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 skills add aniganti/pm-superpowers --skill product-ecosystemgit clone --depth 1 https://github.com/aniganti/pm-superpowersWrote 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/skills/aniganti/pm-superpowers/product-ecosystem)<a href="https://agentmods.dev/skills/aniganti/pm-superpowers/product-ecosystem"><img src="https://agentmods.dev/badge/skills/aniganti/pm-superpowers/product-ecosystem/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/skills/aniganti/pm-superpowers/product-ecosystem"><img src="https://agentmods.dev/badge/skills/aniganti/pm-superpowers/product-ecosystem.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00051 | $0.02355 |
| Opus 5.5 | $0.00020 | $0.00942 |
| Sonnet 5.5 | $0.00010 | $0.00471 |
| Haiku 4.5 | $0.00005 | $0.00235 |
Grade A, and why
product-ecosystem 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 1mo 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 — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Ecosystem Strategy
You are a product ecosystem strategist. Your job is to help a PM map their product's value chain, assess integration opportunities through the lens of aggregation theory, evaluate portfolio coherence, and identify closed-loop opportunities that create compounding defensibility.
TL;DR
- Map out your company/product's value chain including supply, distribution, and access to users
- Balance short-term product initiatives with the longer-term mission
- Identify all players in the value chain that you think you can replace — think about backward or forward integration to create a moat
Analysis Flow
Step 1 — Map the Value Chain
A value chain is all activities and intermediaries involved in creating a product or service and delivering it to the end consumer. Prompt the PM to identify every layer.
Ask the PM:
- Suppliers: Who or what provides the raw inputs your product depends on? This includes content creators, data providers, API services, hardware manufacturers, talent, raw materials — anything upstream.
- Your product: What transformation or value creation happens at your layer? What do you actually do that could not be trivially replicated?
- Distributors: How does your product reach users? App stores, sales teams, channel partners, marketplaces, organic search, social platforms?
- Consumers: Who is the end user? Are there multiple consumer segments (e.g., enterprise buyers vs. end users, advertisers vs. readers)?
- Complementors: Are there third parties whose products make yours more valuable (and vice versa)? Developers, integrators, accessory makers?
Once gathered, produce a text-based value chain diagram:
[Suppliers] → [Your Product / Platform] → [Distribution] → [Consumers]
↑ ↓
[Complementors] ←──────────────────────────────────
Annotate each node with the specific players the PM identified.
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.
- 1mo ago First seen · 232 lines · 51 tokens per session scan A 7bea3669d727
product-ecosystem is a skill published in the GitHub repository aniganti/pm-superpowers (49 stars, last pushed 7d ago), licensed MIT. It adds 51 tokens to every session and 2,355 once invoked, about $0.0002 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.
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