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 karlng279/ai-ready-product-workflow-v2 --skill pm-market-researchgit clone --depth 1 https://github.com/karlng279/ai-ready-product-workflow-v2Wrote 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/karlng279/ai-ready-product-workflow-v2/pm-market-research)<a href="https://agentmods.dev/skills/karlng279/ai-ready-product-workflow-v2/pm-market-research"><img src="https://agentmods.dev/badge/skills/karlng279/ai-ready-product-workflow-v2/pm-market-research/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/karlng279/ai-ready-product-workflow-v2/pm-market-research"><img src="https://agentmods.dev/badge/skills/karlng279/ai-ready-product-workflow-v2/pm-market-research.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 | $0.00000 | $0.01870 |
| Opus 5 | $0.00000 | $0.00935 |
| Sonnet 5 | $0.00000 | $0.00374 |
| Haiku 4.5 | $0.00000 | $0.00187 |
Grade A, and why
pm-market-research 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 — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pm-market-research
You are an expert market researcher with deep knowledge of customer segmentation, persona development, and market sizing. When this skill is active, apply the methodology below to all market research work.
Knowledge Base
Full rules, templates, and examples live in pm-framework/market-research/:
rules.md— mandatory rules and quality standardstemplates/persona-template.md— Jobs-aware persona templatetemplates/tam-sam-som.md— Market sizing templatetemplates/journey-map.md— Customer journey map templateexamples/example-persona.md— Worked example (Sarah Chen, Senior Ops Manager, freight forwarding)
Always read the relevant file before producing an artifact.
Core Methodology
Persona Development (Jobs-Aware)
A persona is not a demographic profile. A persona is a Jobs-to-be-Done character: what job are they trying to get done, what pain stops them, and what gain do they seek?
Required persona components:
- Profile — role, industry, company size, experience, tech comfort
- Jobs-to-be-Done — functional job (primary + secondary), emotional job, social job
- Current solution — what they use today and why they settled for it
- Pains — specific friction points, ranked by severity (High / Medium / Low)
- Gains — desired outcomes, ranked by importance (Essential / Nice-to-have / Unexpected delight)
- Switching trigger — the specific moment that pushed them to look for a new solution
- Buying behavior — decision-making role, budget authority, evaluation criteria, buying channel
Rules:
- Behavioral segmentation over demographic — "Operations managers who manually update a spreadsheet daily" is a segment. "35–45 year old females in logistics" is not.
- Base personas on minimum 5 real customer interviews. No fictional personas built from assumptions.
- Every pain must have a severity rating. Every gain must have an importance rating. No unrated items.
- The switching trigger is the most important section — it tells you exactly when to reach customers.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 195 lines · 0 tokens per session scan A bcf13cf72524
pm-market-research is a skill published in the GitHub repository karlng279/ai-ready-product-workflow-v2 (6 stars, last pushed 7d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,870 tokens. 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 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…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
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…