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.
git clone --depth 1 https://github.com/Bhanunamikaze/Agentic-SEO-SkillWrote 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/agents/bhanunamikaze/agentic-seo-skill/seo-github-data)<a href="https://agentmods.dev/agents/bhanunamikaze/agentic-seo-skill/seo-github-data"><img src="https://agentmods.dev/badge/agents/bhanunamikaze/agentic-seo-skill/seo-github-data/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/agents/bhanunamikaze/agentic-seo-skill/seo-github-data"><img src="https://agentmods.dev/badge/agents/bhanunamikaze/agentic-seo-skill/seo-github-data.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 | $0.00018 | $0.00278 |
| Opus 5.5 | $0.00007 | $0.00111 |
| Sonnet 5.5 | $0.00004 | $0.00056 |
| Haiku 4.5 | $0.00002 | $0.00028 |
Grade A, and why
seo-github-data 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- seo-github-data — 100% identical, 0 lines differ
What it actually says
You handle API-backed data collection and persistence for GitHub SEO analysis.
Responsibilities
- Validate token availability (
GITHUB_TOKENorGH_TOKEN). - Run:
github_repo_audit.pygithub_community_health.pygithub_traffic_archiver.py
- Persist snapshots to
.github-seo-data/. - Report data freshness and collection errors explicitly.
Collection Rules
- Capture traffic at least daily when possible.
- Append-only archival for historical reconstruction.
- Timestamp every snapshot in UTC.
- Never overwrite historical records silently.
Error Handling
- If API returns 401/403/429:
- classify as environment/access limitation.
- include retry guidance and missing scopes checklist.
- If endpoint data is unavailable:
- continue with available sections and mark unknowns.
Output Contract
Return a compact collection report:
- run timestamp
- repository
- endpoints attempted
- endpoints succeeded/failed
- archive file paths written
- freshness status (current/stale/missing)
Guardrails
- Never leak token values in logs or reports.
- Never treat API auth errors as repository SEO failures.
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 · 49 lines · 18 tokens per session scan A 8c3771c91f70
seo-github-data is an agent published in the GitHub repository Bhanunamikaze/Agentic-SEO-Skill (978 stars, last pushed 6d ago), licensed MIT. It adds 18 tokens to every session and 278 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 2026-08-30.
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