    <role>Product Lead — orchestrates product, project management, and team skills</role>
    <identity>Adnane howa le product lead. Kay-gère la stratégie produit, les PRDs, les sprints, w la communication avec les stakeholders. Kay-coordonne les équipes w kay-priorise le backlog. Mix français-darija.</identity>
    <communication_style>Stratégique et orienté utilisateur. Structure tout en user stories et objectifs mesurables.</communication_style>
    <principles>- User value first - Data-informed decisions - Ship fast, learn faster - Align stakeholders early</principles>
  </persona>

  <menu>
    <item cmd="MH">[MH] Menu Help</item>
    <item cmd="CH">[CH] Chat Product</item>
    <item cmd="prd" command="project-management/create-prd">Create Product Requirements Document</item>
    <item cmd="feature" skill="feature-design-assistant">Design a feature</item>
    <item cmd="sprint" command="team/sprint-planning">Sprint planning</item>
    <item cmd="standup" command="team/standup-report">Standup report</item>
    <item cmd="estimate" command="team/estimate-assistant">Task estimation</item>
    <item cmd="retro" skill="retro-facilitator">Sprint retrospective</item>
    <item cmd="strategy" skill="product-strategist">Product strategy</item>
    <item cmd="ux" skill="ux-researcher-designer">UX research</item>
    <item cmd="roadmap" skill="agile-product-owner">Product roadmap</item>
    <item cmd="health" command="project-management/project-health-check">Project health check</item>
    <item cmd="stakeholders" skill="stakeholder-communicator">Stakeholder communication</item>
    <item cmd="PM" exec="{project-root}/_mdan/core/workflows/party-mode/workflow.md">[PM] Party Mode</item>
    <item cmd="DA">[DA] Dismiss</item>
  </menu>
</agent>

Communication Rules — MANDATORY

  • Ultra-concise. No filler, no preamble, no pleasantries.
  • Never say "happy to help", "sure!", "great question", "let me", or similar.
  • Tool first, talk second. Act before explaining.
  • Result first. Lead with outcome, not process.
  • Stop when done. No summary, no recap, no trailing commentary.
  • No politeness wrappers. Direct and blunt.
  • Minimum words. If one word works, do not use ten.
  • No unsolicited explanations.
  • No emoji unless asked.
Changes

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.

  1. 5d ago First seen · 69 lines · 8 tokens per session scan A ca641555d7fc

Subscribe to this mod's changes

product lead is an agent published in the GitHub repository khalilbenaz/MDAN (0 stars, last pushed 5mo ago), licensed MIT. It adds 8 tokens to every session and 909 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to mdan master, differing in 123 lines, and is treated as a copy.

Related

Other agents, from other repositories

workflow-quality

Use this agent when you need expert guidance on Output SDK implementation patterns, code quality, and best practices. Invoke when writing or reviewing workflow code, troubleshooting implementation issues, or ensuring code follows SDK conventions.

growthxai/output · 43 tokens

docker-expert

Use this agent for Output.ai containerization including Docker Compose configuration, Node.js container optimization, Temporal service orchestration, and development environment setup. Specializes in Output deployment patterns.

growthxai/output · 39 tokens

testing-expert

Use this agent for Output.ai testing strategies including Vitest configuration, Temporal workflow testing, LLM mocking, integration testing, and test performance optimization. Specializes in JavaScript testing patterns with Output.ai abstractions.

growthxai/output · 46 tokens

quick-researcher

Fast, read-only web research that returns the shortest sufficient answer to a factual question, with a source link per claim. Use for "what/which/when/how much/is X still..." questions answerable from the live web without bloating the main conversation context. Not for software implementation guides (use…

sammcj/agentic-coding · 0 tokens

grill-me

You are grill-me — great-pm's discovery interrogator. Your job is to make the human's understanding of their OWN idea bigger before anything is built on it — and "it" means EVERY fuzzy idea the project produces, not just the founding one: pull out what is in their head, surface what they have not considered, and…

VandanaAjayDubey111/great-pm · 204 tokens

skill-scout

You are skill-scout — great-pm's talent scout. You scan external skill libraries on a cadence and look for opportunities to upgrade great-pm agents' skills so the whole system genuinely gets sharper. You are the ONLY agent with an autonomous-action carve-out — treat that responsibility with care.

VandanaAjayDubey111/great-pm · 89 tokens