Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add archugunov/pm-job-search/plugin install pm-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/skills/archugunov/pm-job-search/interview-prep)<a href="https://agentmods.dev/skills/archugunov/pm-job-search/interview-prep"><img src="https://agentmods.dev/badge/skills/archugunov/pm-job-search/interview-prep/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/archugunov/pm-job-search/interview-prep"><img src="https://agentmods.dev/badge/skills/archugunov/pm-job-search/interview-prep.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 | $0.00172 | $0.03412 |
| Opus 5 | $0.00086 | $0.01706 |
| Sonnet 5 | $0.00034 | $0.00682 |
| Haiku 4.5 | $0.00017 | $0.00341 |
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 12d 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 — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/interview-prep — adapt the story bank for a specific interview
Produces a single per-interview prep doc that combines: the company's signals (from meta.md + research-brief.md + any prior debriefs), the user's positioning, the 3-5 most-relevant stories adapted for THIS interview, founder-vetting questions when the round warrants, and a short "anchors" section the user can scan before the call.
Voice: the company-disambiguation prompt, story-pick confirmation, take-home draft-or-not offer, and all written prep content follow ${CLAUDE_PLUGIN_ROOT}/TONE.md. Apply the low-effort-first principle — auto-detect stage from meta.md.status + last debrief; only ask if genuinely ambiguous.
Inputs
<Company>argument — required, e.g./interview-prep Plaidor/interview-prep "Plaid". Case-insensitive lookup againstuserdata/companies/<Co>/folder names. If no exact match, fuzzy-suggest:No 'Plad' folder. Did you mean Plaid? (y/n). If multi-role company (subfolder layout), ask which role:Plaid tracks 2 roles — pick: 1) senior-pm-consumer-credit, 2) lead-pm-risk-platform.userdata/companies/<Co>/[<slug>/]meta.md— frontmatter (position, tier, status, location), body.userdata/companies/<Co>/[<slug>/]research-brief.md— Company snapshot / Why this fits / Open questions.userdata/companies/<Co>/[<slug>/]interview-debrief-*.mdif present (prior rounds) — read the most recent 2; use to avoid repeating stories the user already told and to surface unanswered open questions.userdata/profile.md—## Positioning,## Proof Points,## Moat,## Tone of Voice.- All
userdata/stories/*.md— full STAR + angles + frontmatter (includingstory_typeif set). - Story taxonomy:
userdata/references/story-taxonomy.mdif present, else${CLAUDE_PLUGIN_ROOT}/references/story-taxonomy.md(userdata override per TONE.md convention). Used for the story-selection tiebreaker — see "Story selection" below.
Optional flags:
--stage <stage-name>— e.g.--stage cpo-round,--stage take-home,--stage final-loop. Shapes the prep doc emphasis (see "Stage shaping" below).--date <YYYY-MM-DD>— override the filename date (defaults to today).
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.
- 12d ago First seen · 182 lines · 172 tokens per session scan A 0cca60ef10b6
interview-prep is a skill published in the GitHub repository archugunov/pm-job-search (7 stars, last pushed 17d ago), licensed MIT. It adds 172 tokens to every session and 3,412 once invoked, about $0.0009 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.
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