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 lignertys/reddit-research-skills --skill reddit-researchgit clone --depth 1 https://github.com/lignertys/reddit-research-skillsWrote 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/lignertys/reddit-research-skills/reddit-research)<a href="https://agentmods.dev/skills/lignertys/reddit-research-skills/reddit-research"><img src="https://agentmods.dev/badge/skills/lignertys/reddit-research-skills/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/lignertys/reddit-research-skills/reddit-research"><img src="https://agentmods.dev/badge/skills/lignertys/reddit-research-skills/reddit-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 7 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 51 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
- high Prompt Injection · line 76 This pattern attempts to override system instructions or ignore safety constraints. Without LLM analysis, manual review is recommended.Fix: Remove or rewrite any text that instructs the agent to ignore prompts, override safety rules, or trust unverified content. Ensure skill content cannot be injected to alter agent behavior.
- high Supply Chain · line 186 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- medium Excessive Agency · line 104 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 109 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Data Exfiltration · line 131 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 186 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00186 | $0.03777 |
| Opus 5 | $0.00093 | $0.01888 |
| Sonnet 5 | $0.00037 | $0.00755 |
| Haiku 4.5 | $0.00019 | $0.00378 |
Grade B, and why
reddit-research scanned grade B with 2 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.
Instruction-override phrasingmediumPrompt injection
Text telling the model to disregard its earlier instructions or safety rules is the shape of a prompt injection, whoever wrote it.
phrased as one ("ignore previous instructions", "run this command", a Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST "https://reddapi.dev/api/v1/search/vector" \ How it starts
The opening of the file, as written. The whole thing — 344 lines — stays where its author put it; the contents beside it link to each section on GitHub.
reddit-research Skill
Overview
Reddit is where people complain, compare, and ask for alternatives before they ever fill out a survey. This skill turns that into a queryable research tool via reddapi.dev: search by meaning across 50,000+ subreddits, 20M+ posts, and 40M+ comments using 1024-dimension vector embeddings - "frustrated with X" finds the frustration even when the post never uses the word "frustrated" - then pull trend momentum and subreddit context around it.
Why reddapi.dev instead of the official Reddit API: no OAuth flow, no
registered app, no praw-style setup - just an API key. It's a third-party
index, not Reddit itself, so treat it as a research tool, not a replacement
for Reddit's own API where official data provenance matters.
Key Advantages:
- ✅ Semantic, not keyword - matches intent and phrasing variants a keyword search misses
- ✅ Scale - 50,000+ subreddits, 20M+ posts, 40M+ comments indexed
- ✅ Zero Reddit setup - no OAuth, no registered app, no scraping
- ✅ Trend + subreddit context included - not a separate scrape
Which Search Mode to Use
This matters more than it looks - the two modes are not interchangeable:
- Vector search searches the full archive, fills the requested
limit, and is the faster of the two. Re-measured 2026-07-31 after a server-side fix:limit: 30→ 30 results andlimit: 100→ 100 results, spanning 2026-01-01 to 2026-07-30, in 835ms of server time. It also takesstart_date/end_date, and the filter really applies (a 2026-01-01..03-31 window returned 20/20 rows, none outside the range).totalis the count actually returned, not the size of the match set. - Semantic search also fills the requested
limit(100 → 100) at comparable speed (cold-cache 2.9s), adds LLM keyword extraction and an optional AI summary, and caches per query for ~12h. It accepts no date filter. - Default to vector search: full archive, exact counts, faster, and the
only mode with date filtering. Reach for semantic search when you want the
LLM-side extras (
include_summary, keyword expansion) rather than raw nearest-neighbour hits.
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 · 344 lines · 186 tokens per session scan B cd9e5114c3d3
reddit-research is a skill published in the GitHub repository lignertys/reddit-research-skills (433 stars, last pushed 1mo ago), licensed MIT. It adds 186 tokens to every session and 3,777 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it B with 2 findings (instruction-override phrasing, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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