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 yuusakuri/agent-skills --skill summarize-interviewgit clone --depth 1 https://github.com/yuusakuri/agent-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/yuusakuri/agent-skills/summarize-interview)<a href="https://agentmods.dev/skills/yuusakuri/agent-skills/summarize-interview"><img src="https://agentmods.dev/badge/skills/yuusakuri/agent-skills/summarize-interview/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/yuusakuri/agent-skills/summarize-interview"><img src="https://agentmods.dev/badge/skills/yuusakuri/agent-skills/summarize-interview.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 | $0.00046 | $0.00429 |
| Opus 5.5 | $0.00018 | $0.00172 |
| Sonnet 5.5 | $0.00009 | $0.00086 |
| Haiku 4.5 | $0.00005 | $0.00043 |
Grade A, and why
summarize-interview 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 2mo 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.
This is a copy
100% identical to summarize-interview — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Summarize Customer Interview
Transform an interview transcript into a structured summary focused on Jobs to Be Done, satisfaction, and action items.
Context
You are summarizing a customer interview for the product discovery of $ARGUMENTS.
The user will provide an interview transcript — either as an attached file (text, PDF, audio transcription) or pasted directly. Read any attached files first.
Instructions
-
Read the full transcript carefully before summarizing.
-
Fill in the summary template below. Use "-" if information is unavailable. Replace numeric values with qualitative descriptions if needed (e.g., "not satisfied").
-
Use clear, simple language — a primary school graduate should be able to understand the summary.
Output Template
**Date**: [Date and time of the interview]
**Participants**: [Full names and roles]
**Background**: [Background information about the customer]
**Current Solution**: [What solution they currently use]
**What They Like About Current Solution**:
- [Job to be done, desired outcome, importance, and satisfaction level]
**Problems With Current Solution**:
- [Job to be done, desired outcome, importance, and satisfaction level]
**Key Insights**:
- [Unexpected findings or notable quotes]
**Action Items**:
- [Date, Owner, Action — e.g., "2025-01-15, Paweł Huryn, Follow up with customer about pricing"]
Save the summary as a markdown document in the user's workspace.
Further Reading
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.
- 2mo ago First seen · 54 lines · 46 tokens per session scan A 5a2a0c8257f5
summarize-interview is a skill published in the GitHub repository yuusakuri/agent-skills (2 stars, last pushed 14d ago), licensed MIT. It adds 46 tokens to every session and 429 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to summarize-interview, differing in 0 lines, and is treated as a copy.
summarize-interview compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| summarize-interviewyuusakuri/agent-skills | Skill | 2 | 14d ago | MIT | A | 46 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |