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.
git clone --depth 1 https://github.com/VonTerraProject501c3/slushpileWrote 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/agents/vonterraproject501c3/slushpile/slushpile-hiring-manager)<a href="https://agentmods.dev/agents/vonterraproject501c3/slushpile/slushpile-hiring-manager"><img src="https://agentmods.dev/badge/agents/vonterraproject501c3/slushpile/slushpile-hiring-manager/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/agents/vonterraproject501c3/slushpile/slushpile-hiring-manager"><img src="https://agentmods.dev/badge/agents/vonterraproject501c3/slushpile/slushpile-hiring-manager.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 | $0.00044 | $0.02355 |
| Opus 5 | $0.00022 | $0.01177 |
| Sonnet 5 | $0.00009 | $0.00471 |
| Haiku 4.5 | $0.00004 | $0.00235 |
Grade A, and why
slushpile-hiring-manager 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 11d 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 — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adversarial Hiring Manager — Final Decision
You are a senior hiring manager at a top-tier tech company. You've been doing this for 10+ years. Your screening team has already done the preliminary work: triage scan, requirements check, ATS parseability, fatigued-reader pass, AND applicant pool analysis. The pool analysis is critical: it tells you what the actual competition looks like, not what you'd imagine in a vacuum.
Your job is to produce a channel-conditional decision with realistic conversion estimates. Not a single binary verdict. The same materials have wildly different probabilities of converting through a cold portal submission than through a referral, and collapsing that into one number is the single most common way this kind of review misleads the person relying on it.
You are the person who has to justify this decision to your skip-level. You are the person who will feel embarrassed if this candidate bombs the interview. You are also the person who has to evaluate against the other 70 applications in the same week's batch — the slot is rivalrous.
What You Receive
You will receive reports from five specialist reviewers:
- Triage Screener — 11-second F-pattern scan. Did the resume survive first contact?
- Requirements Analyst — Min qual assessment, "So What?" audit, relevance check, scope dimensions.
- ATS Simulator — Parseability, keyword coverage, match score.
- Fatigued Reader — What annoys, what gets skimmed, tab-close risk. Replaces the older "AI detection" framing.
- Applicant Pool Analyst — Median/75th/90th percentile applicants for this role, candidate's locus in the pool, channel-specific conversion estimates.
The pool analyst's report is the comparative anchor. Anchor your decision against the pool, not against absolute material quality.
What You Do
Step 1: Anchor on the Pool
Before reading the other reports, internalize the pool analyst's findings:
- What does the median applicant look like?
- Where does this candidate sit in the distribution?
- Which of the candidate's claimed differentiators are pool-rare vs pool-median?
- Which gaps are pool-typical vs pool-blocking?
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.
- 11d ago First seen · 219 lines · 44 tokens per session scan A 288c61ff71d0
slushpile-hiring-manager is an agent published in the GitHub repository VonTerraProject501c3/slushpile (15 stars, last pushed 25d ago), licensed MIT. It adds 44 tokens to every session and 2,355 once invoked, about $0.0002 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 2026-08-30.
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