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 mayrsascha/deep-research-skill --skill deep-researchgit clone --depth 1 https://github.com/mayrsascha/deep-research-skillWrote 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/mayrsascha/deep-research-skill/deep-research)<a href="https://agentmods.dev/skills/mayrsascha/deep-research-skill/deep-research"><img src="https://agentmods.dev/badge/skills/mayrsascha/deep-research-skill/deep-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/mayrsascha/deep-research-skill/deep-research"><img src="https://agentmods.dev/badge/skills/mayrsascha/deep-research-skill/deep-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 | $0.00050 | $0.00781 |
| Opus 5.5 | $0.00020 | $0.00312 |
| Sonnet 5.5 | $0.00010 | $0.00156 |
| Haiku 4.5 | $0.00005 | $0.00078 |
Grade A, and why
deep-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 2mo 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a research prompt engineer. Your job is to take a research request, ground it in the user's project context, transform it into an expert Deep Research prompt, and copy it to the user's clipboard.
Instructions
-
Take the research request provided by the user.
-
Gather project context — this is not optional. Before crafting the prompt:
- Check package.json, requirements.txt, Cargo.toml, or equivalent for the tech stack and dependencies
- Check the recent conversation for the problem being solved or decision being made
- Note any constraints, existing integrations, or architectural decisions already in play
- If you already have this context from the current session, use it — do NOT re-explore the codebase. Only look up files if the user's request references something you haven't seen.
-
Craft the prompt using this structure:
## Objective
[One paragraph: what to research and why it matters for this project]
## Context
[Tech stack, existing integrations, constraints, scale, team size — concrete details from the project]
## Investigate
[Numbered list of specific angles, questions, or comparisons to explore]
## Output Format
[Exactly what structure the research should be delivered in — report sections, comparison matrix, decision framework, etc.]
## Constraints
[Scope boundaries, what to exclude, any preferences or non-negotiables]
- Copy the prompt to the clipboard using a pipe and heredoc. Try clipboard commands in order until one works. If none are available, print the prompt to stdout and tell the user to copy it manually.
cat <<'PROMPT' | pbcopy 2>/dev/null || cat <<'PROMPT' | xclip -selection clipboard 2>/dev/null || cat <<'PROMPT' | wl-copy 2>/dev/null || cat <<'PROMPT' | clip.exe 2>/dev/null
[your crafted prompt here]
PROMPT
If all clipboard commands fail, output the prompt in a clearly marked block and tell the user: "Could not access clipboard. Copy the prompt above manually."
- After copying, confirm to the user:
- That the prompt has been copied to their clipboard
- A brief summary of what the prompt asks to be researched
- Suggest pasting into their preferred deep research tool (Gemini Deep Research, Perplexity, ChatGPT, etc.)
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.
- 2mo ago First seen · 73 lines · 50 tokens per session scan A 9dbfb5ccd9f4
deep-research is a skill published in the GitHub repository mayrsascha/deep-research-skill (5 stars, last pushed 8mo ago), licensed MIT. It adds 50 tokens to every session and 781 once invoked, about $0.0002 per session on Opus 5.5. 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.
deep-research compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| deep-researchmayrsascha/deep-research-skill | Skill | 5 | 8mo ago | MIT | A | 50 | Claude Code, Codex |
| skillnoteluna-prompts/skillnote | Skill | 68 | 6d ago | MIT | A | 54 | Claude Code, Codex |
| ai-architect-newsletterfrankxai/claude-skills-library | Skill | 47 | yesterday | MIT | A | 85 | Claude Code |
| loop-designerfrankxai/claude-skills-library | Skill | 47 | yesterday | MIT | A | 106 | Claude Code |
| acos-metafrankxai/claude-skills-library | Skill | 47 | yesterday | MIT | A | 63 | Claude Code |
| github-project-managementfrankxai/claude-skills-library | Skill | 47 | yesterday | MIT | A | 49 | Claude Code |
| hive-mind-advancedfrankxai/claude-skills-library | Skill | 47 | yesterday | MIT | A | 47 | Claude Code |