lignertys/reddit-research-skills: Reddit research skills for Claude Code and AI agents

What reddit-research-skills actually solves

Reddit is where people describe broken products, half-finished migrations and tools they regret buying. Getting at that text programmatically has traditionally meant either the official Reddit API, with its app registration and OAuth dance, or a scraper you maintain yourself. This repository takes a third route: it ships prompt-level skills that call reddapi.dev, a third-party service the README explicitly describes as "not Reddit official", so no Reddit OAuth or app registration is needed.

The audience is narrow and specific. These are skills for Claude Code and AI agents, distributed as agent-skill packages rather than as a Python library you import. If you are a product manager asking an agent to summarize complaints about a competitor, or a founder testing whether a niche has real demand, the skill turns that request into a sequence of API calls without you writing the query logic. The repository also carries a reddit-leads skill for B2B lead discovery, which finds posts with buying intent, scores them 0 to 100 and classifies them by lead type: pain_point, solution_request, complaint, feature_request or comparison.

The README is blunt about the trade-off. This is not unlimited access. It is gated by plan-based rate limits, and an invalid or exhausted key returns HTTP 429. So the project solves the integration problem, not the data-access problem.

Four skills, one engine, and why the naming matters

The repository exposes four skill packages, and the distinction between them is mostly about framing rather than capability. reddit-research is the canonical skill: market research, user research and product validation, with query playbooks for competitor research, niche validation and trend tracking. reddapi is the legacy name for the same engine, kept live for existing installs and described as fully functional standalone, with new installs steered toward reddit-research for the expanded playbooks. reddit-search-api is a pure API reference covering endpoints, parameters, response schemas and error codes, with no research-workflow framing, aimed at developers who just want the docs. reddit-leads is the odd one out, because it requires a paid plan.

That redundancy is a real cost. Three names for overlapping functionality means a reader has to decide which one to install, and the README's own guidance is the only signal. My read is that reddit-search-api is the honest choice if you are going to write your own prompts anyway, since the research framing adds nothing to an agent that already knows what it wants to ask.

Underneath, all four sit on the same engine: vector search, semantic search, a trends API and subreddit discovery. The README claims coverage of 50K+ subreddits, 20M+ posts and 40M+ comments. Those are the vendor's figures, not something this review can confirm.

Vector search versus semantic search: picking the right endpoint

The two search modes behave differently in ways that matter for research design. Vector Search does full-archive embedding similarity and returns a similarity_score, supports working date filters, and gives exact result counts up to limit: 100. Semantic Search runs natural-language queries at comparable speed, adds LLM keyword extraction and an optional AI summary, but has no date filter.

That is not a minor omission. If your question is "what changed in how people talk about this since last quarter", Semantic Search cannot answer it, because you cannot bound the window. You would have to fall back to Vector Search and lose the keyword extraction and summary. Conversely, if you want a quick read on a fuzzy concept and do not care when the posts were written, Semantic Search is the faster path.

The Trends API is the third leg: topic momentum over a required date range. Note the word required. You cannot ask for a trend without specifying the range, which is the correct design for a momentum metric but does mean the API will reject a vague request rather than guess a default. Subreddit Discovery rounds out the set with listing and lookup.

One practical consequence: the 100-result cap on Vector Search is a hard ceiling, not a pagination hint. For broad topics, plan to slice by date range or subreddit rather than expecting to pull everything.

Installing the skill and running a first query

The README gives a single install command using the skills CLI. It targets the reddit-research skill specifically, which is what you want for a new install:

npx skills add https://github.com/lignertys/reddit-research-skills --skill reddit-research

After that, the skill is available in conversation. You do not call functions or write JSON. You ask in natural language, and the README's examples look like this:

Find discussions about iPhone problems and complaints on Reddit

Search for user frustrations with current productivity tools

What are people saying about AI agent limitations?

The skill translates the request into reddapi.dev calls and returns relevant discussions with engagement metrics. You will need an API key, which the README points to at https://reddapi.dev. The repository does not document where that key is stored or which environment variable the skill reads, so that is something to check in the skill's own SKILL.md before you assume it is configured.

