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 jmagly/aiwg --skill customize-contribute-backgit clone --depth 1 https://github.com/jmagly/aiwgWrote 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/jmagly/aiwg/customize-contribute-back)<a href="https://agentmods.dev/skills/jmagly/aiwg/customize-contribute-back"><img src="https://agentmods.dev/badge/skills/jmagly/aiwg/customize-contribute-back/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/jmagly/aiwg/customize-contribute-back"><img src="https://agentmods.dev/badge/skills/jmagly/aiwg/customize-contribute-back.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector 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 | $0.00029 | $0.01119 |
| Opus 5.5 | $0.00012 | $0.00448 |
| Sonnet 5.5 | $0.00006 | $0.00224 |
| Haiku 4.5 | $0.00003 | $0.00112 |
Grade A, and why
customize-contribute-back 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.
How it starts
The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Customize Contribute Back
You help users contribute a customization from their fork back to the upstream AIWG repo. You first assess whether the customization is generally useful (not just personal), then create a feature branch, commit, and open a PR.
Triggers
- "PR this back to AIWG"
- "contribute this upstream"
- "submit this agent to the main repo"
- "open a PR to AIWG"
- "share this with the AIWG project"
- "could this be useful for everyone?"
Trigger Patterns Reference
| Pattern | Example | Action |
|---|---|---|
| Explicit PR | "PR this back to AIWG" | Assess → branch → PR |
| Contribution question | "could this be useful for everyone?" | Assess only, ask to proceed |
| Submit | "submit this skill upstream" | Assess → branch → PR |
Behavior
When triggered:
-
Identify what to contribute — ask if not clear:
"Which customization would you like to contribute? (e.g., the domain-specialist agent, the my-conventions rule)"
-
Assess for general applicability:
- Review the file(s) in question
- Ask: is this useful to anyone installing AIWG, or is it specific to this user's context?
- Personal signals (do NOT contribute): references to the user's name, team, specific internal tools, personal preferences ("always call me X"), org-specific vocabulary
- General signals (good candidate): adds new capability, improves an existing agent/skill for a common use case, fixes a gap in the framework
If personal: decline gracefully:
"This looks specific to you — it references [X]. That's perfect as a private customization but wouldn't be a fit for the main repo. Keep it in your fork."
If general: confirm with user before proceeding:
"This looks generally useful. Want me to open a PR to jmagly/aiwg?"
-
Create feature branch:
git -C <edgePath> checkout -b feat/contribute-<name> git -C <edgePath> add <file(s)> git -C <edgePath> commit -m "<conventional-commit-message>" git -C <edgePath> push origin feat/contribute-<name>
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 · 127 lines · 29 tokens per session scan A 8f4ea671170e
customize-contribute-back is a skill published in the GitHub repository jmagly/aiwg (225 stars, last pushed today), licensed MIT. It adds 29 tokens to every session and 1,119 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 2026-09-03.
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