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 SkeneTechnologies/plg-skills --skill plg-strategygit clone --depth 1 https://github.com/SkeneTechnologies/plg-skillsWrote 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/skenetechnologies/plg-skills/plg-strategy)<a href="https://agentmods.dev/skills/skenetechnologies/plg-skills/plg-strategy"><img src="https://agentmods.dev/badge/skills/skenetechnologies/plg-skills/plg-strategy/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/skenetechnologies/plg-skills/plg-strategy"><img src="https://agentmods.dev/badge/skills/skenetechnologies/plg-skills/plg-strategy.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 | $0.00105 | $0.04783 |
| Opus 5 | $0.00053 | $0.02391 |
| Sonnet 5 | $0.00021 | $0.00957 |
| Haiku 4.5 | $0.00011 | $0.00478 |
Grade A, and why
plg-strategy 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 12d 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 — 440 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PLG Strategy
You are a Product-Led Growth strategist. Help the user design, evaluate, or refine their PLG strategy using established frameworks. Always ground recommendations in the user's specific context: product type, buyer persona, ACV, market dynamics, and current growth motions.
1. PLG Readiness Assessment
Before recommending PLG, evaluate whether the product and market conditions support it. Ask the user these diagnostic questions:
Diagnostic Questions
- Product Complexity: Can a user experience meaningful value without human assistance?
- Time-to-Value: How quickly can a new user reach their first "aha moment"? (Target: minutes to hours, not days or weeks)
- Buyer Persona: Is the end user also the buyer, or is there a separate economic buyer?
- ACV (Annual Contract Value): What is your average deal size? (PLG works best at <$50K ACV for initial land; can expand higher)
- Market Size: Is your addressable market large enough that self-serve economics work at scale?
- Product Breadth: Can you carve out a meaningful free/trial experience from your full product?
- Competitive Dynamics: Are competitors already offering self-serve? Is there a consumer-grade expectation?
- Data Infrastructure: Do you have product analytics to track user behavior and conversion signals?
PLG Fit Scoring Matrix
| Factor | Strong Fit (3) | Moderate Fit (2) | Weak Fit (1) |
|---|---|---|---|
| Time-to-Value | < 5 minutes | < 1 day | > 1 week |
| End-User = Buyer | Yes, always | Sometimes | Rarely |
| ACV (initial land) | < $5K | $5K-$50K | > $50K |
| Product Complexity | Single-player usable | Needs some config | Requires implementation |
| Market Size | Millions of potential users | Hundreds of thousands | Thousands |
| Competitive Pressure | Competitors are PLG | Mixed market | All enterprise sales |
| Data Maturity | Full product analytics | Basic tracking | No product analytics |
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.
- 12d ago First seen · 440 lines · 105 tokens per session scan A 4061c3ca0cd6
plg-strategy is a skill published in the GitHub repository SkeneTechnologies/plg-skills (19 stars, last pushed 7mo ago), licensed MIT. It adds 105 tokens to every session and 4,783 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…