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.
git clone --depth 1 https://github.com/pmprompt/claude-plugin-product-managementWrote 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/commands/pmprompt/claude-plugin-product-management/discover)<a href="https://agentmods.dev/commands/pmprompt/claude-plugin-product-management/discover"><img src="https://agentmods.dev/badge/commands/pmprompt/claude-plugin-product-management/discover/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/commands/pmprompt/claude-plugin-product-management/discover"><img src="https://agentmods.dev/badge/commands/pmprompt/claude-plugin-product-management/discover.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 | $0.00009 | $0.00348 |
| Opus 5.5 | $0.00004 | $0.00139 |
| Sonnet 5.5 | $0.00002 | $0.00070 |
| Haiku 4.5 | $0.00001 | $0.00035 |
Grade A, and why
discover 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 2d 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.
What it actually says
/discover — Product Discovery Workflow
Structured product discovery from problem to validated experiments.
What It Does
Chains together Opportunity Solution Trees, assumption testing, and experiment design to take you from a product idea to validated next steps.
When to Use
- New product or feature idea that needs structured discovery
- Customer problem that could be solved multiple ways
- Need to validate assumptions before building
- Want to map opportunities to outcomes
Workflow
-
Build an Opportunity Solution Tree — Map desired outcome → customer opportunities → solution ideas → experiments (uses
opportunity-solution-treesskill) -
Identify Assumptions — Surface risky assumptions across Value, Usability, Viability, Feasibility (uses
trustworthy-experimentsskill) -
Prioritize Assumptions — Rank by impact × risk (uses
feature-prioritization-assistantskill) -
Design Experiments — Create fast, cheap tests for top assumptions (uses
trustworthy-experimentsskill)
Usage
/discover [product idea or problem statement]
Example:
/discover AI-powered meeting summarizer for remote teams
Output
- Complete Opportunity Solution Tree
- Prioritized list of risky assumptions
- 3-5 experiment designs with success criteria
- Suggested next steps
Next Steps After /discover
/strategy— Define positioning and strategic narrative/write-prd— Document the validated solution- Run the top experiments and return with learnings
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.
- 2d ago Changed · +5 lines · +9 tokens per session 3f099e4bb5d4
- 1mo ago First seen · 49 lines · 0 tokens per session scan A d1bcfdb0a6ea
discover is a command published in the GitHub repository pmprompt/claude-plugin-product-management (53 stars, last pushed 2d ago), licensed MIT. It adds 9 tokens to every session and 348 once invoked, about $0.0000 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.
Other commands, from other repositories
workflow-foundation-sprint
Run the Foundation Sprint workflow (2-day strategic-alignment arc producing a Founding Hypothesis).
chain
Run an ad-hoc ordered chain of pm-skills with shared context (ephemeral; routes to the pm-workflow-orchestrator).
workflow-post-launch-learning
Run the Post-Launch Learning workflow (instrumentation -> dashboard -> results -> retro -> lessons).
workflow-product-strategy
Run the Product Strategy workflow (competitive analysis -> stakeholders -> opportunities -> solution -> ADR).
workflow-sprint-planning
Run the Sprint Planning workflow (refinement -> stories -> edge cases).
plan-okrs
Brainstorm team-level OKRs aligned with company objectives — qualitative objectives with measurable key results.