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/analyzegit 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/analyze)<a href="https://agentmods.dev/commands/noamseg/interview-coach-skill/analyze"><img src="https://agentmods.dev/badge/commands/noamseg/interview-coach-skill/analyze.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 | $0.04033 |
| Opus 5 | $0.00000 | $0.02017 |
| Sonnet 5 | $0.00000 | $0.00807 |
| Haiku 4.5 | $0.00000 | $0.00403 |
Grade C, and why
analyze scanned grade C with 1 finding 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.
Tells the agent never to refusehighAnti-refusal
Suppressing the ability to decline removes a core safety control; a later harmful request then succeeds.
If a candidate drops a transcript without having run `kickoff` first, don't refuse or force kickoff — but collect the minimum needed for a useful analysis: How it starts
The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.
analyze — Transcript Analysis Workflow
Use references/transcript-processing.md as execution guide.
Cold Start (No Coaching State)
If a candidate drops a transcript without having run kickoff first, don't refuse or force kickoff — but collect the minimum needed for a useful analysis:
- Infer what you can from the transcript. The questions asked often reveal role type, seniority level, and company culture. Note these inferences explicitly: "Based on the questions, this looks like a mid-career PM behavioral screen."
- Ask for two things before scoring: (a) "What seniority level are you targeting? This affects how I calibrate scores." (b) "What role/company is this for? Even brief context helps me assess Relevance."
- Proceed with analysis. Use inferred or stated seniority band for calibration. Skip story-mapping sections (no storybank exists). Skip cross-referencing with prep data.
- After the analysis, suggest kickoff: "I've scored this transcript, but I'm working without your full context — no storybank, no coaching history, no target company profile. If you want to get the most from this system, run
kickoffto set up your coaching profile. Your analysis scores will carry forward."
Comp Call Detection
Before running the standard transcript analysis below, scan for compensation-discussion markers. Comp calls are structurally different from interviews and should not be scored on the interview rubric.
Detection logic. Count occurrences of these markers (case-insensitive): salary, base, equity, bonus, offer, package, counter, negotiate, compensation, vesting, sign-on, stock, RSU, pro-rate, band, range, budget.
- 3+ distinct markers → route to negotiation-specific analysis: score against the 5 Negotiation Performance Dimensions in
references/commands/negotiate.md("Comp Call Scoring"), not the standard interview rubric. Output the Negotiation Performance Scorecard. Write results to theComp Strategysection ofcoaching_state.md(not Score History — comp calls aren't interviews). - Fewer than 3 markers → proceed with the standard Step Sequence below.
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 · 207 lines · 0 tokens per session scan C 624770e65979
analyze 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 4,033 tokens. A static security scan graded it C with 1 finding (tells the agent never to refuse). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.