AI-Assisted Research SKILL.md

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---
name: ai-assisted-research
description: "Use AI research tools well: choosing between deep research modes, AI search, assistants and browsing agents, writing research briefs with preferred sources and evidence standards, verifying citations, filling gaps, resolving conflicts, protecting confidential data and writing a human-checked synthesis. Use whenever someone uses deep research, AI search or an AI agent to research a topic, wants better research prompts, needs to verify AI-cited sources or turn an AI research report into a reliable summary."
license: CC-BY-4.0
metadata:
  author: Afeez Adebayo
  author_url: https://afeezadebayo.com
  author_linkedin: https://www.linkedin.com/in/afeez-adebayo/
  author_x: https://x.com/za_icon
  source: https://afeezadebayo.com/skills-md/productivity/research-learning/ai-assisted-research/
  category: productivity
  subcategory: research-learning
  version: "1.0.0"
  created: "2026-10-10"
  updated: "2026-10-14"
---

# AI-Assisted Research

AI research tools such as deep research features in assistants, AI search engines and agents that browse can read dozens of sources in minutes and produce long, polished reports. They are useful for getting oriented quickly, finding sources and drafting syntheses. They also make specific mistakes: citing sources that do not support the claim, mixing outdated and current information, presenting weak sources confidently, missing paywalled or non-English material, and inventing details when evidence is thin. The skill is not in pressing the button; it is in briefing the tool well and verifying what comes back.

This skill uses AI for research effectively and safely: choosing the right tool, writing a strong research brief, steering source quality, asking for structured outputs with citations, verifying claims, filling gaps with targeted searches and combining AI findings with human judgement.

## Operating principles
1. **Brief like a research lead.** Question, scope, sources to prefer and avoid, output format and evidence standards.
2. **Citations are leads, not proof.** Open sources for every key claim.
3. **Ask for uncertainty.** Request confidence levels, conflicts and gaps, not just answers.
4. **Prefer primary sources.** Tell the tool which source types count.
5. **Iterate.** Follow up on gaps and weak sections with targeted questions.
6. **Protect confidential data.** Do not paste sensitive information into tools that are not approved for it.

## Tool types
| Tool | Strengths | Watch for |
|---|---|---|
| Deep research modes in assistants | Long multi-source reports, planning steps | Over-confident synthesis; check citations |
| AI search engines | Fast answers with links | Shallow coverage; SEO-heavy sources |
| Assistant with web search | Conversational follow-up | Variable source quality |
| Agents with browsing (for example Claude Code or computer-use tools) | Systematic collection into tables | Need clear instructions and limits |
| Academic AI tools | Finding and summarising papers | Check papers exist and say what is claimed |

## When to use, and when not to
Use it to get oriented on a new topic, build a source list, draft literature or market overviews, compare options, collect structured data from many pages and prepare for interviews.

Don't rely on it alone for high-stakes facts, legal, medical or financial advice, or claims you will publish without verification.

## Inputs
- The research plan or question.
- Preferred and excluded source types.
- Regions, dates and languages.
- Output format and evidence standards.
- Any internal documents the tool may use (if approved).

## Workflow

### Step 1. Write the brief
Use the template below.

### Step 2. Choose the tool
Quick orientation: AI search. Comprehensive overview: deep research mode. Structured collection: agent with browsing.

### Step 3. Run and skim
Read the summary and structure; note claims that matter most for the decision.

### Step 4. Verify key claims
Open the cited sources; confirm wording, numbers and dates; check source quality.

### Step 5. Fill gaps
Ask targeted follow-ups or run your own searches for weak or missing areas.

### Step 6. Cross-check conflicts
Where sources disagree, find the original data and explain the difference.

### Step 7. Write your own synthesis
Use the AI draft as raw material; your final output states what is verified, with confidence labels.

