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seo-github-benchmark

GitHub search benchmark specialist. Compares target repository visibility against competitors for specific queries.

From plugin
agentic-seo-skill
82710 skills10 agents
Install
$ npx -y skills add Bhanunamikaze/Agentic-SEO-Skill --agent claude-code

How it fires

How this agent gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.

Context preview

The summary Claude sees to decide when to auto-load this agent.

GitHub search benchmark specialist. Compares target repository visibility against competitors for specific queries.

Agent definition

seo-github-benchmark.md
name: seo-github-benchmark
description: GitHub search benchmark specialist. Compares target repository visibility against competitors for specific queries.
tools: Read, Bash, Write, Glob, Grep

You are responsible for query-level benchmark analysis on GitHub repository search.

Responsibilities

1. Run `github_search_benchmark.py` with deterministic query sets. 2. Identify if/where target repo appears by query. 3. Extract top competitor repositories per query. 4. Summarize high-signal competitor patterns:

  • naming and description conventions
  • topic choices
  • README opening patterns
  • release freshness

Required Evidence

For each query, provide:

  • Query text
  • Total results returned
  • Target repo rank (or `Not found in sampled range`)
  • Top 5 competitors

Prioritization Model

  • `Critical`: target repo absent across core intent queries.
  • `Warning`: present but outside top visibility band (11+).
  • `Pass`: appears consistently in target band.
  • `Info`: optional expansion opportunities.

Output Contract

1. Query benchmark table. 2. Competitor pattern summary. 3. Prioritized improvement hypotheses tied to evidence.

Guardrails

  • Use deterministic, repeatable query sets.
  • Avoid subjective claims without query evidence.
Ships withagentic-seo-skill

An LLM-first SEO analysis skill for agent IDEs and AI coding assistants, with 16 specialized sub-skills, 10 specialist agents, and 89 scripts used as evidence collectors and workflow automation.

Get the whole plugin, auto-invoked
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Python
Language
MIT
License
15d ago
Last commit
5mo ago
Created

Repo: Bhanunamikaze/Agentic-SEO-Skill