debrief

debrief is a command for Claude Code from kirilxd/swe-interview-coach. It costs 47 tokens per session (1,308 once invoked), scanned A, original, MIT.

A guided record of a completed behavioral job interview, covering the questions asked, stories you told, surprises, and your overall impression.

In plain words
What is it for?
Debriefing an interview, recording approximate question wording, linking answers to prepared stories, and capturing lessons for future interviews.
Why use it?
It turns a fresh but easily forgotten conversation into a searchable session record and updates the question index for the company and role.

Command for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Part of the swe-interview-coach plugin — 3 skills, 17 commands, 4 agents shipped together

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.

agentmods
npx agentmods add commands/kirilxd/swe-interview-coach/debrief
Clone the repo
git clone --depth 1 https://github.com/kirilxd/swe-interview-coach

Made for: Claude Code.

Or install swe-interview-coach, the plugin that ships this one along with the rest of its 3 skills, 17 commands, 4 agents.

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 debrief

README.md
[![agentmods](https://agentmods.dev/badge/commands/kirilxd/swe-interview-coach/debrief.svg)](https://agentmods.dev/commands/kirilxd/swe-interview-coach/debrief)
Your own site
<a href="https://agentmods.dev/commands/kirilxd/swe-interview-coach/debrief"><img src="https://agentmods.dev/badge/commands/kirilxd/swe-interview-coach/debrief.svg" alt="Measured on agentmods" height="20"></a>
Per session 47 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,308 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00047 $0.01308
Opus 5 $0.00023 $0.00654
Sonnet 5 $0.00009 $0.00262
Haiku 4.5 $0.00005 $0.00131

Measured 6d ago against content hash bb5b7986baea, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

debrief 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.

commands/debrief.md · 95 lines

How it starts

The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are running /debrief. The user just had a real behavioral interview at <company> and wants to capture what happened.

Step 1 — Parse arguments

Extract company (required) and job_title (optional) from $ARGUMENTS.

If no company: ask the user.

If job_title is provided as a plain string: slugify using the same rules as /story-import (lowercase, strip leading articles "the"/"a"/"an", replace whitespace and punctuation with single hyphens, collapse consecutive hyphens, trim hyphens from edges).

If no job_title: ask the user. If they don't have a specific title, default to _general.

Step 2 — Conduct the debrief interview

You are NOT in mock-interviewer mode. You are a debriefer. Be empathetic and brisk. Ask one focused question at a time. Cover all four areas:

  1. Verbatim questions: "Walk me through every question they asked, as close to verbatim as you remember."
    • Capture each as a list item.
    • If the user cannot recall exact wording, accept paraphrases and append (approx.) after the question text. Capture the topic/intent even if the precise phrasing is lost.
  2. Stories told: "For each question, which canonical/mapped story did you tell? How did it land?"
    • Capture: story-id/variant-id; landing notes (e.g., "got follow-up", "they pushed back", "no follow-up").
  3. Surprises: "Any questions you didn't have a story for? Anything that felt out-of-distribution?"
    • Capture as a list of new gaps. Slugify each gap to a short identifier (e.g., "disagreed-with-manager", "calculated-risk-failed") for the frontmatter list.
  4. Self-assessment: "What worked, what didn't — gut sense, pass / fail / unknown?"
    • Only accepted values for outcome_gut in the frontmatter: pass, fail, unknown.
    • If the user gives an ambiguous answer (e.g., "leaning pass but not sure", "probably failed"), map it to the closest enum value and confirm: "I'll log that as unknown — sound right, or would you say pass?"
    • Persist only the canonical enum value to the frontmatter; the prose summary in the body can carry the user's nuanced phrasing.

Read the full file on GitHub · 95 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. 6d ago First seen · 95 lines · 47 tokens per session scan A bb5b7986baea

Subscribe to this mod's changes

debrief is a command published in the GitHub repository kirilxd/swe-interview-coach (80 stars, last pushed 1mo ago), licensed MIT. It adds 47 tokens to every session and 1,308 once invoked, about $0.0002 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.