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 skills/scrollmark/socialgpt-mcp/competitor-gap-analysisnpx skills add scrollmark/socialgpt-mcp --skill competitor-gap-analysisgit clone --depth 1 https://github.com/scrollmark/socialgpt-mcpWrote 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/skills/scrollmark/socialgpt-mcp/competitor-gap-analysis)<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>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 5.1 | $0.00144 | $0.01289 |
| Opus 5 | $0.00072 | $0.00645 |
| Sonnet 5 | $0.00029 | $0.00258 |
| Haiku 4.5 | $0.00014 | $0.00129 |
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.
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.
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
-
Confirm access. Make sure the SocialGPT MCP tools are connected. If
list_videosandlist_creator_videosaren't available, point the user to the connect page above and stop. -
Pull your own top content. Call the MCP tool:
list_videos(sort="top", limit=15, include_analysis=true)include_analysis=trueis what gives each video itscontent_themes— the script extracts gaps far more accurately when themes are present (it falls back to caption keywords if they're missing). -
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, pollget_analysis_status(job_id)until done, then calllist_creator_videos. -
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": <...>} ] }
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.
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.
- 6d ago First seen · 116 lines · 144 tokens per session scan A 12c7c0ac0b47
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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