competitor-gap-analysis

competitor-gap-analysis is a skill for Claude Code, Codex from scrollmark/socialgpt-mcp. It costs 144 tokens per session (1,289 once invoked), scanned A, original, MIT.

A workflow for comparing a creator's best social-media content with the best content from one to three named competitors. It uses SocialGPT data to identify topics or approaches the creator is missing.

In plain words
What is it for?
Use it to find content gaps, compare a creator with rivals, identify topics competitors cover, and produce a shareable gap-analysis report. SocialGPT tools must be connected to supply the data.
Why use it?
It replaces guesswork and manually scrolling through competitors' feeds with a side-by-side comparison of content themes.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

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 skills/scrollmark/socialgpt-mcp/competitor-gap-analysis
Any agent
npx skills add scrollmark/socialgpt-mcp --skill competitor-gap-analysis
Clone the repo
git clone --depth 1 https://github.com/scrollmark/socialgpt-mcp

Made for: Claude Code, Codex.

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 competitor-gap-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/scrollmark/socialgpt-mcp/competitor-gap-analysis.svg)](https://agentmods.dev/skills/scrollmark/socialgpt-mcp/competitor-gap-analysis)
Your own site
<a href="https://agentmods.dev/skills/scrollmark/socialgpt-mcp/competitor-gap-analysis"><img src="https://agentmods.dev/badge/skills/scrollmark/socialgpt-mcp/competitor-gap-analysis.svg" alt="Measured on agentmods" height="20"></a>
Per session 144 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,289 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found 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 5.1 $0.00144 $0.01289
Opus 5 $0.00072 $0.00645
Sonnet 5 $0.00029 $0.00258
Haiku 4.5 $0.00014 $0.00129

Measured 6d ago against content hash 12c7c0ac0b47, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

competitor-gap-analysis 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 6d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/analyze.py, scripts/sgpt_lib.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/competitor-gap-analysis/SKILL.md · 116 lines

How it starts

The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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": <...>}
      ]
    }
    

Read the full file on GitHub · 116 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 6d ago First seen · 116 lines · 144 tokens per session scan A 12c7c0ac0b47

Subscribe to this mod's changes

competitor-gap-analysis is a skill published in the GitHub repository scrollmark/socialgpt-mcp (10 stars, last pushed 1mo ago), licensed MIT. It adds 144 tokens to every session and 1,289 once invoked, about $0.0007 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 2026-08-31.

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