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 skills add jeffreytse/grimoire-core --skill design-hiring-processgit clone --depth 1 https://github.com/jeffreytse/grimoire-coreWrote 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/jeffreytse/grimoire-core/design-hiring-process)<a href="https://agentmods.dev/skills/jeffreytse/grimoire-core/design-hiring-process"><img src="https://agentmods.dev/badge/skills/jeffreytse/grimoire-core/design-hiring-process/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/jeffreytse/grimoire-core/design-hiring-process"><img src="https://agentmods.dev/badge/skills/jeffreytse/grimoire-core/design-hiring-process.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 | $0.00027 | $0.00884 |
| Opus 5 | $0.00014 | $0.00442 |
| Sonnet 5 | $0.00005 | $0.00177 |
| Haiku 4.5 | $0.00003 | $0.00088 |
Grade A, and why
design-hiring-process 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 9d 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Hiring Process
Create a structured, repeatable hiring process that predicts job performance and reduces bias.
Why This Is Best Practice
Adopted by: Google (Project Oxygen), Stripe, Airbnb, and organizations following Schmidt & Hunter's 80-year meta-analysis of hiring validity Impact: Structured interviews have 2× the predictive validity of unstructured ones (Schmidt & Hunter, 1998); Google's data-driven hiring reduced bad hires by 25% after removing brain-teasers and adding structured rubrics
Why best: Unstructured hiring defaults to affinity bias — interviewers hire people like themselves. A structured process defines what "good" looks like before meeting any candidate, forcing evaluation against a common standard.
Steps
- Write the job scorecard — Before opening the role, define 4–6 competencies required for success in the first year. Each competency has a behavioral definition and an "A-player" example. This is not a job description; it is the evaluation rubric.
- Map the interview stages — Assign each competency to one interviewer. No competency is assessed by more than two people. Typical stages: recruiter screen → technical/skills screen → structured panel → executive calibration.
- Write structured questions — For each competency, write 2–3 behavioral questions ("Tell me about a time when…") and 1 work-sample prompt. Behavioral questions are more predictive than hypotheticals.
- Define the scoring rubric — Use a 1–4 scale per competency: 1 = clear no, 2 = leaning no, 3 = leaning yes, 4 = clear yes. Write behavioral anchors for 2 and 4 so scorers calibrate consistently.
- Train interviewers — Run a 60-minute calibration session before the first candidate. Interviewers practice scoring on a sample response. Standardize how the debrief will run.
- Run independent scoring — Each interviewer submits a written score before the debrief. Verbal-only debriefs allow the first person to speak to anchor everyone else.
- Debrief with data — Facilitator reads scores aloud. Discuss only competencies with disagreement (≥2 point gap). Make a hire/no-hire decision tied to scorecard, not gut feel.
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.
- 9d ago First seen · 53 lines · 27 tokens per session scan A 8c7e4140e401
design-hiring-process is a skill published in the GitHub repository jeffreytse/grimoire-core (4 stars, last pushed 24d ago), licensed MIT. It adds 27 tokens to every session and 884 once invoked, about $0.0001 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 2026-09-03.
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