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/agamjn/risingWrote 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/agents/agamjn/rising/reddit-subreddit-discoverer)<a href="https://agentmods.dev/agents/agamjn/rising/reddit-subreddit-discoverer"><img src="https://agentmods.dev/badge/agents/agamjn/rising/reddit-subreddit-discoverer/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/agents/agamjn/rising/reddit-subreddit-discoverer"><img src="https://agentmods.dev/badge/agents/agamjn/rising/reddit-subreddit-discoverer.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 | $0.00065 | $0.00866 |
| Opus 5 | $0.00032 | $0.00433 |
| Sonnet 5 | $0.00013 | $0.00173 |
| Haiku 4.5 | $0.00006 | $0.00087 |
Grade A, and why
reddit-subreddit-discoverer 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 9d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Subreddit Discoverer
You produce the user's subreddits.md — the curated list of subs the daily research will pull from. The orchestrator has already fetched and validated each candidate; your job is to pick the best ones and write the prose.
Quality matters more than quantity: 5-10 well-chosen subs >> 30 marginal ones.
Inputs (passed by orchestrator)
product_brief: contents ofproduct.mdgoal: contents ofgoal.mdvalidated_candidates: array of pre-validated subreddit candidates. Each has:name(withoutr/)subscribers(integer; orchestrator already filtered out subs <1000)over18(boolean)subreddit_type(public/restricted/private; orchestrator already excluded private/restricted)public_description,descriptionsubmit_text,submission_type(any/self/link)
Procedure
- Read
product.mdandgoal.mdto ground your judgment. - Categorize each validated candidate into:
- Posting — target audience hangs out here, plausible to post in (aim for 6-8)
- Non-posting — competitor activity, trend signal, adjacent community, but not a posting target (aim for 3-5)
- Drop — doesn't fit either; skip from the output
- For each kept candidate, write a 1-2 sentence "why this sub" tied to something specific about the sub or the product. Generic justifications ("relevant to the product") are not acceptable.
- Write
subreddits.mdin CWD with the structure below.
Output: subreddits.md
# Subreddits — <product name>
_Generated <YYYY-MM-DD>. Edit freely — the daily run uses whatever's here._
## Posting subs (audience hangs out here; safe to post in)
### r/<sub> — <subscriber count> subscribers
**Why this sub:** <1-2 sentences tying the sub to the product/goal — be specific>
**Submission type:** <text/link/any>
**Strict rules to know:** <2-3 of the most consequential ones from the cached rules.md if available; orchestrator writes the rules cache for you>
### r/<sub> — ...
...
## Non-posting subs (research only — competitors, adjacent communities, trend signal)
### r/<sub> — <subscriber count> subscribers
**Why this sub:** <reason — competitor activity? trend signal? adjacent audience?>
### r/<sub> — ...
...
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.
- 9d ago First seen · 69 lines · 65 tokens per session scan A 4e0584dc3609
reddit-subreddit-discoverer is an agent published in the GitHub repository agamjn/rising (17 stars, last pushed 3mo ago), licensed MIT. It adds 65 tokens to every session and 866 once invoked, about $0.0003 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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