competitor-gap-analysis

name	competitor-gap-analysis
description	Compare a creator's top content against 1-3 named competitors to find where the competitors win and the creator is silent. Use when a SocialGPT user asks "what are my competitors doing that I'm not", "find my content gaps", "what should I steal from @rival", "where am I getting beaten", or wants a side-by-side read of their catalog vs. a competitor's. Pulls the user's top videos and each competitor's top videos via the SocialGPT MCP, extracts themes (from analysis or caption keywords), and writes a visual report of content gaps, owned territory, format gaps, and three angles to test. Requires the SocialGPT MCP server to be connected.
license	MIT

Competitor Gap Analysis

Put a creator's best content next to 1-3 competitors' best content and answer "what are they winning on that I'm not even showing up for?" — instead of scrolling rivals' feeds and guessing, you measure the overlap.

This skill pairs with the SocialGPT MCP server (https://mcp.gpt.social/mcp). The MCP provides the data; this skill provides the gap analysis and a shareable report. If the SocialGPT tools below aren't available, the user needs to connect the MCP first: https://gpt.social/integrations/mcp

When to use

Trigger on requests like: "what are my competitors doing that I'm not?", "find my content gaps", "compare me to @rival", "what should I steal from them?", "where am I getting beaten?", "what topics do they own?"

Workflow

1. Confirm access. Make sure the SocialGPT MCP tools are connected. If list_videos and list_creator_videos aren't available, point the user to the connect page above and stop.

2. Pull your own top content. Call the MCP tool:

   list_videos(sort="top", limit=15, include_analysis=true)
   

   include_analysis=true is what gives each video its content_themes — the script extracts gaps far more accurately when themes are present (it falls back to caption keywords if they're missing).

3. Pull each competitor's top content. For each of the 1-3 competitors the user named, call:

   list_creator_videos(platform="<tiktok|instagram|youtube>", username="<handle>", sort="top", limit=15, include_analysis=true)
   

   If a competitor isn't in the library yet, run analyze_creator(platform, username) first, poll get_analysis_status(job_id) until done, then call list_creator_videos.

4. Assemble gap.json. Write a single JSON file in the working directory shaped like this (the raw tool envelopes are fine — the script unwraps them):

   {
     "me": <the list_videos result, envelope or bare list>,
     "competitors": [
       {"name": "@rival_one", "videos": <that creator's list_creator_videos result>},
       {"name": "@rival_two", "videos": <...>}
     ]
   }
   

5. Run the analysis (it has no third-party dependencies):

   python scripts/analyze.py gap.json
   

   The script reads gap.json, builds the gap matrix, prints a Markdown summary to stdout, and writes competitor-gap-report.html.

6. Relay the result. Present the Markdown summary the script printed, then offer the user the generated competitor-gap-report.html to download / open (on Claude.ai it appears as a downloadable file).

What the script does

It splits the videos into cohorts — you, each named competitor, and a pooled competitors set — and for each cohort reads a theme distribution plus median views, engagement rate, duration, and sequel/series rate.

• Themes come from each video's analysis content_themes. If themes are largely missing (e.g. include_analysis was false), it falls back to keyword topics mined from titles and captions (lowercased, tokenized, stopwords dropped, top terms treated as pseudo-themes).
• Content gaps — themes competitors cover heavily (≥20% of their videos, and ≥2 competitor videos) where you have ~zero coverage.
• Owned territory — themes you cover (≥2 of your videos) that competitors barely touch.
• Format gaps — a Me vs. Competitors (pooled) table on median duration, sequel rate, median engagement, and median views, with the direction of each gap called out.
• Three content angles to test, grounded in the biggest gaps.

See references/methodology.md for how themes, coverage shares, and gaps are computed, plus the caveats.

Notes

• Needs a real competitor set. It requires at least one competitor with ≥3 videos. With fewer it tells you what to pull rather than inventing gaps.
• Themes beat keywords. Always prefer include_analysis=true. Keyword fallback finds topic words, but analysis themes are cleaner and the gaps are sharper.
• Gaps are leads, not verdicts. A gap means a competitor is getting reach on a topic you're absent from — it's the best thing to test next, not proof it'll work for your audience. The report says this explicitly.
• Re-runnable. Suggest re-running as you ship against the gaps; the owned/gap split shifts as both catalogs grow.
• Part of a larger loop. This is the research stage of the going-viral strategy loop — the gaps it finds feed straight into data-driven ideation.