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/pedrolucazx/job-search/interview-prepgit clone --depth 1 https://github.com/pedrolucazx/job-searchWrote 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/pedrolucazx/job-search/interview-prep)<a href="https://agentmods.dev/commands/pedrolucazx/job-search/interview-prep"><img src="https://agentmods.dev/badge/commands/pedrolucazx/job-search/interview-prep.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 5.1 | $0.00000 | $0.00080 |
| Opus 5 | $0.00000 | $0.00040 |
| Sonnet 5 | $0.00000 | $0.00016 |
| Haiku 4.5 | $0.00000 | $0.00008 |
Grade A, and why
interview-prep 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.
What it actually says
Read workflows/interview-prep.md, profile/candidate.yaml,
rules/interview-roteiro.md + rules/job-evaluation.md (to re-fetch the
job description) and rules/cv-rules.md (for the overlap logic reused when
picking the project). Execute the steps described there for the company
received in $ARGUMENTS.
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 · 6 lines · 0 tokens per session scan A 8d258f3bcb70
interview-prep is a command published in the GitHub repository pedrolucazx/job-search (5 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 80 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 2026-08-31.
Other commands, from other repositories
setup
You are running the onboarding setup for the AI Job Search framework. Your goal is to collect the user's professional information and populate all profile files so the /apply workflow works out of the box.
apply
You are orchestrating a two-agent job application workflow. The job posting is provided below as $ARGUMENTS (either a URL or pasted text).
add-portal
You are helping the user build a job-portal search skill for a US job board. The repo ships a worked example of the pattern (freehire-search) — this command turns that pattern into a guided workflow: investigate the portal, scaffold the skill from the canonical structure, and test-run a live query before registering…
add-template
You are helping the user register their own CV or cover letter template with the AI Job Search framework — LaTeX, Typst, or any other toolchain that compiles to PDF from the command line. The framework ships with moderncv (banking style) for CVs and a custom cover.cls for cover letters. This command lets the user swap…
rank
You are batch-scoring the jobs that /scrape has collected, so the user can decide where to spend /apply effort. /scrape finds and dedupes postings; /apply evaluates one at a time in depth. /rank is the bridge: it scores every new posting against the fit framework and returns a ranked shortlist.
outcome
You are recording what happened to a job application: progress updates (interview invitations, stages completed, offers) and final resolutions (hired, rejected, no response). The data lands in two places the framework already reads but nothing systematically writes.