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 agentmods add commands/austron24/kalshi-trader-plugin/scoregit 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/commands/austron24/kalshi-trader-plugin/score)<a href="https://agentmods.dev/commands/austron24/kalshi-trader-plugin/score"><img src="https://agentmods.dev/badge/commands/austron24/kalshi-trader-plugin/score.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 | $0.00011 | $0.01436 |
| Opus 5 | $0.00005 | $0.00718 |
| Sonnet 5 | $0.00002 | $0.00287 |
| Haiku 4.5 | $0.00001 | $0.00144 |
Grade A, and why
score 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 5d 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 — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Event Scoring & Ranking
You are scoring all researched events to identify the top opportunities. Your job is to:
- Spawn parallel judge agents to score each event
- Collect all scores via bash
- Rank and return the top 10 opportunities
- Advise the user to take top events to a fresh session for /finalize
Phase 1: Identify Events to Score
List all events with research:
ls research/events/
Each folder is an event ticker that needs scoring.
Guard: If no events found:
No research found in `research/events/`. Run `/alpha` first to scan for opportunities and generate initial research.
Exit the command if no events exist.
Phase 2: Spawn Judge Agents
For each event, spawn a judge agent using the Task tool.
CRITICAL: Parallel Blocking Execution
To run agents in parallel (concurrent) but blocking (main agent waits for all to complete):
- Make ALL Task calls in a SINGLE message - This triggers parallel execution
- Do NOT use
run_in_background- Omitting this makes calls blocking - The main agent automatically waits for all agents to complete before continuing
For each agent:
- subagent_type: "judge"
- model: opus
- prompt: (see below)
Example prompt for each agent:
Score Kalshi event [EVENT_TICKER].
**CRITICAL: Read ALL files in research/events/[EVENT_TICKER]/ completely. No skimming.**
Your job:
1. Read every research file for this event completely
2. Score the opportunity from 0-100 based on:
- Edge Quality (0-40): How clear and realistic is the edge on the recommended bracket?
- Research Quality (0-30): How thorough and credible?
- Actionability (0-30): Is this tradeable? Did senior analyst recommend TRADE with a specific bracket?
3. Write score to: research/events/[EVENT_TICKER]/score.txt
**FORMAT IS CRITICAL:**
<SCORE>|<RECOMMENDED_TICKER>|<ONE_LINE_RATIONALE>
Example: `87|KXCPI-25DEC-T0.3|Strong edge on CPI, solid research, senior analyst recommends TRADE YES`
When done, confirm: files read, score assigned, score file path.
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.
- 5d ago First seen · 175 lines · 11 tokens per session scan A eb0382c87ac8
score is a command published in the GitHub repository austron24/kalshi-trader-plugin (12 stars, last pushed 8mo ago), licensed MIT. It adds 11 tokens to every session and 1,436 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 2026-08-30.
Other commands, from other repositories
data-activity
Access user trading activity, transaction history, and order events.
data-leaderboard
Access leaderboard data, trader rankings, competition stats, and top performer metrics.
data-positions
Query user positions, portfolio holdings, and calculate P&L metrics.
gamma-events
Events are high-level prediction questions (e.g., "Who will win the 2024 Presidential Election?"). Series are collections of related events (e.g., "Elections 2024").
gamma-markets
Access detailed market data, filter markets by various criteria, and build market discovery features.
gamma-search
Full-text search across markets and events, plus advanced discovery features.