Researcher

SkillDev tools

Research current topics with multiple sources and produce a structured brief, comparison, recommendation, or fact-check. Use when the user asks for investigation, market/product landscape scans, option evaluation, due diligence, source-backed validation, or a research report. Do not use for summarizing a single provided URL/document, or for GitHub issue/PR operations.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Researcher skill

What this skill tells your AI

The instructions your AI receives, as published by understudy-ai/understudy in skills/researcher/SKILL.md and read by ahel’s review.

Use this skill for bounded, source-backed research.

Default goal: turn an open-ended question into a concise research output with explicit evidence, tradeoffs, and uncertainty.

When to use

Use this skill when the user wants any of:

  • a comparison of products, vendors, tools, APIs, papers, or approaches
  • a market or ecosystem landscape scan
  • due diligence on a company, category, or technical option
  • fact-checking or claim validation with citations
  • a structured research brief, memo, or recommendation

Do not use this skill for:

  • summarizing one URL, one article, one video, or one local file; use the more specific summarize flow instead
  • GitHub issue, PR, release, or CI workflows; use the GitHub-specific skills instead
  • purely internal codebase exploration with no web research component

Working style

Prefer current sources over memory. Use a small search budget first, then expand only if the evidence is weak or conflicting.

Unless the user already gave a narrow format, produce:

  1. Research goal
  2. Short answer or recommendation
  3. Comparison or findings
  4. Risks, caveats, and unknowns
  5. Sources

If the user asks for a persistent artifact, write a Markdown report under research/ with a short kebab-case filename that matches the topic.

Workflow

Follow these phases in order.

1. Frame the question

Before searching, extract or infer:

  • the decision to be made
  • the comparison axes or success criteria
  • any hard constraints such as budget, platform, geography, or timeline

If one missing detail would materially change the answer, ask a short clarifying question. Otherwise proceed with a stated assumption.

2. Make a research plan

Break the work into 3-7 subquestions. Keep them concrete and decision-relevant.

Examples:

  • What options belong in scope?
  • What are the meaningful differences?
  • What evidence is primary vs secondary?
  • What risks or hidden costs matter?

3. Use a bounded search budget

Start with a tight first pass:

  • 2-4 targeted searches to map the space
  • fetch the strongest candidate sources
  • expand only if the first pass is incomplete, outdated, or contradictory

Avoid aimless searching. Stop when additional searches are no longer changing the answer.

4. Prefer stronger evidence

When possible, prioritize:

  • official product or vendor documentation
  • original papers, specs, standards, or release notes
  • first-party pricing or policy pages
  • reputable primary reporting or direct statements

Use secondary summaries only to discover leads, not as the sole basis for important conclusions.

5. Compare and validate

For each important claim:

  • note which source supports it
  • look for disagreement or missing context
  • cross-check high-impact claims with at least two independent sources when feasible

Call out any inference you are making from the evidence instead of presenting it as a confirmed fact.

6. Produce a decision-ready output

Keep the final answer structured and useful. Include:

  • the answer up front
  • a short comparison table or bullets when multiple options are involved
  • the strongest evidence and why it matters
  • explicit uncertainty, recency limits, and open questions
  • source links or source identifiers

Output templates

Comparison / recommendation

Use this shape by default:

  • Recommendation
  • Why it wins
  • Alternatives considered
  • Key risks or tradeoffs
  • Sources

Fact-check / validation

Use this shape:

  • Verdict: supported / mixed / unsupported / unclear
  • What the evidence says
  • What remains uncertain
  • Sources

Landscape scan

Use this shape:

  • Category snapshot
  • Main players or approaches
  • How they differ
  • Notable gaps, risks, or trends
  • Recommendation or next step
  • Sources

Tool guidance

Prefer web_search to discover candidates, web_fetch to read exact page contents, and pdf when a primary source is a PDF.

Use the browser only when a relevant source requires interactive navigation, login, or a page state that the normal web tools cannot reach.

Quality bar

Do not end with a pile of links. Synthesize.

Do not present stale or weakly supported claims as settled.

Do not hide uncertainty. If the evidence is thin, say so clearly and narrow the recommendation.

Signals

GitHub stars
456
Forks
34
Last commit
Jun 2026
Advanced
Catalog kind
skill
Gateway key
researcher-understudy-ai
Source
github.com/understudy-ai/understudy