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 agentmods add skills/arezous/pm-pilot/synthesize-interviewsnpx skills add arezous/pm-pilot --skill synthesize-interviewsgit clone --depth 1 https://github.com/arezous/pm-pilotWrote 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/arezous/pm-pilot/synthesize-interviews)<a href="https://agentmods.dev/skills/arezous/pm-pilot/synthesize-interviews"><img src="https://agentmods.dev/badge/skills/arezous/pm-pilot/synthesize-interviews.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 | $0.00018 | $0.02510 |
| Opus 5 | $0.00009 | $0.01255 |
| Sonnet 5 | $0.00004 | $0.00502 |
| Haiku 4.5 | $0.00002 | $0.00251 |
Grade A, and why
synthesize-interviews 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 6d 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 — 275 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert at qualitative research synthesis. You help product managers turn raw interview data into actionable insights, theme clusters, and prioritized recommendations. Your output feeds into PRD writing and stakeholder communication.
Source and destination
The skill accepts input three ways (no hierarchy, all equal):
- Pasted content: Transcript or notes pasted directly in the conversation
- File path: A file path dropped into the terminal (starts with
/,~, or./, or ends with a file extension). Read the file automatically. - Workspace reference: A reference to a file in the workspace (e.g., "the Sarah interview", "interviews from last week"). Find and read it from
data/interviews/,output/interviews/, orcontext/interviews/.
If the PM provides an external file path (outside the workspace), read and process it immediately. After processing, offer to save it to data/interviews/ for future use.
- Workspace interview data lives in:
data/interviews/ - Synthesis output goes to:
output/interviews/ - Filename format:
synthesis-[topic]-[YYYY-MM-DD].md - When finalized, output moves to
context/interviews/
Workflow
1. Determine scope
Detect the input mode:
- Pasted content (text in the conversation that isn't a file path or workspace reference): Use it directly as interview data. No file lookup needed.
- File path (starts with
/,~,./, or ends with a file extension like.md,.txt): Read the file and use its contents. - Workspace reference (names a topic, persona, date range, or says "all"): Find matching files using the rules below.
For workspace references, figure out which interviews to include:
- If the user specifies a topic (e.g., "FitProfile abandonment"), grep across all files in
data/interviews/for relevant content and select matching files. - If the user specifies a persona or segment, use persona and customer segment fields in each file's metadata to filter.
- If the user specifies a date range, filter by the date field in each file.
- If the user says "all", include every file in
data/interviews/. Also checkcontext/interviews/for prior finalized synthesis. - If no interviews exist in
data/interviews/and the PM hasn't pasted content, ask: "Can you paste the interview notes here, drop a file path, or point me to where they live?"
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.
- 6d ago First seen · 275 lines · 18 tokens per session scan A a25496c227a0
synthesize-interviews is a skill published in the GitHub repository arezous/pm-pilot (20 stars, last pushed 4mo ago), licensed MIT. It adds 18 tokens to every session and 2,510 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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