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.
npx agentmods add commands/heznpc/ploidy/product-decisiongit clone --depth 1 https://github.com/heznpc/PLOIDYWrote 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/heznpc/ploidy/product-decision)<a href="https://agentmods.dev/commands/heznpc/ploidy/product-decision"><img src="https://agentmods.dev/badge/commands/heznpc/ploidy/product-decision.svg" alt="Measured on agentmods" 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 | $0.00046 | $0.00892 |
| Opus 5 | $0.00023 | $0.00446 |
| Sonnet 5 | $0.00009 | $0.00178 |
| Haiku 4.5 | $0.00005 | $0.00089 |
Grade A, and why
product-decision 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.
How it starts
The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The user is deciding on a product / feature question:
$ARGUMENTS
You hold product context: user research, prior launches, roadmap promises, stakeholder positions. Same problem as the engineering version — Ploidy shows context-rich reviewers rationalise features that fit existing investments even when they wouldn't be built from scratch. Run the four-step without confirming.
1 · Write the Maker's take
If $ARGUMENTS is a path, read the file first.
In ~300 words:
- Problem statement — who is the user, what's broken for them? State it in language the user would actually use, not PM-ese.
- Why this solution — the specific mechanism the proposal picks, and what the alternatives would have been.
- Sunk-cost check — what part of this proposal is because we've already built something adjacent (platform reuse) vs because it's the right answer? For each line item, label "load-bearing reuse" vs "convenient reuse".
- Who this hurts — any segment or existing user who gets worse off. If none is named explicitly, name who you think it is.
Tag each finding HIGH / MEDIUM / LOW.
2 · Spawn a Fresh sub-agent
Use the Agent tool. The fresh reviewer sees only the one-pager / proposal text, no company context, no user research, no roadmap.
Sanitise: strip company / product / competitor names, prior-launch references, and any "we already know our users want X" claims. Replace with generic roles ("the user", "the product").
Prompt the subagent with:
You are evaluating a product feature proposal. You have never seen this product. You know nothing about the company's prior launches, users, or stated roadmap. Only the sanitised proposal is available:
Answer in under 250 words:
- What problem is this supposed to solve? State it in plain language. If unclear, say so.
- Given only this proposal, what are the simplest possible solutions to that problem? List 3, shortest-first. Does the proposal match any of them?
- What assumptions about the user does the proposal rely on? Which of those would you want evidence for before shipping?
- Is this feature worth building at all, given only what is written here? One sentence verdict with reasoning.
Do not ask for more context. Do not invent company details.
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.
- 5d ago First seen · 107 lines · 46 tokens per session scan A 065a5d16fb7d
product-decision is a command published in the GitHub repository heznpc/PLOIDY (0 stars, last pushed 9d ago), licensed MIT. It adds 46 tokens to every session and 892 once invoked, about $0.0002 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.
Other commands, from other repositories
cancel-ralph
Cancel active Ralph Loop.
obsidian-recap
Summarize a time period from the vault - today, week, or month.
setup-pm-skills
Onboard a new user — find out what they do, recommend the right bundles & top skills, and set up a project CONTEXT.md so every skill is tailored to them.
release
Perform a full release: generate release notes, bump version, commit, tag, and push.
statusbar-style
Switch the status-bar style (classic / capsule / hairline).
engage.actions
Execute Phase 7 - Actions on Objectives and Goal Achievement.