# Internet Skill
Deep iterative web research for current facts, verification, due diligence, comparisons, market maps, and cited synthesis.
`internet` turns broad research prompts into a disciplined investigation loop: preflight the question, plan source classes, search in passes, read primary evidence, check contradictions, track claims, and synthesize with citations. When research should become durable memory, it prepares review-gated AKBP source and claim previews.
## Install
Install this repository with any skill-capable agent or skill manager that can consume a `skills/` directory. The skill itself lives at `skills/internet/SKILL.md` and is intentionally agent-portable.
With SkillKit:
```bash
npx skillkit install rohitg00/internet-skill
```
With an agent-specific plugin marketplace, add `rohitg00/internet-skill` and install the `internet` skill using that agent's normal plugin flow.
## What It Does
- Plans research before searching.
- Catches ambiguous prompts, generic rankings, numeric traps, temporal traps, and high-stakes edge cases.
- Searches orientation, primary, independent, community, contradiction, and gap-fill passes.
- Tracks claims, source tiers, dates, confidence, caveats, contradictions, and unresolved gaps.
- Prepares AKBP source and claim previews without silently writing durable memory.
- Produces cited briefs, reports, comparisons, timelines, recommendation memos, and evidence packs.
- Includes a workspace helper for long-running investigations.
## Example Prompts
```text
Use $internet to research whether we should adopt Bun for a TypeScript monorepo in 2026.
```
```text
Use $internet to build a detailed competitor map for AI browser automation tools.
```
```text
Use $internet to verify the latest Kubernetes Gateway API production readiness claims.
```
## Workspace Helper
```bash
WORKSPACE="$(python3 skills/internet/scripts/research_workspace.py create "AI browser automation tools" --depth deep | sed -n '1p')"
python3 skills/internet/scripts/research_workspace.py add-query "$WORKSPACE" --pass-label orientation --query "AI browser automation tools 2026" --tool web --why "discover landscape" --result "identified primary projects"
python3 skills/internet/scripts/research_workspace.py add-source "$WORKSPACE" --url "https://example.com" --title "Source title" --type primary --tier 1 --published YYYY-MM-DD
python3 skills/internet/scripts/research_workspace.py add-claim "$WORKSPACE" --claim "Material claim" --evidence "Evidence note" --source-id S001 --confidence High
python3 skills/internet/scripts/research_workspace.py add-evidence "$WORKSPACE" --source-id S001 --claim-id C001 --evidence "Structured evidence note"
python3 skills/internet/scripts/research_workspace.py summary "$WORKSPACE"
```
The helper creates a working folder and records query, source, claim, evidence, contradiction, gap, and AKBP intake ledgers. Recorder commands also update `research.md`, so deep research does not end with an empty-looking report.