## Research brief template
```
Question: <specific question and the decision it informs>
Scope: <regions, time period, segments>
Prefer sources: <official statistics, filings, peer-reviewed studies, reputable press>
Avoid: <vendor blogs, undated pages, forums unless for customer language>
Output: <structure, e.g. summary, findings by sub-question, table, sources>
For each finding: cite the source with date, give a confidence level and note conflicts.
List what you could not find or verify.
```

## Verification checklist
- [ ] Each key number traced to a source that states it.
- [ ] Source dates recorded; outdated data flagged.
- [ ] Source types match the brief (primary where needed).
- [ ] Quotes match originals.
- [ ] Conflicts explained.
- [ ] Gaps listed rather than filled with guesses.

## Prompts for better AI research
- "Before answering, list the sub-questions you will research."
- "Use official statistics and peer-reviewed studies first; mark any vendor or blog sources."
- "For each claim, give the exact sentence from the source it comes from."
- "What evidence would contradict this conclusion? Search for it."
- "List the three weakest parts of this report."

## Structured collection with agents
For tasks like comparing 40 competitors' pricing or collecting regulations across 10 countries, give an agent a table schema, the list of targets and rules (official pages only, record URL and date, leave blank if not found). Review a sample of rows against the sources before trusting the full table. Structured collection is where AI saves the most time, because the output is easy to check row by row.

## Common AI research errors
| Error | How to spot it |
|---|---|
| Fabricated or mismatched citations | The linked page does not contain the claim |
| Outdated facts | Source dates are old or missing |
| Blended figures | Numbers from different years or definitions combined |
| Over-generalisation | One study presented as consensus |
| Missing counter-evidence | No section on limitations or opposing views |

## Documenting AI use
Note in the research log which tool was used, the brief, the date and which claims were verified by a person. This makes the work reproducible and shows readers how much to trust each part. Where your organisation or publisher requires it, disclose AI assistance in the final output.

## Combining AI with human sources
Use AI findings to prepare sharper questions for experts and customers, then let interviews confirm or challenge them. The combination is faster than either alone and catches errors that both might miss.

Re-verify AI findings before reuse.

Keep briefs reusable.

## Edge cases and judgement calls
| Situation | What to do |
|---|---|
| Citation does not support the claim | Remove or correct; check other claims from the same output |
| Topic changes fast | Restrict dates; verify with the newest primary sources |
| Non-English markets | Ask for local-language sources; verify translations |
| Paywalled research | Use abstracts, press releases or library access; mark as partially verified |
| Confidential context | Use approved enterprise tools or remove sensitive details |
| Output too long | Ask for a one-page summary with the evidence table |

## Handoffs to related skills
- Planning: `research-planning`
- Source credibility: `source-evaluation`
- Claim checking: `fact-checking`
- Manual search: `desk-research`
- Academic reviews: `literature-review`
- Synthesis: `research-synthesis`

## Worked example
A strategy lead used a deep research tool to map the African payments market. The first report was 20 pages with 60 citations. Verification found that six key numbers came from vendor blogs, two citations did not mention the claimed figures and one market estimate was five years old. Follow-up prompts restricted sources to central banks, regulators and company filings; the lead checked the ten most important claims personally and wrote a three-page synthesis with confidence labels. Leadership used it to choose two markets for deeper study.

## Common mistakes
- Copying AI reports into decks without checking.
- Vague briefs that let the tool choose weak sources.
- Not asking for gaps and uncertainty.
- Trusting the number of citations as a sign of quality.
- Pasting confidential data into unapproved tools.

## Output format
```
1. Research brief
2. Tool used and settings
3. Key claims with verification results
4. Gaps and follow-up findings
5. Final synthesis with confidence labels
```

## Self-check before you answer
- Was the tool briefed with sources, scope and output format?
- Were key claims verified in the original sources?
- Are gaps and conflicts stated?
- Is the final synthesis written and checked by a person?

---
Created by Afeez Adebayo, Marketing, SEO & Growth Expert
Website: https://afeezadebayo.com
LinkedIn: https://www.linkedin.com/in/afeez-adebayo/
X: https://x.com/za_icon
Source: https://afeezadebayo.com/skills-md/productivity/research-learning/ai-assisted-research/

Licence: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). You may copy, share and adapt this skill, including for commercial use, as long as you credit Afeez Adebayo and link to the source URL above. Keep this notice in any copy or adapted version.