Deep-Research-skills is a structured research workflow for Claude Code, OpenCode, and Codex that guides agents through outlining and then investigating a question. Researchers use it for tasks such as literature reviews, technology comparisons, market analysis, and due diligence, with human approval during the process.
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 Weizhena/Deep-Research-skills --skill research-add-fieldsgit clone --depth 1 https://github.com/Weizhena/Deep-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/weizhena/deep-research-skills/research-add-fields)<a href="https://agentmods.dev/skills/weizhena/deep-research-skills/research-add-fields"><img src="https://agentmods.dev/badge/skills/weizhena/deep-research-skills/research-add-fields/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/weizhena/deep-research-skills/research-add-fields"><img src="https://agentmods.dev/badge/skills/weizhena/deep-research-skills/research-add-fields.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
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 | $0.00012 | $0.00187 |
| Opus 5 | $0.00006 | $0.00093 |
| Sonnet 5 | $0.00002 | $0.00037 |
| Haiku 4.5 | $0.00001 | $0.00019 |
Grade A, and why
research-add-fields 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 11d 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.
What it actually says
Research Add Fields - Supplement Research Fields
Trigger
/research-add-fields
Workflow
Step 1: Auto-locate Fields File
Find */fields.yaml file in current working directory, auto-read existing fields definitions.
Step 2: Get Supplement Source
Ask user to choose:
- A. User direct input: User provides field names and descriptions
- B. Web Search: Launch agent to search common fields in this domain
Step 3: Display and Confirm
- Display suggested new fields list
- User confirms which fields to add
- User specifies field category and detail_level
Step 4: Save Update
Append confirmed fields to fields.yaml, save file.
Output
Updated {topic}/fields.yaml file (in-place modification, requires user confirmation)
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.
- 11d ago First seen · 31 lines · 12 tokens per session scan A 93757fb5ea74
research-add-fields is a skill published in the GitHub repository Weizhena/Deep-Research-skills (2,135 stars, last pushed 18d ago), licensed MIT. It adds 12 tokens to every session and 187 once invoked, about $0.0001 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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