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 agentmods add skills/clever-cc-plugins/cc-content/research-promptnpx skills add clever-cc-plugins/cc-content --skill research-promptgit clone --depth 1 https://github.com/clever-cc-plugins/cc-contentWrote 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/clever-cc-plugins/cc-content/research-prompt)<a href="https://agentmods.dev/skills/clever-cc-plugins/cc-content/research-prompt"><img src="https://agentmods.dev/badge/skills/clever-cc-plugins/cc-content/research-prompt.svg" alt="Measured on agentmods" 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 | $0.00125 | $0.01068 |
| Opus 5 | $0.00063 | $0.00534 |
| Sonnet 5 | $0.00025 | $0.00214 |
| Haiku 4.5 | $0.00013 | $0.00107 |
Grade A, and why
research-prompt 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 6d 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Prompt Generator
You are generating a single, vendor-neutral prompt the owner can paste into the "deep research" feature of any AI tool they have available (Claude, ChatGPT, Gemini, Perplexity, DeepSeek, or similar). This skill produces the prompt only — it does not run research, call any tool or API, or prescribe where the owner saves the result. Keep it that way: no tool-specific phrasing, no "upload this to context/" instructions in the generated prompt. Where the owner stores the research report afterward is entirely up to them.
Step 0: Recall learnings
If .claude/learnings.md exists, read it silently. Apply all entries relevant to this
run. Do not announce this step. If the file is absent, continue normally.
Step 1: Gather the topic
If $ARGUMENTS contains a topic, use it. Otherwise ask:
"What topic do you want researched?"
Wait for the answer.
Step 2: Refine scope (optional)
Ask once, offering a sensible default:
"Any specific angle, sub-questions, or things to exclude — or should I keep it a broad, comprehensive overview of [topic]?"
If the owner gives a specific angle or sub-questions, fold them into the prompt as explicit coverage points. If they say broad/no preference, proceed with a general comprehensive-overview framing.
Step 3: Generate the prompt
Produce a single research prompt with this structure:
- Open with a role framing appropriate to the topic (e.g. "You are a research analyst investigating...") — do not name or assume any specific AI tool or vendor.
- State the topic and scope clearly, including any sub-questions or exclusions from Step 2.
- Ask for a comprehensive, well-structured response using headers to separate major areas of coverage.
- Require credible, verifiable sources throughout, with in-text citations.
- Require a formatted source list in APA style at the end.
- Request the output in Markdown, since the owner will save the response as a
.mdfile.
Step 4: Present the prompt
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.
- 6d ago First seen · 125 lines · 125 tokens per session scan A d7331abb5a10
research-prompt is a skill published in the GitHub repository clever-cc-plugins/cc-content (1 stars, last pushed 11d ago), licensed MIT. It adds 125 tokens to every session and 1,068 once invoked, about $0.0006 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 2026-08-31.
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