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.
git clone --depth 1 https://github.com/stefanoskarakasis/Product-Marketing-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/commands/stefanoskarakasis/product-marketing-skills/interview-summary)<a href="https://agentmods.dev/commands/stefanoskarakasis/product-marketing-skills/interview-summary"><img src="https://agentmods.dev/badge/commands/stefanoskarakasis/product-marketing-skills/interview-summary/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/commands/stefanoskarakasis/product-marketing-skills/interview-summary"><img src="https://agentmods.dev/badge/commands/stefanoskarakasis/product-marketing-skills/interview-summary.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 | $0.00011 | $0.00153 |
| Opus 5 | $0.00005 | $0.00077 |
| Sonnet 5 | $0.00002 | $0.00031 |
| Haiku 4.5 | $0.00001 | $0.00015 |
Grade A, and why
interview-summary 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.
What it actually says
/pmm-execution:interview-summary -- Interview Summary
Turn a raw customer or prospect interview transcript into a structured discovery summary anchored in Jobs to Be Done theory.
Invocation
/pmm-execution:interview-summary [paste transcript]
/pmm-execution:interview-summary Win-loss call with Acme Corp, lost to
Salesforce
Workflow
Uses the interview-summary skill. Extracts the Job, pain points, and
signal quotes from the transcript, flags any competitor or pattern
signal worth routing elsewhere, and produces the structured summary.
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 · 24 lines · 11 tokens per session scan A 2a39a20113f7
interview-summary is a command published in the GitHub repository stefanoskarakasis/Product-Marketing-Skills (5 stars, last pushed yesterday), licensed MIT. It adds 11 tokens to every session and 153 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 2026-08-31.
Other commands, from other repositories
brief-me
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design-ai-feature
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competitive-intel
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discover
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retro
Run a post-ship retrospective — measure outcomes vs. predictions, extract lessons, update memory, and feed insights back into the PM system.
setup-metrics
Set up your metrics framework — North Star selection, funnel definition, dashboard structuring, and A/B test design for your key bets.