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 bostonaholic/team --skill product-thinkinggit clone --depth 1 https://github.com/bostonaholic/teamWrote 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/bostonaholic/team/product-thinking)<a href="https://agentmods.dev/skills/bostonaholic/team/product-thinking"><img src="https://agentmods.dev/badge/skills/bostonaholic/team/product-thinking.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 | $0.00026 | $0.00348 |
| Opus 5 | $0.00013 | $0.00174 |
| Sonnet 5 | $0.00005 | $0.00070 |
| Haiku 4.5 | $0.00003 | $0.00035 |
Grade A, and why
product-thinking 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 3d 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
Product Thinking
This reasoning lens produces no artifact and blocks nothing. It guides pre-implementation scope toward work a real person wants.
Core Lenses
- Demand evidence over assertion: identify a real demand signal, not technical possibility.
- Smallest thing people want: choose the thinnest valuable version; reject speculative work.
- Build for someone specific, not nobody: name the person or role served; surface absent users.
- Talk-to-users mindset: treat stated intent as a demand proxy and mark assumptions that lack validation.
When Framing the Task
For 1-task.md inferred goal and acceptance signals, ask: Who specifically is this for? What observable signal shows demand? What is the smallest version that serves them?
These questions affect 1-task.md framing only. Never put the goal or demand assumptions into 2-questions.md.
When Designing
For ## Decisions made and ## Out of scope, ask whether each decision serves a known rather than hypothetical need, where demand is assumed, and what thinnest design delivers the wanted outcome. Record uncertainty as an open question.
When Slicing
Ask whether slice 1 delivers something wanted rather than infrastructure, whether any slice serves nobody, and whether scope can shrink further. Cut or reorder slices that fail.
Lens, Not Dogma
Use judgment. This lens never gates the pipeline or requires extra user-research ceremony when stated intent identifies the user and demand. Empty/trivial tasks require no extra questions.
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.
- 3d ago Changed · -41 lines · -14 tokens per session c549d2c06bc7
- 8d ago First seen · 76 lines · 40 tokens per session scan A c45eb5fe49a7
product-thinking is a skill published in the GitHub repository bostonaholic/team (11 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 348 once invoked, about $0.0001 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.
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