Borrowing it
Nothing to install: this file belongs to alecs5am/ralphy. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/alecs5am/ralphy/main/.agents/skills/researcher/SKILL.mdgit clone --depth 1 https://github.com/alecs5am/ralphyWrote 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/alecs5am/ralphy/researcher)<a href="https://agentmods.dev/skills/alecs5am/ralphy/researcher"><img src="https://agentmods.dev/badge/skills/alecs5am/ralphy/researcher.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Excessive Agency · line 19 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.
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 | $0.00232 | $0.01920 |
| Opus 5 | $0.00116 | $0.00960 |
| Sonnet 5 | $0.00046 | $0.00384 |
| Haiku 4.5 | $0.00023 | $0.00192 |
Grade A, and why
researcher 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trigger refinements
ALSO FIRE if the message contains a URL on tiktok / instagram / youtube / youtu.be / x / twitter / reddit / facebook AND asks anything analytical about it (in any language).
DO NOT FIRE for rendered-mp4 quality checks (that is /evaluator), for raw downloads-only (use ralphy ref pull directly), or once a scenario is already locked and the user wants prompts / assets (handback to scenarist / art-director).
Hard invariants
- Never ask the user to "send the file" if the URL is on a social platform — WebFetch returns a JS shell on those, but
ralphy ref pull(yt-dlp) gets the mp4. - All LLM / vision calls route through
cli/lib/providers/llm.ts → callLLM()via the CLI. Don't paste raw OpenRouter / yt-dlp code into ad-hoc scripts.
researcher
You take open-ended reference material — URLs, handles, trend queries — and produce a single deep-research document with cited sources. The contract is: the report is the handoff. A scenarist reading report.md should not need to open the source URLs again to write the scenario.
What this skill is not
- Not a quality checker for rendered mp4s. For "is this video good / find issues" use
/evaluator. - Not a one-off downloader. For "just give me the mp4 from this URL" use
ralphy ref pull <url>directly. - Not a scenario writer. The report ends in handoff — the scenarist consumes
sources.jsonand writes from there.
The workflow
Four CLI verbs cover the loop. Don't skip steps — the synthesis step depends on the per-source ref chain having run.
# 1. Start a topic (creates .ralphy/research/<slug>/state.json)
ralphy research start <topic-slug> --question "<the research question>"
# 2. Add each source (full ref chain: pull → frames → transcribe → analyze → audio-describe → blueprint)
ralphy research add-source <url> --topic <slug>
# 3. Cross-source LLM synthesis → report.md + sources.json
ralphy research synthesize <slug>
# 4. Inspect at any time
ralphy research show <slug>
ralphy research list
What ships with it
16 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/playbook.md 6.7 KB
- references/report-schema.md 4.6 KB
- references/research-bootstrap.md 7.6 KB
- references/site-extract.md 3.9 KB
- references/site-grounding.md 8.5 KB
- references/social-extract.md 5.0 KB
- references/transcript.md 2.5 KB
- references/viral-moments.md 2.4 KB
- references/yt-dlp.md 5.1 KB
- scripts/analyze-video.ts 16 KB runs code
- scripts/cross-analyze.ts 5.6 KB runs code
- scripts/extract-design.ts 15 KB runs code
- scripts/extract-playdate-gamelist.ts 5.9 KB runs code
- scripts/extract-playdate-sections.ts 4.2 KB runs code
- scripts/find-viral-moments.ts 10 KB runs code
- scripts/scrape-tiktok-trends.ts 6.6 KB runs code
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 · 109 lines · 232 tokens per session scan A 162b616138c2
researcher is a skill published in the GitHub repository alecs5am/ralphy (132 stars, last pushed 13d ago), licensed Apache-2.0. It adds 232 tokens to every session and 1,920 once invoked, about $0.0012 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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