Borrowing it
Nothing to install: this file belongs to Sma1lboy/coforce-apply. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Sma1lboy/coforce-apply/main/.agents/skills/interview/SKILL.mdgit clone --depth 1 https://github.com/Sma1lboy/coforce-applyWrote 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/sma1lboy/coforce-apply/interview)<a href="https://agentmods.dev/skills/sma1lboy/coforce-apply/interview"><img src="https://agentmods.dev/badge/skills/sma1lboy/coforce-apply/interview/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/sma1lboy/coforce-apply/interview"><img src="https://agentmods.dev/badge/skills/sma1lboy/coforce-apply/interview.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 | $0.00085 | $0.01440 |
| Opus 5.5 | $0.00034 | $0.00576 |
| Sonnet 5.5 | $0.00017 | $0.00288 |
| Haiku 4.5 | $0.00009 | $0.00144 |
Grade A, and why
interview 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 2mo 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interview — prep for a tracked application
The apply/campaign skills optimize what the company reads; this skill optimizes what the company hears. The bridge is consistency: the interviewer has read the submitted resume, so every talking point prepared here must match what that document claims.
Read ~/.coforce/instructions.md first if present — it overrides everything
below. Data home resolves as $COFORCE_HOME → <checkout>/.coforce/ →
~/.coforce.
Step 0: Identify the application
$ARGUMENTS may name a company (optionally a role). Match against
~/.coforce/applications.json (tracker skill's schema), case-insensitive on
company, then position/title. One match → proceed. Several → list and
ask. None → not tracked; accept the posting and role directly if the user
wants to prep anyway (suggest tracking it after).
Without an argument: list entries whose status suggests a live process
(interviewing, offer, or applied updated in the last 21 days) and ask
which one. Prep targets a specific application — for generic practice,
prep against a real tracked entry instead.
Step 1: Load the application context
- The tracker entry:
description(the JD as applied to),notes,history— feedback recorded from an earlier stage is the highest-value input for the next stage's prep. - The archive
~/.coforce/applications/<id>/: the resume PDF that was actually submitted (campaign copy orout/copy). This is what the interviewer read — Read it; every story told in the interview must be consistent with its claims. Also any existinginterview-prep.md(you are updating for a new stage, not starting over) and the globalinterview-cheatsheet.mdsibling if present. ~/.coforce/profile.json— the verified pool. STAR stories may only draw on bullets and facts that live there; an interview answer is held to the same never-fabricate law as the resume.- Ask the user what this interview is (skip anything already recorded): stage (phone screen / technical / system design / behavioral / final), date, format, and who is interviewing (names/titles if known).
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.
- 2mo ago First seen · 123 lines · 85 tokens per session scan A fbbaa19ab35c
interview is a skill published in the GitHub repository Sma1lboy/coforce-apply (5 stars, last pushed 1mo ago), licensed MIT. It adds 85 tokens to every session and 1,440 once invoked, about $0.0003 per session on Opus 5.5. 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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