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 cyberelf/agent_skills --skill deepresearchgit clone --depth 1 https://github.com/cyberelf/agent_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/cyberelf/agent_skills/deepresearch)<a href="https://agentmods.dev/skills/cyberelf/agent_skills/deepresearch"><img src="https://agentmods.dev/badge/skills/cyberelf/agent_skills/deepresearch/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/cyberelf/agent_skills/deepresearch"><img src="https://agentmods.dev/badge/skills/cyberelf/agent_skills/deepresearch.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 | $0.00093 | $0.01363 |
| Opus 5.5 | $0.00037 | $0.00545 |
| Sonnet 5.5 | $0.00019 | $0.00273 |
| Haiku 4.5 | $0.00009 | $0.00136 |
Grade A, and why
deepresearch 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Research Skill
Conduct rigorous, multi-part research on a complex topic producing a report grounded entirely in confirmed sources. No design assumptions before research is complete. All claims backed by source links.
Skill Files
This skill is split across files — read the relevant ones before proceeding:
| File | Purpose |
|---|---|
security.md |
Full template and agent prompts for security research mode |
techtrend.md |
Full template and agent prompts for tech trend / ecosystem research mode |
law-policy.md |
Full template and agent prompts for law, policy, regulatory, and compliance research mode |
report-template.html |
HTML report template — use when user requests an HTML output |
Step 1: Detect Mode
Determine research mode from the query before reading any template:
| Mode | Trigger keywords | Template to read |
|---|---|---|
security |
security, threat, CVE, attack, defense, vulnerability, exploit, risk, malware | Read security.md |
techtrend |
trend, forecast, ecosystem, landscape, technology, hardware, market, adoption | Read techtrend.md |
law-policy |
law, policy, regulation, compliance, legal requirement, statutory, retention, audit trail, recordkeeping, regulator, licensee, service provider, data residency, data protection, privacy, telecom law, cybersecurity law | Read law-policy.md |
| Ambiguous | None clearly applies, or multiple modes are plausible | Ask: "Is this a security analysis, technology trend/ecosystem research, or law/policy compliance research?" |
Step 2: Read the Template
After detecting mode, read the appropriate template file in full before writing the research plan or launching agents. The template files contain:
- The 5-part structure for that mode
- Per-part research questions and source guidance
- Agent prompt scaffolding
- Lessons learned specific to that mode
Step 3: Execute
Follow the execution steps in the template. The core workflow is the same for all modes:
What ships with it
4 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.
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 · 123 lines · 93 tokens per session scan A b1216cc4b69f
deepresearch is a skill published in the GitHub repository cyberelf/agent_skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 93 tokens to every session and 1,363 once invoked, about $0.0004 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.
deepresearch compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| deepresearchcyberelf/agent_skills | Skill | 2 | 2mo ago | MIT | A | 93 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| chat-pet-sprite-creationmicrosoft/vscode | Skill | 195k | today | MIT | A | 53 | Claude Code, Codex |