If you are installing for Gemini CLI rather than Claude Code, the repository carries a gemini-extension.json at the top level, which is the manifest that path uses. The README does not walk through the Gemini install separately.

The paid-plan gate and the 429 you will hit

The clearest limitation is commercial, not technical. reddit-leads requires a paid reddapi.dev plan, and the README directs you to skills/reddit-leads/SKILL.md for the plan and quota table. Everything is subject to plan-based rate limits, and an invalid or exhausted key returns HTTP 429.

That failure mode is worth planning around. A 429 does not distinguish between "you typed the key wrong" and "you burned your quota", so an agent workflow that retries on failure will simply retry into the same wall. If you are building anything automated on top of these skills, treat the 429 as terminal until a human checks the key and the quota.

The second limitation is the third-party dependency itself. Because this is not Reddit official, the data pipeline is only as available as reddapi.dev. There is no fallback path in the repository, and no self-hosted mode. If reddapi.dev changes its pricing, its endpoints or its terms, the skills are affected directly and your only recourse is to stop using them.

The third is scope. These skills are research and discovery tools. They are not a monitoring system, not an alerting pipeline, and not a historical archive you control. If you need data you can re-query offline in two years, this is the wrong shape of tool.

How this differs from scraping Reddit yourself

The obvious alternative is rolling your own: pull from Reddit's official API or a scraper library, embed the posts, and query your own vector store. The difference in approach is where the work sits. Self-hosting gives you control over retention, no per-query cost beyond compute, no rate limit imposed by a vendor, and no dependency on a third party's uptime. What it costs you is the embedding pipeline, the storage, the subreddit coverage decisions, and the ongoing job of keeping ingestion running as Reddit's access rules shift.

reddit-research-skills is the opposite bet. You trade control and marginal cost for zero infrastructure. The engine already covers the corpus, the query playbooks are written for you, and the install is one command. For a one-off validation question, that trade is clearly correct. For a standing data product, it clearly is not.

There is a middle position the repository itself acknowledges: install reddit-search-api instead of reddit-research if you want the endpoint reference without the workflow framing. That is still the hosted engine, but it stops pretending to be a research methodology and just documents the API.

A second alternative worth naming is doing nothing programmatic at all. Reddit's own search plus manual reading is free and often sufficient for a single question. The skills earn their place when the question repeats.

Maintenance, licence and what the last push tells you

The repository is not archived, and the last push was on 2026-08-06, roughly six weeks before this writing. That is recent enough that the project is not stale, but the release history is thin: the only release listed is 1.0.0 from 2026-02-06. So the code has moved since the last tagged release, and anyone pinning to 1.0.0 is pinning to something six months behind the branch.

The upgrade surface is small, which is the good news. There is no server to run, no database to migrate, and no compiled artifact. Upgrading means reinstalling the skill through the same npx skills add command, and the main risk is that a skill's prompt behavior changes under you. Because the skills are prompt-level, a version bump can change output format without changing any API signature, and the README does not document a rollback path. If you need reproducibility, pin the commit you installed from.

The licence is MIT, which is permissive and places few obligations on how you use the skill code. Note the boundary: MIT covers this repository, not reddapi.dev. Your use of the API is governed by that service's own terms and pricing, and the README does not reproduce them. Nothing here is legal advice, but the practical point is that the permissive licence on the skills does not grant you any rights to the underlying data service.

Editorial conclusion

Adopt it if your agent already runs Claude Code or Gemini CLI and you are willing to pay for a reddapi.dev plan, because the skills are thin wrappers and the API key is the real dependency. Do not adopt it if you need a self-hosted, unlimited Reddit data pipeline, or if you want the lead-scoring workflow without a paid plan, since reddit-leads is gated and an exhausted key returns HTTP 429. Before installing, verify the current plan and quota table in skills/reddit-leads/SKILL.md, confirm that reddit-research is the skill name you want rather than the legacy reddapi name, and check whether your workflow needs date filters, which only Vector Search and Trends support.

Frequently asked questions

Official sources

1. License: MIT
2. lignertys/reddit-research-skills on GitHub
3. Project website
4. README
5. Releases