Web ResearchSAFE
The batteries-included agent harness.
Overview
The batteries-included agent harness.
5008d6f3b5f7OBSERVED · 2026-10-27What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
--- name: web-research description: Searches multiple web sources, synthesizes findings, and produces cited research reports using delegated subagents. Use when the user asks to research a topic online, search the web, look something up, find current information, compare options, or produce a research report. --- # Web Research Skill ## Research Process ### Step 1: Create and Save Research Plan Before delegating to subagents, you MUST: 1. **Create a research folder** - Organize all research files in a dedicated folder relative to the current working directory: ``` mkdir research_[topic_name] ``` This keeps files organized and prevents clutter in the working directory. 2. **Analyze the research question** - Break it down into distinct, non-overlapping subtopics 3. **Write a research plan file** - Use the `write_file` tool to create `research_[topic_name]/research_plan.md` containing: - The main research question - 2-5 specific subtopics to investigate - Expected information from each subtopic - How results will be synthesized **Planning Guidelines:** - **Simple fact-finding**: 1-2 subtopics - **Comparative analysis**: 1 subtopic per comparison element (max 3) - **Complex investigations**: 3-5 subtopics ### Step 2: Delegate to Research Subagents For each subtopic in your plan: 1. **Use the `task` tool** to spawn a research subagent with: - Clear, specific research question (no acronyms) - Instructions to write findings to a file: `research_[topic_name]/findings_[subtopic].md` - Budget: 3-5 web searches maximum 2. **Run up to 3 subagents in parallel** for efficient research **Subagent Instructions Template:** ``` Research [SPECIFIC TOPIC]. Use the web_search tool to gather information. After completing your research, use write_file to save your findings to research_[topic_name]/findings_[subtopic].md. Include key facts, relevant quotes, and source URLs. Use 3-5 web searches maximum. ``` ### Step 3: Synthesize Findings After all subagents complete: 1. **Review the findings files** that were saved locally: - First run `list_files research_[topic_name]` to see what files were created - Then use `read_file` with the **file paths** (e.g., `research_[topic_name]/findings_*.md`) - **Important**: Use `read_file` for LOCAL files only, not URLs 2. **Synthesize the information** - Create a comprehensive response that: - Directly answers the original question - Integrates insights from all subtopics - Cites specific sources with URLs (from the findings files) - Identifies any gaps or limitations 3. **Write final report** (optional) - Use `write_file` to create `research_[topic_name]/research_report.md` if requested **Note**: If you need to fetch additional information from URLs, use the `fetch_url` tool, not `read_file`. ## Best Practices - **Plan before delegating** - Always write research_plan.md first - **Clear subtopics** - Ensure each subagent has distinct, non-overlapping scope - **File-based communication** - Have subagents save findings to files, not return them directly - **Systematic synthesis** - Read all findings files before creating final response - **Stop appropriately** - Don't over-research; 3-5 searches per subtopic is usually sufficient
Trust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
5008d6f3b5f7full audit observations/trust-audit/skill/langchain-ai__web-research.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-27 | 5008d6f3b5f7 | SAFE | B | 89 | first audit |
Questions
What does the web-research — langchain-ai/deepagents skill do?
The batteries-included agent harness.
Is web-research — langchain-ai/deepagents safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can web-research — langchain-ai/deepagents access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
What do I need installed to use web-research — langchain-ai/deepagents?
Its own instructions reference fetch_url. Dependencies are pinned to exact versions.
How current is this page?
The grade is for one exact copy of the source (5008d6f3b5f7), read on 2026-10-27. The repository is watched, and a new audit runs when it changes — this is the first audit.
Add this badge to your README
Shows this page's audit result and links back to it. It updates when the audit does.
[](https://modelsatlas.com/skills/langchain-ai/web-research/)
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