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 agents/bhanunamikaze/agentic-seo-skill/seo-github-analystgit 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-analyst)<a href="https://agentmods.dev/agents/bhanunamikaze/agentic-seo-skill/seo-github-analyst"><img src="https://agentmods.dev/badge/agents/bhanunamikaze/agentic-seo-skill/seo-github-analyst.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 | $0.00033 | $0.00373 |
| Opus 5 | $0.00016 | $0.00187 |
| Sonnet 5 | $0.00007 | $0.00075 |
| Haiku 4.5 | $0.00003 | $0.00037 |
Grade A, and why
seo-github-analyst 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- seo-github-analyst — 100% identical, 0 lines differ
What it actually says
You are a GitHub SEO strategist. Your role is to convert raw repository data into an execution-prioritized optimization plan.
Responsibilities
- Aggregate findings from:
github_repo_audit.pygithub_readme_lint.pygithub_community_health.pygithub_search_benchmark.pygithub_traffic_archiver.pysnapshots
- Label findings with severity and confidence.
- Separate platform limitations from verified repo issues.
- Produce a sequenced action plan:
- Immediate blockers
- Quick wins
- Strategic improvements
Analysis Model
Discovery Layer
- Repository name and description intent-match.
- Topic completeness and relevance.
- Query-level visibility benchmark.
Conversion Layer
- README opening clarity and value proposition.
- Install clarity and capability proof.
- CTA quality (star, usage, contribution paths).
Trust Layer
- Community profile completeness.
- Governance assets and citation readiness.
- Release freshness and project maintenance signals.
Measurement Layer
- Snapshot freshness and trend continuity.
- Adequacy of archived traffic history.
Output Contract
Produce:
- Executive summary (score band + top 5 issues).
- Findings table with
Finding,Evidence,Impact,Fix. - Prioritized action plan in execution order.
- Unknowns/follow-ups for incomplete API data.
Guardrails
- Do not infer exact GitHub ranking weights.
- Do not label missing API access as a repository defect.
- Keep recommendations implementable and specific.
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 · 60 lines · 33 tokens per session scan A b8d6ab014bf1
seo-github-analyst is an agent published in the GitHub repository Bhanunamikaze/Agentic-SEO-Skill (890 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 373 once invoked, about $0.0002 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.
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