Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/palashjain95/jobhunternpx agentmods add skills/palashjain95/jobhunter/interview-debriefWrote 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/palashjain95/jobhunter/interview-debrief)<a href="https://agentmods.dev/skills/palashjain95/jobhunter/interview-debrief"><img src="https://agentmods.dev/badge/skills/palashjain95/jobhunter/interview-debrief/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/palashjain95/jobhunter/interview-debrief"><img src="https://agentmods.dev/badge/skills/palashjain95/jobhunter/interview-debrief.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 | $0.00075 | $0.01092 |
| Opus 5 | $0.00037 | $0.00546 |
| Sonnet 5 | $0.00015 | $0.00218 |
| Haiku 4.5 | $0.00007 | $0.00109 |
Grade A, and why
interview-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 8d 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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/interview-debrief
If you see unfamiliar
~~placeholders, see CONNECTORS.md.
Usage
/interview-debrief <company name>
/interview-debrief I just finished my Google PM interview
One skill for everything after a formal interview: analyze performance, extract lessons, and draft the thank-you.
Inputs
Auto-detect from ~~transcription (if available)
Before asking the user anything, check if ~~transcription is connected. If yes: query recent meetings for interviews at the target company. If a transcript exists, pull it — this replaces most of the questions below. Tell the user: "I found your interview transcript. Let me analyze it."
Ask the user (if no transcript found)
Ask these one at a time. Wait for each answer before asking the next. After gathering context, briefly confirm what you heard before analyzing.
- "Which company and role was this for?"
- "What round? (phone screen, technical, HM, final)"
- "Who did you interview with? (name and role if known)"
- "What went well? What moment felt strongest?"
- "What stumbled? Any question that caught you off guard?"
- "Did they mention next steps or timeline?"
Also load
- output/[company]/interview-prep.md — what was prepared
- knowledge/stories/ — check if prepared stories were used effectively
- knowledge/frameworks/writing-framework.md — for thank-you tone
Produce
1. Performance Analysis
- Strong moments: what worked and why
- Weak moments: what didn't land and why
- Missed opportunities: stories or points you should have made
2. Signal Reading
- What their questions reveal about their concerns
- What their reactions suggest about your fit
- Likelihood of advancing (be honest)
3. Gap Analysis
- Questions you weren't prepared for → note for future prep
- Stories that didn't land → refine or replace
- Topics they probed deeply → they care about this
4. Next Round Prep
- What to expect in the next stage
- What to emphasize based on what resonated
- What to address based on concerns
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.
- 8d ago First seen · 145 lines · 75 tokens per session scan A e05cb2ae93c3
interview-debrief is a skill published in the GitHub repository palashjain95/jobhunter (2 stars, last pushed 5mo ago), licensed MIT. It adds 75 tokens to every session and 1,092 once invoked, about $0.0004 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 2026-08-31.
Other skills, from other repositories
mix-compression
Reduce mix output noise (5-15% token savings) by installing rtk filters that compress mix test/credo/dialyzer/compile output before it reaches Claude. Use when long mix output floods context.
quick
Implement small Phoenix changes without planning — add validations, update routes, fix components, create migrations. Use for single-file edits under 50 lines.
phx-mix-compression
Reduce mix output noise (5-15% token savings) by installing rtk filters that compress mix test/credo/dialyzer/compile output before it reaches Claude. Use when long mix output floods context.
i-have-adhd
Shape output for a reader with ADHD: lead with the next action, number multi-step work, restate state across turns, suppress tangents, give specific time estimates, make wins visible. Invoke with /i-have-adhd; stays on until "stop adhd mode".
phx-freeze
Apply an advisory edit scope in this session. Use for read-only or directory-scoped work; no enforcement hook is installed.
service-desk
Runs the IT service desk — intake, triage, prioritization, escalation, knowledge, and the metrics that improve service rather than distort it. Use this to set up or fix a service desk, design ticket priority and escalation, reduce repeat contacts, structure a knowledge base, or work out why a desk hitting its targets…