Interview Coach is a Claude Code-based coaching system for the full job-search process, including job-description analysis, application materials, interview practice, answer evaluation, and offer negotiation. It is intended for job seekers who want tailored feedback and structured preparation based on their own experience and interview transcripts. Its catalogue entry consists of commands, a setting, and a skill that provide the coaching workflows.
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/noamseg/interview-coach-skill/concernsgit clone --depth 1 https://github.com/noamseg/interview-coach-skillWrote 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/noamseg/interview-coach-skill/concerns)<a href="https://agentmods.dev/commands/noamseg/interview-coach-skill/concerns"><img src="https://agentmods.dev/badge/commands/noamseg/interview-coach-skill/concerns.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 | $0.00000 | $0.01230 |
| Opus 5 | $0.00000 | $0.00615 |
| Sonnet 5 | $0.00000 | $0.00246 |
| Haiku 4.5 | $0.00000 | $0.00123 |
Grade A, and why
concerns 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 5d 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
concerns — Concern Anticipation Workflow
Sequence
- Ask candidate what concerns they expect.
- Validate correct concerns.
- Generate concerns from real data — don't work in a vacuum. Pull from:
- Resume analysis (career gaps, short tenures, domain switches, seniority mismatches — from kickoff)
- Storybank gaps (competencies with no strong story)
- Previous analyze results (patterns and weak dimensions)
- The specific role/company (does the JD require something the candidate lacks?)
- Career narrative gaps (transitions that need explaining)
- Outcome Log (if real interview outcomes exist): Use past rejections as counter-evidence for current concerns. If the candidate was previously rejected for "not enough leadership experience" but has since advanced at two other companies on leadership questions, that outcome data weakens this concern. Conversely, if the same concern has driven 2+ rejections, it's confirmed — escalate its severity.
- Add any concerns the candidate missed.
- Rank by severity: Not all concerns are equal. Assign each one:
- Dealbreaker: This could single-handedly end the candidacy if not addressed well (e.g., missing a core required skill, a very short recent tenure that looks like termination)
- Significant: Will come up and needs a strong counter, but won't kill the candidacy alone (e.g., no direct industry experience, a slightly junior background)
- Minor: Might come up as a probe but unlikely to be decisive (e.g., a 2-year-old role change, a less prestigious school)
- Attach counter strategies — with multiple framings for each significant+ concern:
- The direct question: How to answer "Why did you leave after 8 months?" head-on
- The subtle probe: How to handle "Tell me about a time things didn't work out" when they're really asking about the short tenure
- The follow-up challenge: How to handle "But wouldn't that be a risk in this role too?" after your initial counter
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.
- 5d ago First seen · 87 lines · 0 tokens per session scan A 976d5eeaebab
concerns is a command published in the GitHub repository noamseg/interview-coach-skill (2,112 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,230 tokens. 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.
Other commands, from other repositories
cancel-ralph
Cancel active Ralph Loop.
obsidian-recap
Summarize a time period from the vault - today, week, or month.
setup-pm-skills
Onboard a new user — find out what they do, recommend the right bundles & top skills, and set up a project CONTEXT.md so every skill is tailored to them.
release
Perform a full release: generate release notes, bump version, commit, tag, and push.
statusbar-style
Switch the status-bar style (classic / capsule / hairline).
engage.actions
Execute Phase 7 - Actions on Objectives and Goal Achievement.