interview-notes

interview-notes is a skill for Claude Code from niharya/skills-drawer. It costs 139 tokens per session (2,612 once invoked), scanned A, original, MIT.

An interview-transcript analysis workflow that cleans a recorded conversation, logs its edits, and separates a quick summary from detailed notes. It also answers follow-up questions using checked quotes and findings.

In plain words
What is it for?
Use it to clean founder, customer, staff, or client interviews; identify patterns and important points; and create readable notes with verified quotes, counts, and numbers.
Why use it?
It removes the need to manually tidy a transcript and search through it for themes, decisions, and evidence. It helps prevent misquoting people or treating unsupported statements as facts.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the interviews plugin — 1 skill shipped together

Good fit Use it to clean founder, customer, staff, or client interviews; identify patterns and important points; and create readable notes with verified quotes, counts, and numbers.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/niharya/skills-drawer/interview-notes
Install

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.

Any agent
npx skills add niharya/skills-drawer --skill interview-notes
Clone the repo
git clone --depth 1 https://github.com/niharya/skills-drawer

Made for: Claude Code.

Or install interviews, the plugin that ships this one along with the rest of its 1 skill.

Wrote 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.

agentmods badge for interview-notes

README.md
[![agentmods](https://agentmods.dev/badge/skills/niharya/skills-drawer/interview-notes/github.svg)](https://agentmods.dev/skills/niharya/skills-drawer/interview-notes)
Your own site
<a href="https://agentmods.dev/skills/niharya/skills-drawer/interview-notes"><img src="https://agentmods.dev/badge/skills/niharya/skills-drawer/interview-notes/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.

agentmods 80×15 button for interview-notes

Your own site · 80×15
<a href="https://agentmods.dev/skills/niharya/skills-drawer/interview-notes"><img src="https://agentmods.dev/badge/skills/niharya/skills-drawer/interview-notes.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 139 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,612 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00139 $0.02612
Opus 5.5 $0.00056 $0.01045
Sonnet 5.5 $0.00028 $0.00522
Haiku 4.5 $0.00014 $0.00261

Measured 3d ago against content hash 03ea4bdb62c7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

interview-notes 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 3d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/hinglish.py, scripts/ia.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

interviews/skills/interview-notes/SKILL.md · 111 lines

How it starts

The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Interview Notes

Read one interview the way a careful analyst would, before the interviewer listens to it themselves. Do the parsing, organising and pattern-finding that AI does well; never put words in anyone's mouth. First the transcript is cleaned into a copy people can read, with every change logged. Then the user gets two layers: the read in chat (one screen: what matters most, what to check) and the notes in a doc (the full depth, every quote checked). Then anything they ask afterwards.

Find this skill's folder from the "Base directory for this skill" line shown when it loaded; call it SKILL_DIR. Every check runs through python3 -I "$SKILL_DIR/scripts/ia.py" <command> …, from a fresh working folder (mkdir -p ~/interview-notes && cd ~/interview-notes). Never run the scripts from inside the upload folder. reference/commands.md lists every command.

Creed

Stories beat statements. One correction beats ten agreements. Their words beat ours. One true finding beats five safe ones. Look before you confirm. Silence only counts if you asked. Say what you can't see.

Rules that never bend

  1. The checks govern claims, never noticing. Anything striking may be reported, labelled as noticed. Every claim, quote, count and number passes the scripts before the user sees it.
  2. The interviewer's words are never the person's evidence. Quote marks hold only the interviewee's words; the interviewer's words go in italics. Every quote carries its turn, (T042). A "yes" to a cut-off question is a backchannel, not agreement.
  3. Code does the checking, never memory: parsing, quotes, turn references, counts, numbers, chapter coverage. Never count by hand. Never add up counts in your head; ask the script.
  4. Their words stay theirs. Quote exactly as the transcript has it, hesitations and all (uh, -, repeats), or exactly as the clean copy has it (its only differences are logged corrections and removed fillers). Keep the script they were transcribed in: Hindi in Devanagari stays Devanagari; English that the transcriber wrote in Devanagari goes back into English, word for word, and the checks confirm it sounds the same. Never translate silently; gloss in square brackets if needed. Each quote appears once in the notes.
  5. Say what you can't tell. Every read and every set of notes ends with what the interview cannot show. Flags travel with the quotes they touch.
  6. Opinions about the evidence, never about the person. Find how they work, what they say, choose and reject, and how they answer. Never claim what they fear, need, secretly mean or "really are". No diagnosis, no adjectives about character.
  7. Nothing is deleted from the base or the clean copy. The clean copy keeps every stretch, money and small talk included; Stage 1 keeps everything; the notes rank it, the read selects. Private material informs the read and never reaches anything shareable.
  8. Transcript only. If given audio or video, say plainly that this skill works from a transcript and suggest transcribing it first (with speaker labels on). Do not transcribe. A second transcript of the same recording (the video's own, a phone app's) is a dictionary for hard words: ref add, never a part, never quoted.
  9. Ask, then wait; check, then say done. When you ask the user something, wait for the answer before building on it. Before calling any stage done, run its check and read the result once yourself. Things for the user to check come as a short list.

Read the full file on GitHub · 111 lines

Changes

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.

  1. 3d ago First seen · 111 lines · 139 tokens per session scan A 03ea4bdb62c7

Subscribe to this mod's changes

interview-notes is a skill published in the GitHub repository niharya/skills-drawer (2 stars, last pushed 4d ago), licensed MIT. It adds 139 tokens to every session and 2,612 once invoked, about $0.0006 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 2026-11-08.

Related

interview-notes compared with skills from other repositories

interview-notes next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
interview-notesniharya/skills-drawerSkill24d agoMITA139Claude Code
layout-disciplinecrazyzlnofficial/layout-disciplineSkill44mo agoMITA105Claude Code, Codex
huedominikmartn/hueSkill900yesterdayMITA84Claude Code, Codex
social-postHao0321/claude-skill-social-postSkill84527d agoMITA119Codex
comfyuiSlavaSexton/ComfyUI-Agent-KitSkill1208d agoApache-2.0A107Claude Code
socialpostHao0321/claude-skill-social-postSkill84527d agoMITA92Codex
minimax-h3SlavaSexton/ComfyUI-Agent-KitSkill1208d agoApache-2.0A102Claude Code