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 skills/rubenmarcus/ralph-starter/ralph-linearnpx skills add rubenmarcus/ralph-starter --skill ralph-lineargit clone --depth 1 https://github.com/rubenmarcus/ralph-starterWrote 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/rubenmarcus/ralph-starter/ralph-linear)<a href="https://agentmods.dev/skills/rubenmarcus/ralph-starter/ralph-linear"><img src="https://agentmods.dev/badge/skills/rubenmarcus/ralph-starter/ralph-linear.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 | $0.00222 |
| Opus 5 | $0.00005 | $0.00111 |
| Sonnet 5 | $0.00002 | $0.00044 |
| Haiku 4.5 | $0.00001 | $0.00022 |
Grade A, and why
ralph-linear 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.
What it actually says
Fetch specs from Linear tickets and run an autonomous coding loop to implement them.
-
Use
ralph_fetch_specwithsource: "linear"to preview the ticket:identifier: project or team name- Use
projectandlabelto filter tickets
-
Use
ralph_runto build from the ticket:- Set
from: "linear"and provideproject(team/project name) - Optionally filter with
label - Set
auto: true,commit: true,validate: truefor full automation
- Set
-
Use
ralph_taskto manage Linear tickets directly:action: "list"withsource: "linear"to see ticketsaction: "create"to create new ticketsaction: "update"/action: "close"with the ticket ID (e.g., "RAL-42")
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 · 21 lines · 11 tokens per session scan A f2cfd3782a24
ralph-linear is a skill published in the GitHub repository rubenmarcus/ralph-starter (106 stars, last pushed 1mo ago), licensed MIT. It adds 11 tokens to every session and 222 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 skills, from other repositories
develop
Project conventions and recurring gotchas for implementer agents working on agent-orchestrator. Use before committing any change in orchestrator/, tests/, or docs/.
review
Review checklist for reviewer agents on agent-orchestrator PRs. Use when evaluating a developer-produced branch before approval or change-requests.
gh-stars-classifier
Classify the user's GitHub starred repositories into semantic categories and add them to GitHub Lists. Use when the user asks to organize, classify, categorize, or clean up their GitHub stars.
create-pr
Create GitHub pull requests with Conventional Commits-formatted titles and structured PR bodies. Use when creating PRs, submitting changes for review, or when the user says /pr or asks to create a pull request.
github-recon
Scan Git repositories, GitHub organizations, and source code for leaked secrets, API keys, credentials, and sensitive data. Use when analyzing source code security, when checking for credential exposure, or when the user mentions secret scanning or credential leaks.
pr-writer
ALWAYS use this skill when creating or updating pull requests — never create or edit a PR directly without it. Follows Sentry conventions for PR titles, descriptions, and issue references. Trigger on any create PR, open PR, submit PR, make PR,...