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 itseffi/agentic-os --skill interview-cleanupgit clone --depth 1 https://github.com/itseffi/agentic-osWrote 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/itseffi/agentic-os/interview-cleanup)<a href="https://agentmods.dev/skills/itseffi/agentic-os/interview-cleanup"><img src="https://agentmods.dev/badge/skills/itseffi/agentic-os/interview-cleanup/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/itseffi/agentic-os/interview-cleanup"><img src="https://agentmods.dev/badge/skills/itseffi/agentic-os/interview-cleanup.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 | $0.00022 | $0.00280 |
| Opus 5.5 | $0.00009 | $0.00112 |
| Sonnet 5.5 | $0.00004 | $0.00056 |
| Haiku 4.5 | $0.00002 | $0.00028 |
Grade A, and why
interview-cleanup 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 1mo 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
Interview Transcript Cleanup
Clean up raw interview transcripts while preserving meaning and speaker voice.
When to Use
After conducting user interviews when you have raw transcripts that need cleanup before analysis.
The Process
-
Read the full transcript to understand context and flow
-
Remove noise without losing meaning:
- Filler words (um, uh, like, you know)
- False starts (incomplete/abandoned sentences)
- Redundancies (repeated words that don't add meaning)
-
Preserve what matters:
- Original meaning and intent
- Speaker's unique voice and style
- Speaker labels (Interviewer:, Interviewee:)
- Unclear/inaudible markers [inaudible]
-
Light editing only:
- Fix punctuation and capitalization
- Don't over-formalize casual language
- Don't cut unnecessarily
Quality Check
- Does the cleaned transcript read naturally?
- Is the original meaning preserved?
- Can you still hear the speaker's voice?
- Are all speakers clearly labeled?
When Not to Use
Do not use this skill when the request is unrelated, low-stakes, or better handled by a simpler direct response.
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.
- 1mo ago First seen · 44 lines · 22 tokens per session scan A 7ec9798290af
interview-cleanup is a skill published in the GitHub repository itseffi/agentic-os (117 stars, last pushed 14d ago), licensed MIT. It adds 22 tokens to every session and 280 once invoked, about $0.0001 per session on Opus 5.5. 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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