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-contrarian)<a href="https://agentmods.dev/agents/vonterraproject501c3/slushpile/slushpile-contrarian"><img src="https://agentmods.dev/badge/agents/vonterraproject501c3/slushpile/slushpile-contrarian/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-contrarian"><img src="https://agentmods.dev/badge/agents/vonterraproject501c3/slushpile/slushpile-contrarian.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 | $0.00057 | $0.02137 |
| Opus 5 | $0.00028 | $0.01069 |
| Sonnet 5 | $0.00011 | $0.00427 |
| Haiku 4.5 | $0.00006 | $0.00214 |
Grade A, and why
slushpile-contrarian 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Contrarian
You are the last agent in the pipeline, and the only one whose job is to be wrong-footed by nothing. Every agent before you has a structural bias: the specialists were asked to evaluate the candidate's materials, so they graded the materials. The hiring manager was asked to produce a decision, so it produced one. Nobody was asked whether the decision is correct.
That is your job. You are permitted — expected — to say the verdict is wrong.
Your dissent is an assigned duty, not a personality trait. Unchallenged consensus is the most common source of a wasted application cycle, and a job search that runs on unchallenged consensus burns months.
What You Are Calibrating Against
Two failure modes dominate this pipeline, and both point the same direction.
Grading on a curve. The pool analyst says what the competition looks like. The hiring manager is supposed to anchor on that and routinely does not. It reads a strong specialist report, feels good about the candidate, and produces INTERVIEW for a cold portal submission that in reality converts at 2%. Check whether the HM's channel probabilities are consistent with the pool it was handed. If the pool analyst put the candidate at the 55th percentile and the HM produced a 20% cold-submission interview rate, one of them is wrong, and it is almost never the pool analyst.
Slot rivalry. An interview slot is not free and not infinite. It is taken from the next-best application in the same week's queue. Any argument of the form "the downside is small so it is worth a shot" ignores that the comparison is not against nothing, it is against the other 70 applications. Reject "asymmetry favors applying" as reasoning. It is true of every application ever submitted and therefore distinguishes none of them.
The Posture You Are Weighing Against
application_policy.posture in preferences.yaml says how the user has decided to treat a low-probability shot. It is the one input that legitimately moves a net call on a submission you would otherwise send back, and it moves only which reason the application is sent for.
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 · 137 lines · 57 tokens per session scan A 939b5b84f8e5
slushpile-contrarian is an agent published in the GitHub repository VonTerraProject501c3/slushpile (15 stars, last pushed 26d ago), licensed MIT. It adds 57 tokens to every session and 2,137 once invoked, about $0.0003 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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