A command for finding fast-growing topics and themes in social-media data. It can use Reddit or X data and produces classified results with engagement, sentiment, and popular posts.

Use it for weekly topic discovery or to investigate a specific subject and identify related posts and reactions.

It removes the need to inspect large amounts of social-media data manually when looking for emerging subjects.

discovery — Command for Claude Code by skainguyen1412

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.

Clone the repo

git clone --depth 1 https://github.com/skainguyen1412/social-media-research-skill

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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/skainguyen1412/social-media-research-skill/discovery/github.svg)](https://agentmods.dev/commands/skainguyen1412/social-media-research-skill/discovery)

Your own site

<a href="https://agentmods.dev/commands/skainguyen1412/social-media-research-skill/discovery"><img src="https://agentmods.dev/badge/commands/skainguyen1412/social-media-research-skill/discovery/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.

Your own site · 80×15

<a href="https://agentmods.dev/commands/skainguyen1412/social-media-research-skill/discovery"><img src="https://agentmods.dev/badge/commands/skainguyen1412/social-media-research-skill/discovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 11 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 169 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00011	$0.00169
Opus 5.5	$0.00004	$0.00068
Sonnet 5.5	$0.00002	$0.00034
Haiku 4.5	$0.00001	$0.00017

Measured 2mo ago against content hash d432ed529433, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

discovery 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 2mo 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.

templates/base/commands/discovery.md · 20 lines

What it actually says

This command produces a discovery analysis. It follows the orchestrated pipeline with discovery as the target.

Ensure raw data exists
Check if reddit_data.json or x_data.json exists. If missing or stale, delegate to the social_media_fetch skill to fetch data with --mode=discovery:
- Broad weekly feed: topic = DISCOVERY_WEEKLY
- Topic-focused: topic = user's query
Run analysis

Read the social_media_discovery skill instructions and follow them to generate classified_discovery.json.
Present results

Display discovered topics with engagement scores, sentiment, and top posts from classified_discovery.json.

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.

2mo ago First seen · 20 lines · 11 tokens per session scan A d432ed529433

Subscribe to this mod's changes

discovery is a command published in the GitHub repository skainguyen1412/social-media-research-skill (62 stars, last pushed 8mo ago), licensed MIT. It adds 11 tokens to every session and 169 once invoked, about $0.0000 per session on Opus 5.5. 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.

Analytics and metrics Marketing and SEO ai skills

discovery next to 6 commands from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
discoveryskainguyen1412/social-media-research-skill	Command	62	8mo ago	MIT	A	11	Claude Code
cancel-ralphanthropics/claude-plugins-official	Command	46k	yesterday	Apache-2.0	A	4	Claude Code
constraintsvinvcn/addyosmani-agent-skills-zh	Command	46	17d ago	MIT	A	20	Claude Code
spec-forgetercel/spec-forge	Command	10	1mo ago	MIT	A	33	Claude Code
releasekomunite/kalfa	Command	246	6mo ago	MIT	A	13	Claude Code
rclone_config_dumpchaunsin/agent-skills	Command	2	7d ago	Apache-2.0	A	7	Claude Code
dd-initmkhrdev/cc-spec-driven	Command	30	9mo ago	none	A	7	Claude Code