Gloss: Skill for Claude Code

.agents/skills/turbo-quant-gatekeeper/SKILL.md

turbo-quant-gatekeeper is a skill for Claude Code, Codex from RecursiveIntell/Gloss. It costs 29 tokens per session (170 once invoked), scanned A, original, AGPL-3.0.

A workflow for selecting and checking TurboQuant candidates in semantic memory, where stored information is searched by meaning, then exact matches are verified.

In plain words
What is it for?
Use it when working on TurboQuant search acceleration, exact reranking, vector files, fallback behavior, or operation records.
Why use it?
It helps keep fast approximate searches accurate by reranking results and recording what happened when vector data is created or used.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing. Also seen: installed under .agents/ (shared by several agents).

This is RecursiveIntell/Gloss's own configuration. It tells Claude Code and Codex how to work on Gloss itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything Gloss configures →

Reuse

Borrowing it

Nothing to install: this file belongs to RecursiveIntell/Gloss. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/RecursiveIntell/Gloss/master/.agents/skills/turbo-quant-gatekeeper/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/RecursiveIntell/Gloss

Made for: Claude Code, Codex.

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 turbo-quant-gatekeeper

README.md
[![agentmods](https://agentmods.dev/badge/skills/recursiveintell/gloss/turbo-quant-gatekeeper/github.svg)](https://agentmods.dev/skills/recursiveintell/gloss/turbo-quant-gatekeeper)
Your own site
<a href="https://agentmods.dev/skills/recursiveintell/gloss/turbo-quant-gatekeeper"><img src="https://agentmods.dev/badge/skills/recursiveintell/gloss/turbo-quant-gatekeeper/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 turbo-quant-gatekeeper

Your own site · 80×15
<a href="https://agentmods.dev/skills/recursiveintell/gloss/turbo-quant-gatekeeper"><img src="https://agentmods.dev/badge/skills/recursiveintell/gloss/turbo-quant-gatekeeper.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 170 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 unknown 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 $0.00029 $0.00170
Opus 5.5 $0.00012 $0.00068
Sonnet 5.5 $0.00006 $0.00034
Haiku 4.5 $0.00003 $0.00017

Measured 2mo ago against content hash bbb951a55e1a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

turbo-quant-gatekeeper 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 2mo 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.

.agents/skills/turbo-quant-gatekeeper/SKILL.md · 25 lines

The source is not reproduced here

Licensed AGPL-3.0

The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

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. 2mo ago First seen · 25 lines · 29 tokens per session scan A bbb951a55e1a

Subscribe to this mod's changes

turbo-quant-gatekeeper is a skill published in the GitHub repository RecursiveIntell/Gloss (46 stars, last pushed 2d ago), licensed AGPL-3.0. It adds 29 tokens to every session and 170 once invoked, about $0.0001 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 2026-08-30.

Related

Other skills, from other repositories

browserwing-admin

Manage and operate BrowserWing — an intelligent browser automation platform. Install dependencies, configure LLM, create/manage/execute automation scripts, use AI-driven exploration to generate scripts, browse the script marketplace, and troubleshoot issues.

MemTensor/MemOS · 47 tokens

context-window-engineer

Expert guide for engineering and optimizing ultra-large context windows (2M+ tokens) across Gemini 4 Pro, Claude 5.5, and GPT Astra 6 — context partitioning, retrieval-augmented context injection, sliding window strategies, and cost-aware token budgeting / Panduan ahli rekayasa dan optimasi context window ultra-besar…

roedyrustam/vibes-plug · 124 tokens

gno

Search local documents, files, notes, and knowledge bases. Index directories, search with BM25/vector/hybrid, get AI answers with citations. Use when user wants to search files, find documents, query notes, look up information in local folders, index a directory, set up document search, build a knowledge base, needs…

gmickel/gno · 86 tokens

karpathy-llm-wiki

Use when building or maintaining a personal LLM-powered knowledge base. Triggers: ingesting sources into a wiki, querying wiki knowledge, linting wiki quality, 'add to wiki', 'what do I know about', or any mention of 'LLM wiki' or 'Karpathy wiki'.

Astro-Han/karpathy-llm-wiki · 67 tokens

local-embedding

Run embedding on-device with ONNX Runtime. Build from source, model selection, offline mode. Use when setting up local embedding without an API key.

matrixorigin/memoria · 34 tokens

dify

Use when self-hosting an LLM app platform with visual orchestration — docker compose up in dify/docker, knowledge bases with hybrid retrieval + rerank, Chatflow/Workflow nodes (Knowledge Retrieval, Code, HTTP Request, Iteration), custom tools from OpenAPI schema, /v1/chat-messages and /v1/workflows/run API keys; also…

znlgis/opengis-skills · 115 tokens