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 stefanoskarakasis/Product-Marketing-Skills --skill interview-summarygit 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/skills/stefanoskarakasis/product-marketing-skills/interview-summary)<a href="https://agentmods.dev/skills/stefanoskarakasis/product-marketing-skills/interview-summary"><img src="https://agentmods.dev/badge/skills/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/skills/stefanoskarakasis/product-marketing-skills/interview-summary"><img src="https://agentmods.dev/badge/skills/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 | $0.00110 | $0.03010 |
| Opus 5 | $0.00055 | $0.01505 |
| Sonnet 5 | $0.00022 | $0.00602 |
| Haiku 4.5 | $0.00011 | $0.00301 |
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.
How it starts
The opening of the file, as written. The whole thing — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
interview-summary — Customer Discovery Synthesis Engine
Transforms raw interview transcripts into structured intelligence. Not a transcription service. A synthesis engine that extracts Jobs, surfaces patterns, and flags contradictions with your positioning or ICP. Built on JTBD theory. Sharpened for B2B product and GTM contexts.
Trigger
- When: Any customer or prospect interview needs synthesis into structured discovery output. This includes: discovery calls, win/loss debriefs, churn interviews, competitive research interviews, onboarding feedback, feature validation calls, or any call where you need to extract Jobs, map solutions, and flag contradictions with your positioning or ICP.
- Not for:
- interview-summary is not a transcription tool — use Otter.ai or Fireflies for that.
- interview-summary is not for analyzing your own positioning or messaging in isolation.
If you need to check whether your messaging lands with buyers, route to
positioning-messagingorgaccs-brief. - interview-summary is not for building buyer personas from scratch without interviews. No dedicated persona-building skill exists yet; this skill synthesizes existing transcript data only.
- Example prompts:
- "Summarize this customer discovery call and flag which Jobs matter most"
- "I have a win/loss interview — help me extract what we lost and why"
- "Process this transcript. Flag any positioning signal that contradicts our current narrative"
- "Churn interview debrief — what Job did we fail to deliver on?"
Inputs
- Args: Path to a transcript file (
.txt,.md,.pdf), pasted plain text, structured note dump, or Otter/Fireflies/Rev transcription output. Optional: interview context (interviewee role, company, interview purpose). Free format — transcript alone is sufficient; context makes synthesis sharper. - Defaults: If no context provided, skill asks three orientation questions. If interviewee segment unknown, default to "Unclassified" in ICP match. If no interview type specified, default to "Discovery".
- Context keys:
/foundation/brain.md(ICP, Positioning, Beachhead Segment sections) — optional, if exists: load for validation/context/meta-patterns.md— optional; recurring patterns the user has logged from prior interviews
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 · 222 lines · 110 tokens per session scan A 9ce5d65b89bf
interview-summary is a skill published in the GitHub repository stefanoskarakasis/Product-Marketing-Skills (5 stars, last pushed yesterday), licensed MIT. It adds 110 tokens to every session and 3,010 once invoked, about $0.0006 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.
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