research-gaps

research-gaps is a command for Claude Code from seite-sh/seite. It costs 0 tokens per session (429 once invoked), scanned A, a copy of research-gaps, MIT.

A command that compares your site's search rankings with seven competitors to find keywords they rank for while you do not.

In plain words
What is it for?
Use it to find content gaps, assess keyword volume, difficulty, and search intent, choose a suitable content type, and generate a dated Markdown report.
Why use it?
It shows which relevant search topics competitors cover and helps turn that information into prioritized content opportunities.

Command for Claude Code

Install

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.

agentmods
npx agentmods add commands/seite-sh/seite/research-gaps
Clone the repo
git clone --depth 1 https://github.com/seite-sh/seite

Made for: Claude Code.

Wrote 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.

agentmods badge for research-gaps

README.md
[![agentmods](https://agentmods.dev/badge/commands/seite-sh/seite/research-gaps.svg)](https://agentmods.dev/commands/seite-sh/seite/research-gaps)
Your own site
<a href="https://agentmods.dev/commands/seite-sh/seite/research-gaps"><img src="https://agentmods.dev/badge/commands/seite-sh/seite/research-gaps.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 429 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.00429
Opus 5 $0.00000 $0.00215
Sonnet 5 $0.00000 $0.00086
Haiku 4.5 $0.00000 $0.00043

Measured 5d ago against content hash aea63b3c0549, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

research-gaps 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.

Origin

This is a copy

100% identical to research-gaps — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

seite-sh/.claude/commands/research-gaps.md · 62 lines

What it actually says

Research Gaps Command

Identify content gaps where competitors rank but you don't.

Usage

/research-gaps

What This Command Does

Analyzes 7 competitors to find keywords they rank for (top 20) that you don't rank for at all:

  • Direct Competitors: Configured in config/competitors.json or passed as arguments
  • Content Competitors: Industry blogs and media sites in your niche

For each gap:

  • Filters out branded/irrelevant keywords
  • Scores opportunity based on volume, difficulty, and intent
  • Determines content type needed (listicle, how-to, guide)
  • Prioritizes by potential impact

Process

Execute the competitor gap analysis:

python3 research_competitor_gaps.py

This will:

  1. Fetch your current ranking keywords from GSC
  2. Analyze each competitor's top 20 ranking keywords
  3. Identify gaps (they rank, you don't)
  4. Enrich with search volume, difficulty, SERP features
  5. Score and prioritize opportunities
  6. Generate report: research/competitor-gaps-YYYY-MM-DD.md

Output

The report includes:

  • Top 20 content gap opportunities
  • Priority level (CRITICAL/HIGH/MEDIUM)
  • Competitor intel (who ranks, at what position)
  • Keyword metrics (volume, difficulty, CPC)
  • Search intent and content type needed
  • Specific action steps for each gap

Integration

After running /research-gaps:

  • Use /research-serp [keyword] to analyze what ranks
  • Use /write [keyword] to create content brief
  • Focus on CRITICAL/HIGH priority gaps first

Time & Cost

Time: 3-5 minutes API Cost: ~$1-3 (DataForSEO) - analyzes ~300-500 competitor keywords

When to Run

  • Monthly: Full competitive landscape review
  • When entering new topic: Find what's missing
  • Before content planning: Identify proven opportunities
Changes

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.

  1. 5d ago First seen · 62 lines · 0 tokens per session scan A aea63b3c0549

Subscribe to this mod's changes

research-gaps is a command published in the GitHub repository seite-sh/seite (20 stars, last pushed 20d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 429 tokens. A static security scan graded it A with 0 findings. It is 100% identical to research-gaps, differing in 0 lines, and is treated as a copy.