gammarips-exit-lab

gammarips-exit-lab is a skill for Claude Code from DevDizzle/gammarips-mcp. It costs 95 tokens per session (855 once invoked), scanned A, original, MIT.

A workflow for testing an options exit rule against the realized history of GammaRips pool contracts. An exit rule says when to take profit, stop a loss, or stop holding a position.

In plain words
What is it for?
Use it to compare profit targets, stop losses, trailing stops, and holding windows using touch probabilities and maximum favorable or adverse movement.
Why use it?
It replaces guesswork about targets, stops, and holding periods with historical results, including how often levels were reached and how much prices moved for or against the trade.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the gammarips plugin — 4 skills shipped together

Good fit Use it to compare profit targets, stop losses, trailing stops, and holding windows using touch probabilities and maximum favorable or adverse movement.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/devdizzle/gammarips-mcp/gammarips-exit-lab
Install

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.

Any agent
npx skills add DevDizzle/gammarips-mcp --skill gammarips-exit-lab
Clone the repo
git clone --depth 1 https://github.com/DevDizzle/gammarips-mcp

Made for: Claude Code.

Or install gammarips, the plugin that ships this one along with the rest of its 4 skills.

Wrote 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.

agentmods badge for gammarips-exit-lab

README.md
[![agentmods](https://agentmods.dev/badge/skills/devdizzle/gammarips-mcp/gammarips-exit-lab/github.svg)](https://agentmods.dev/skills/devdizzle/gammarips-mcp/gammarips-exit-lab)
Your own site
<a href="https://agentmods.dev/skills/devdizzle/gammarips-mcp/gammarips-exit-lab"><img src="https://agentmods.dev/badge/skills/devdizzle/gammarips-mcp/gammarips-exit-lab/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.

agentmods 80×15 button for gammarips-exit-lab

Your own site · 80×15
<a href="https://agentmods.dev/skills/devdizzle/gammarips-mcp/gammarips-exit-lab"><img src="https://agentmods.dev/badge/skills/devdizzle/gammarips-mcp/gammarips-exit-lab.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 95 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 855 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00095 $0.00855
Opus 5.5 $0.00038 $0.00342
Sonnet 5.5 $0.00019 $0.00171
Haiku 4.5 $0.00010 $0.00085

Measured 1mo ago against content hash 6d415ab568b6, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

gammarips-exit-lab 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 1mo 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.

plugins/claude/skills/gammarips-exit-lab/SKILL.md · 61 lines

How it starts

The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GammaRips exit lab

Help the user test an exit rule against history. The tools score the rule. The user decides. These tools need GammaRips Pro. If a call returns subscription_required, give the user the tool's message as it is written, offer get_playbook(name="exit-lab") (it is on every plan), and stop.

Steps

  1. Get the rule. Ask for, or confirm: target %, stop %, horizon (same_day or 3d), and optionally a delta band and a date range. For a trailing stop, get trail_pct and activation_pct.
  2. Start from the two exact labels. Call query_outcomes(view="summary", horizon="same_day") (+40% / -30%, flat by 15:45 ET) and query_outcomes(view="summary", horizon="3d") (+80% / -60%, 3 trading days). These are the only exactly simulated brackets, with real fills and slippage. They are the reference points.
  3. Touch probabilities. Call query_outcomes(view="harvest", targets=[...], stops=[...]) with the user's levels. Report the probability of touching each level, with its confidence interval, and which day the peak landed on.
  4. The surface. Call query_outcomes(view="surface", aggregate_only=True, days=<N>) for MFE and MAE quantiles over the same period.
  5. Score the rule. Call query_outcomes(view="exit_rule", rule="bracket", target_pct=<T>, stop_pct=<S>), or rule="trailing" with trail_pct and activation_pct. Its default window is 3 trading days. Report ev_bounds, not one EV number, and report heuristic_share.
  6. Slice, then check stability. If the user wants more, repeat steps 3 to 5 inside a feature slice (for example a delta band with delta_min and delta_max) and across two or more date ranges. Trust a result only if it holds in each range.

How to report

For every number, give its horizon, its row count (N), and its date range. Then give these caveats:

  • Never mix horizons. Same-day and 3-day numbers can point in opposite directions. Compare a rule only with numbers from the same horizon.
  • Touches are not fills. A touch is a bar high or low. Surface and exit-rule estimates apply no slippage. Real stop fills land past the stop level, and more so on thin contracts. Expect real results below the estimate.
  • Heuristic rows. When both levels were crossed inside the window, the order is estimated. If heuristic_share is large, say that the score is uncertain.
  • Excluded rows. Rows with no label (illiquid at the entry anchor) are excluded, and that group is not random. Quote the exclusion counts from the response meta.
  • History is not a promise. A score on history is a research result for that rule on past contracts, not an expected return for the next trade.
  • Paper-traded research data. Educational only. Not investment advice.

Read the full file on GitHub · 61 lines

Changes

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.

  1. 1mo ago First seen · 61 lines · 95 tokens per session scan A 6d415ab568b6

Subscribe to this mod's changes

gammarips-exit-lab is a skill published in the GitHub repository DevDizzle/gammarips-mcp (0 stars, last pushed 1mo ago), licensed MIT. It adds 95 tokens to every session and 855 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-10-03.

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