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 fiber-ai/fiber-ai-plugin --skill enrich-github-handlesgit clone --depth 1 https://github.com/fiber-ai/fiber-ai-pluginWrote 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/fiber-ai/fiber-ai-plugin/enrich-github-handles)<a href="https://agentmods.dev/skills/fiber-ai/fiber-ai-plugin/enrich-github-handles"><img src="https://agentmods.dev/badge/skills/fiber-ai/fiber-ai-plugin/enrich-github-handles.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 5.1 | $0.00087 | $0.01921 |
| Opus 5 | $0.00044 | $0.00960 |
| Sonnet 5 | $0.00017 | $0.00384 |
| Haiku 4.5 | $0.00009 | $0.00192 |
Grade A, and why
enrich-github-handles 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 7d 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fiber AI: Enrich GitHub Handles
Developer-sourcing skill. Start from GitHub handles or profile URLs, resolve to LinkedIn, then optionally layer on email / phone / live profile enrichment. All GitHub resolution is async.
When to use
- User pastes a list of GitHub handles and wants LinkedIn URLs
- User is sourcing developers from OSS contributor lists, top-repos, or a CSV export
- User says "find LinkedIn for these GitHub users", "dev candidate enrichment", "OSS contributors to LinkedIn"
- User wants contact details for a list of engineers identified via GitHub
Do not use when
- User starts from LinkedIn URLs - use
/fiber:enrich-linkedin-csv - User wants to find engineers by role description (not GitHub) - use
/fiber:find-and-enrich-by-role - User wants an exportable audience of thousands of engineers - use
/fiber:build-recruiting-audience - User wants to write a pipeline - use
/fiber:sdk-tsor/fiber:sdk-py
Happy path
Route by what the user actually needs back. Both GitHub operations are async - expect to poll.
- Input is a GitHub handle / profile URL; user only wants the LinkedIn URL - call
githubToLinkedInTrigger, save the returned task id, then pollgithubToLinkedInPollingno more often than every 5 seconds until done. This is the cheapest path and returns just the matched LinkedIn URL. - Input is a GitHub handle / profile URL; user wants full person enrichment - call
githubLookupTrigger, save the returned task id, then pollgithubLookupPollno more often than every 5 seconds until done. This returns a resolved person record (LinkedIn, name, title, company, location). - Once a LinkedIn URL is resolved (path 1 or 2), hand off to the relevant downstream enrichment:
- Contact details (email / phone):
syncQuickContactRevealper row, orstartBatchContactDetails+pollBatchContactDetailsfor batches of 10-2000. - Freshest LinkedIn profile data:
profileLiveEnrich.
- Contact details (email / phone):
- Unresolved handles are expected - GitHub to LinkedIn match rates are not 100%. Skip gracefully and flag misses in the output table.
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.
- 7d ago First seen · 93 lines · 87 tokens per session scan A 34599be20f4d
enrich-github-handles is a skill published in the GitHub repository fiber-ai/fiber-ai-plugin (2 stars, last pushed 2mo ago), licensed MIT. It adds 87 tokens to every session and 1,921 once invoked, about $0.0004 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 2026-08-31.
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