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 skills add SaintNerona/pi-reddit-research --skill reddit-researchgit clone --depth 1 https://github.com/SaintNerona/pi-reddit-researchWrote 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/saintnerona/pi-reddit-research/reddit-research)<a href="https://agentmods.dev/skills/saintnerona/pi-reddit-research/reddit-research"><img src="https://agentmods.dev/badge/skills/saintnerona/pi-reddit-research/reddit-research/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/skills/saintnerona/pi-reddit-research/reddit-research"><img src="https://agentmods.dev/badge/skills/saintnerona/pi-reddit-research/reddit-research.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 | $0.00038 | $0.00630 |
| Opus 5 | $0.00019 | $0.00315 |
| Sonnet 5 | $0.00008 | $0.00126 |
| Haiku 4.5 | $0.00004 | $0.00063 |
Grade A, and why
reddit-research 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 12d 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reddit Research
Use the local Reddit tools when the user asks what people on Reddit say, recommend, complain about, compare, or use in real practice.
Tool Choice
- Use
reddit_packfor most research questions. It searches posts and fetches top comments for a small evidence pack. - Use
reddit_searchwhen you only need candidate posts or want to find whether a topic/repo/error was discussed. - Use
reddit_threadwhen the user gives a Reddit URL or one thread fromreddit_searchlooks important. - Use
reddit_resolve_subredditswhen the user asks where a topic is discussed or when a focused subreddit scope would improve search. - Use
reddit_subredditsonly for raw subreddit search when ranking is not needed. - Use
reddit_url_extractwhen the user gives an arbitrary Reddit URL, old.reddit URL, post id, or comment id. - Use
reddit_trendsfor "what is currently hot/top/new in r/LocalLLaMA" style questions.
Intent Mapping
- opinions: "what do people think", product/tool sentiment, praise vs criticism.
- bugs: frequent problems, complaints, failure modes, risks.
- fixes: how people solved an error or configuration issue.
- compare: A vs B, which tool users pick, migration reasons.
- settings: sampler, scheduler, config, parameters, low denoise, hardware settings.
- alternatives: replacements for a library, service, app, or workflow.
- trends: what topics are surfacing recently.
- guides: tutorials, walkthroughs, reproducible setup posts.
- hardware: devices, VRAM/RAM, speed, thermals, purchase advice.
- general: fallback for broad Reddit research.
Depth
quick: first-pass orientation; fewer posts and comments.normal: default for most user questions.deep: use only when the user asks for thorough research; it fetches more comments and costs more tokens/time.
Answering Rules
- When a tool has a
subredditsparameter, pass multiple subreddits as one comma-separated string likeLocalLLaMA, LocalLLM, ClaudeCode, not as a JSON/list value. - Treat Reddit as anecdotal evidence, not truth.
- Separate repeated patterns from one-off comments.
- Mention uncertainty when evidence is thin or old.
- Cite evidence by post number, subreddit, or thread URL from tool output.
- Prefer concrete details from comments: versions, commands, settings, hardware, exact error text, and final outcome.
- For comparisons, group findings by option and distinguish direct user experience from speculation.
- Do not invent subscriber counts, trend numbers, score totals, or popularity claims unless the tool output includes them.
- Use
evidence_itemsand clusters fromreddit_packas hints, not as final truth.
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.
- 12d ago First seen · 50 lines · 38 tokens per session scan A 1fd24e11fd02
reddit-research is a skill published in the GitHub repository SaintNerona/pi-reddit-research (19 stars, last pushed 3mo ago), licensed MIT. It adds 38 tokens to every session and 630 once invoked, about $0.0002 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.
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