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 skills add jackjin1997/ClawForge --skill language-learninggit clone --depth 1 https://github.com/jackjin1997/ClawForgeWrote 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/skills/jackjin1997/clawforge/language-learning)<a href="https://agentmods.dev/skills/jackjin1997/clawforge/language-learning"><img src="https://agentmods.dev/badge/skills/jackjin1997/clawforge/language-learning/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/skills/jackjin1997/clawforge/language-learning"><img src="https://agentmods.dev/badge/skills/jackjin1997/clawforge/language-learning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
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 | $0.00130 | $0.02607 |
| Opus 5.5 | $0.00052 | $0.01043 |
| Sonnet 5.5 | $0.00026 | $0.00521 |
| Haiku 4.5 | $0.00013 | $0.00261 |
Grade A, and why
language-learning 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 1mo ago First seen · 298 lines · 130 tokens per session scan A bb9b988f3423
language-learning is a skill published in the GitHub repository jackjin1997/ClawForge (13 stars, last pushed 4mo ago), with no licence file. It adds 130 tokens to every session and 2,607 once invoked, about $0.0005 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.
Other skills, from other repositories
deep-student-cloud-sync-e2e
Run real, UI-driven Deep Student cloud sync E2E tests. Use when Codex needs to validate WebDAV/cloud sync, backup, restore, credentials, conflict behavior, multi-device synchronization, or sync regressions through real Tauri UI operations followed by SQLite/WebDAV/log verification.
deep-student-tauri-lab
Manage Deep Student Tauri desktop test instances through the repo-local tauri-lab CLI. Use when Codex needs to create, start, stop, restart, lease, inspect, or clean up one or many Deep Student Tauri app windows for Computer Use testing, parallel subagents, cloud sync simulations, or local E2E debugging.
card-coordinator
A workflow coordinator for creating and checking a set of study cards through several specialised agents. It passes work from content selection to generation, quality checking, and corrections.
card-qa-checklist
A checklist of rules for checking catalogue cards, maintained for a card-quality review sub-agent. The input does not explain the individual checks.
card-outline
A method for turning learning material into a structured outline for study cards. It identifies the smallest useful pieces of knowledge, chooses card types, sets the right amount of detail, and orders priorities.
study
Start or resume a strict-tutor learning session on a topic. Builds an ordered concept path, gathers real resources, and teaches ONE concept at a time with checkpoints. Use when the user says "study X", "teach me X", "I want to learn X", or "/study ".