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 tobihagemann/turbo --skill contributegit clone --depth 1 https://github.com/tobihagemann/turboWrote 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/tobihagemann/turbo/contribute)<a href="https://agentmods.dev/skills/tobihagemann/turbo/contribute"><img src="https://agentmods.dev/badge/skills/tobihagemann/turbo/contribute/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/tobihagemann/turbo/contribute"><img src="https://agentmods.dev/badge/skills/tobihagemann/turbo/contribute.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00043 | $0.00735 |
| Opus 5.5 | $0.00017 | $0.00294 |
| Sonnet 5.5 | $0.00009 | $0.00147 |
| Haiku 4.5 | $0.00004 | $0.00073 |
Grade A, and why
contribute 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 3d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Contribute
Propose an improvement to a turbo skill as an issue on tobihagemann/turbo.
Step 1: Identify the Proposed Change
Take the proposed changes from the lessons passed in: each names the turbo skill it targets, the change, and the session evidence behind it. Without them, take the proposed changes from conversation context. When neither describes a change to a turbo skill, tell the user there is nothing to contribute and stop.
Read each target skill's current text upstream, so each change is stated against the file as it stands on main:
gh api repos/tobihagemann/turbo/contents/claude/skills/<name>/SKILL.md -H 'Accept: application/vnd.github.raw'
Leave out a change whose target skill does not exist upstream, and tell the user.
Present the changes in a summary table:
| # | Skill | Change Summary |
|---|-------|----------------|
| 1 | /evaluate-findings | Added handling for security-default findings |
| 2 | /self-improve | Clarified routing for trusted reviewer feedback |
Use AskUserQuestion to confirm which changes to propose.
Step 2: Craft Contribution Context
For each change, construct a "why" explanation. The goal: the turbo maintainer should understand what happened and why the existing instructions were insufficient, without learning anything about the contributor's project.
Use this template:
During [general workflow description], the skill's instructions [what was missing or wrong]. This caused [what happened]. The change [what it does] so that [benefit].
Example:
During a code review session, the evaluate-findings skill encountered a finding with
security-defaultseverity. The existing instructions only handledcritical,high,medium, andlowseverities, causing the finding to be silently dropped. The change addssecurity-defaultto the severity handling table so these findings are properly triaged.
The maintainer implements the change, so state it concretely alongside the "why": the file path under claude/skills/<name>/, the step or section it belongs in, and the exact replacement text or a diff.
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.
- 3d ago First seen · 69 lines · 43 tokens per session scan A 8e7f9b65a883
contribute is a skill published in the GitHub repository tobihagemann/turbo (420 stars, last pushed today), licensed MIT. It adds 43 tokens to every session and 735 once invoked, about $0.0002 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 2026-11-09.
contribute compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| contributetobihagemann/turbo | Skill | 420 | today | MIT | A | 43 | Claude Code |
| offensive-c2-frameworksSnailSploit/Claude-Red | Skill | 11k | yesterday | MIT | A | 250 | Claude Code, Codex |
| offensive-crypto-attacksSnailSploit/Claude-Red | Skill | 11k | yesterday | MIT | A | 261 | Claude Code, Codex |
| offensive-parameter-pollutionSnailSploit/Claude-Red | Skill | 11k | yesterday | MIT | A | 0 | Claude Code, Codex |
| offensive-z-waveSnailSploit/Claude-Red | Skill | 11k | yesterday | MIT | A | 113 | Claude Code, Codex |
| fiscalisteromainsimon/paperasse | Skill | 2.6k | today | MIT | A | 306 | Claude Code |
| comptableromainsimon/paperasse | Skill | 2.6k | today | MIT | A | 248 | Claude Code |