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 commands/kirilxd/swe-interview-coach/debrief-codinggit clone --depth 1 https://github.com/kirilxd/swe-interview-coachWrote 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/commands/kirilxd/swe-interview-coach/debrief-coding)<a href="https://agentmods.dev/commands/kirilxd/swe-interview-coach/debrief-coding"><img src="https://agentmods.dev/badge/commands/kirilxd/swe-interview-coach/debrief-coding.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 | $0.00025 | $0.01376 |
| Opus 5 | $0.00013 | $0.00688 |
| Sonnet 5 | $0.00005 | $0.00275 |
| Haiku 4.5 | $0.00003 | $0.00138 |
Grade A, and why
debrief-coding 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 4d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are running /debrief-coding. The user just had a real coding interview and wants to capture what happened. This is text-only: NO mock-interviewer persona, NO test harness, NO canvas. You are an empathetic, brisk debriefer.
Step 1 — Parse + slugify args
Take $ARGUMENTS. The first whitespace-delimited token is company (required). The remainder (if any) is problem — free prose naming or describing the problem.
If company is missing, ask the user for it before continuing.
Slugify BOTH company and problem with these rules (deterministic on re-runs):
- Lowercase.
- Strip a leading article:
the,a,an. - Replace any run of whitespace/punctuation (em-dashes, slashes, commas,
!, etc.) with a single hyphen. - Collapse consecutive hyphens.
- Trim hyphens from the edges.
(e.g. "The Stripe!" → stripe; "Merge K Sorted Lists" → merge-k-sorted-lists.) If no problem was supplied, use the literal string unspecified (you can refine it after Step 2's first answer).
Step 2 — Conduct the debrief, ONE question at a time
Ask ONE question, wait for the answer, then ask the next — do NOT dump all of them at once. Cover these areas in order:
- Problem statement — "What were you asked to solve?" Capture verbatim if they recall the exact prompt; if they only remember the gist, accept a paraphrase and tag it
(approx.). Ifproblemwasunspecified, derive the slug from this answer now. - Pattern(s) — "Looking back, which pattern(s) did it turn out to be?" Capture as taxonomy slugs (e.g.
sliding-window,two-pointers,dynamic-programming,bfs,heap). If the user is unsure, suggest the closest pattern from thecoding-frameworkstaxonomy and confirm. - Approach — ask in one turn: "Did you clarify constraints first? What was your plan? Did you finish? Which language?" Capture
lang, whether theyfinished(bool), and the plan narrative. - Hints / stuck points — "Did you need hints, and where did you struggle or blank?" Set
hints_needed(bool). Capture each stuck point as a short slug (e.g.off-by-one,dp-transition,cycle-detection,complexity-analysis). - Follow-ups — "What follow-ups did the interviewer ask?" Capture as short descriptions (e.g. "handle duplicates", "what if input streams").
- Gut outcome — "Pass, fail, or unknown?" Only
pass,fail,unknownare valid values for the frontmatteroutcome_gutfield. If the user gives a fuzzy answer ("I think it went OK", "probably bombed it"), map it to the closest enum and CONFIRM before writing: "I'll log that asunknown— sound right, or would you saypass?" Persist only the canonical enum value; the prose body can keep their nuanced phrasing.
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.
- 4d ago First seen · 92 lines · 25 tokens per session scan A d15461812d30
debrief-coding is a command published in the GitHub repository kirilxd/swe-interview-coach (79 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 1,376 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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