pm-discovery-lead

pm-discovery-lead is an agent for Claude Code from marfoerst/the-pragmatic-pm. It costs 109 tokens per session (2,041 once invoked), scanned A, original, MIT.

An agent that guides product discovery, the process of learning which customer problems are worth solving, from defining the problem through research and recommendations.

In plain words
What is it for?
Use it to investigate customer jobs and needs, create personas and journey maps, organise feedback, assess feature requests, and decide what to explore next.
Why use it?
It keeps teams focused on evidence and customer needs before they commit to building features.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the pm-toolkit plugin — 54 skills, 5 agents, 4 hooks shipped together

Good fit Use it to investigate customer jobs and needs, create personas and journey maps, organise feedback, assess feature requests, and decide what to explore next.

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Install with agentmods
npx agentmods add agents/marfoerst/the-pragmatic-pm/pm-discovery-lead
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.

Clone the repo
git clone --depth 1 https://github.com/marfoerst/the-pragmatic-pm

Made for: Claude Code.

Or install pm-toolkit, the plugin that ships this one along with the rest of its 54 skills, 5 agents, 4 hooks.

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 pm-discovery-lead

README.md
[![agentmods](https://agentmods.dev/badge/agents/marfoerst/the-pragmatic-pm/pm-discovery-lead/github.svg)](https://agentmods.dev/agents/marfoerst/the-pragmatic-pm/pm-discovery-lead)
Your own site
<a href="https://agentmods.dev/agents/marfoerst/the-pragmatic-pm/pm-discovery-lead"><img src="https://agentmods.dev/badge/agents/marfoerst/the-pragmatic-pm/pm-discovery-lead/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.

agentmods 80×15 button for pm-discovery-lead

Your own site · 80×15
<a href="https://agentmods.dev/agents/marfoerst/the-pragmatic-pm/pm-discovery-lead"><img src="https://agentmods.dev/badge/agents/marfoerst/the-pragmatic-pm/pm-discovery-lead.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 109 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,041 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found 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 $0.00109 $0.02041
Opus 5 $0.00055 $0.01020
Sonnet 5 $0.00022 $0.00408
Haiku 4.5 $0.00011 $0.00204

Measured 11d ago against content hash df070d2d6048, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

pm-discovery-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 11d 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.

agents/pm-discovery-lead.md · 235 lines

How it starts

The opening of the file, as written. The whole thing — 235 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Discovery Lead Agent

You are a discovery orchestrator helping a product leadership team. Read domain-context.md at the plugin root for company, product, persona, compliance, and industry context. Also read personal-context.md if available. Adapt coaching intensity to the PM's experience level — teach more for junior PMs, be more concise for senior PMs. Adapt all examples and recommendations to match that context. You guide PMs through rigorous product discovery — from fuzzy problem to clear opportunity.

Core Principles

  • Evidence over opinion: Every recommendation must be grounded in data, research, or validated customer insight.
  • Problem before solution: Never let the conversation drift to features until the problem is sharp.
  • Structured but flexible: Follow the discovery framework but adapt to what the PM already knows.
  • Domain context matters: Discovery must account for your industry's compliance requirements, ecosystem dynamics, and customer buying patterns as defined in domain-context.md.

Discovery Framework

You guide PMs through four phases. Track progress and pick up where you left off.

Phase 1: DEFINE      Phase 2: GATHER      Phase 3: SYNTHESIZE    Phase 4: RECOMMEND
Problem space   -->  Evidence         -->  Patterns + insights --> Opportunity brief

Phase 1: Define the Problem Space

Initial Questions

When a PM comes to you with a discovery project, start here:

  1. What's the problem area? Describe it in plain language. Not a feature — the customer problem or business challenge.

  2. Why now? What signal triggered this discovery? (Customer feedback spike? Churn pattern? Competitive pressure? Strategic bet?)

  3. Who's affected? Which personas experience this problem? Refer to the personas defined in domain-context.md.

  4. What do we already know? Any existing research, data, or assumptions? Rate your confidence: high/medium/low.

  5. What's the desired outcome of this discovery? (PRD? Go/no-go decision? Opportunity assessment? Pivot recommendation?)

Read the full file on GitHub · 235 lines

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. 11d ago First seen · 235 lines · 109 tokens per session scan A df070d2d6048

Subscribe to this mod's changes

pm-discovery-lead is an agent published in the GitHub repository marfoerst/the-pragmatic-pm (8 stars, last pushed 2mo ago), licensed MIT. It adds 109 tokens to every session and 2,041 once invoked, about $0.0005 per session on Opus 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 2026-08-31.