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.
git clone --depth 1 https://github.com/skainguyen1412/social-media-research-skillWrote 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/commands/skainguyen1412/social-media-research-skill/quick)<a href="https://agentmods.dev/commands/skainguyen1412/social-media-research-skill/quick"><img src="https://agentmods.dev/badge/commands/skainguyen1412/social-media-research-skill/quick/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/skainguyen1412/social-media-research-skill/quick"><img src="https://agentmods.dev/badge/commands/skainguyen1412/social-media-research-skill/quick.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00018 | $0.00172 |
| Opus 5 | $0.00009 | $0.00086 |
| Sonnet 5 | $0.00004 | $0.00034 |
| Haiku 4.5 | $0.00002 | $0.00017 |
Grade A, and why
quick 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 11d 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.
What it actually says
-
Fetch data (Reddit only)
Delegate to the
social_media_fetchskill with: topic ="ARGUMENTS", depth =quick, source =reddit. This fetches Reddit data only and skips X for speed. Use/deep-researchfor deeper multi-source analysis. -
Read the raw data
Read
reddit_data.jsononly. Ignorex_data.jsoneven if it exists from a prior run. -
Provide a concise answer
Synthesize a 3–5 sentence answer directly from the Reddit data. Mention the community favorite, 1–2 alternatives, and a real user quote. Do NOT generate any classified files.
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.
- 11d ago First seen · 16 lines · 18 tokens per session scan A 7a863825094e
quick is a command published in the GitHub repository skainguyen1412/social-media-research-skill (57 stars, last pushed 6mo ago), licensed MIT. It adds 18 tokens to every session and 172 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
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spec-forge
Use when generating software specifications — full chain (Idea→Decompose→Tech Design + Feature Specs) or individual documents.
rclone_config_dump
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dd-init
Initialize product documentation structure in current directory.
dd-spec-test
Generate test spec (requires confirmed status).