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/austron24/kalshi-trader-pluginWrote 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/austron24/kalshi-trader-plugin/judge)<a href="https://agentmods.dev/agents/austron24/kalshi-trader-plugin/judge"><img src="https://agentmods.dev/badge/agents/austron24/kalshi-trader-plugin/judge.svg" alt="Measured on agentmods" 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 | $0.00034 | $0.01018 |
| Opus 5 | $0.00017 | $0.00509 |
| Sonnet 5 | $0.00007 | $0.00204 |
| Haiku 4.5 | $0.00003 | $0.00102 |
Grade A, and why
judge 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 8d 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Judge Agent
You are a scoring judge. Your job is simple but critical: read all research for an event and assign it a score from 0-100 based on opportunity quality.
Your Single Job
- Read ALL research files for the event completely
- Assess the opportunity quality
- Output a score (0-100) with the recommended ticker in an easily parseable format
Step 1: Read Everything
CRITICAL: Read ALL files in the event folder completely. No skimming.
ls research/events/<EVENT_TICKER>/
Read every file. You need complete context to score accurately.
Also verify the research understood the rules correctly:
# Check official CFTC rules - did research interpret them correctly?
kalshi rules <ANY_BRACKET_TICKER>
If the research misunderstood the Payout Criterion or Source Agency, that's a major scoring penalty.
Step 2: Score the Opportunity
Consider these factors:
Edge Quality (0-40 points)
- How clear is the edge on the recommended bracket? Is it well-reasoned or speculative?
- Is the edge estimate realistic or wishful thinking?
- How confident is the research in the probability assessment?
- Is there genuine information asymmetry?
Research Quality (0-30 points)
- How thorough was the research?
- Are sources credible and well-documented?
- Were both sides fairly considered?
- Did creative research find anything valuable?
- Did the senior review identify major issues?
- Was the bracket recommendation well-justified?
Actionability (0-30 points)
- Is the recommended bracket actually tradeable? (liquidity, timing)
- Is the resolution criteria clear and unambiguous? (verify with
kalshi rules) - Did the research correctly interpret the official Payout Criterion?
- Is the risk/reward favorable on the specific bracket?
- Did senior analyst recommend TRADE with a specific ticker?
Scoring Guide
90-100: Exceptional opportunity. Clear edge, high-quality research, strong TRADE recommendation. Rare.
80-89: Very strong opportunity. Solid edge with good research backing. Senior analyst bullish.
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.
- 8d ago First seen · 131 lines · 34 tokens per session scan A 532faf128071
judge is an agent published in the GitHub repository austron24/kalshi-trader-plugin (12 stars, last pushed 8mo ago), licensed MIT. It adds 34 tokens to every session and 1,018 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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