deep-research

name	deep-research
version	1.0.0
description	[Research] Use when deeply researching top sources from web-research.

[BLOCKING] Execute skill steps in declared order. NEVER skip, reorder, or merge steps without explicit user approval. [BLOCKING] Before each step or sub-skill call, update task tracking: set in_progress when step starts, set completed when step ends. [BLOCKING] Every completed/skipped step MUST include brief evidence or explicit skip reason. [BLOCKING] If Task tools are unavailable, create and maintain an equivalent step-by-step plan tracker with the same status transitions.

Quick Summary

Goal: Deep-dive into top sources, extract key findings, cross-validate claims, build structured evidence base.

Workflow:

1. Read source map — Load output from web-research step
2. Fetch top sources — WebFetch top 5-8 Tier 1-2 sources
3. Extract findings — Pull key facts, data points, quotes
4. Cross-validate — Compare findings across sources
5. Build evidence base — Structured findings with confidence scores

Key Rules:

• Maximum 8 WebFetch calls per invocation
• Every finding must cite specific source
• Conflicting claims → present both, flag discrepancy

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Deep Research

Step 1: Load Source Map

Read the source map from .claude/tmp/_sources-{slug}.md (output of web-research step).

Prioritize sources for deep-dive:

1. Tier 1-2 sources first
2. High-relevance sources
3. Sources covering identified gaps

Step 2: Fetch Top Sources

For each priority source (max 8):

1. Run WebFetch with the URL
2. Extract: key claims, data points, quotes, methodology
3. Note: publication date, author credentials, source type

Step 3: Extract Findings

For each source, extract:

• Key claims — factual statements with specific data
• Data points — numbers, percentages, dates
• Quotes — notable expert statements
• Methodology — how data was gathered (for market reports)

Step 4: Cross-Validate

Compare findings across sources:

• Agreement — 2+ sources say the same thing → high confidence
• Discrepancy — sources disagree → note both positions
• Unique — only 1 source → mark as "single source, unverified"

Step 5: Build Evidence Base

Write to .claude/tmp/_evidence-{slug}.md:

# Evidence Base: {Topic}

**Date:** {date}
**Sources analyzed:** {count}

## Findings

### Finding 1: {Title}

**Confidence:** {95%|80%|60%|<60%}
**Sources:** [1], [3]
**Content:** {finding with inline citations}
**Cross-validation:** {agreement/discrepancy notes}

## Unresolved Discrepancies

- {claim X from source A vs claim Y from source B}

## Gaps Remaining

- {what couldn't be verified}

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Workflow Recommendation

MANDATORY IMPORTANT MUST ATTENTION — NO EXCEPTIONS: If you are NOT already in a workflow, you MUST ATTENTION use AskUserQuestion to ask the user. Do NOT judge task complexity or decide this is "simple enough to skip" — the user decides whether to use a workflow, not you:

1. Activate research workflow (Recommended) — web-research → deep-research → synthesis → review
2. Execute /deep-research directly — run this skill standalone

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Next Steps

MANDATORY IMPORTANT MUST ATTENTION — NO EXCEPTIONS after completing this skill, you MUST ATTENTION use AskUserQuestion to present these options. Do NOT skip because the task seems "simple" or "obvious" — the user decides:

• "/business-evaluation (Recommended)" — Evaluate business viability from research
• "/knowledge-synthesis" — If synthesizing research report
• "Skip, continue manually" — user decides

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting.

External Memory: For complex or lengthy work (research, analysis, scan, review), write intermediate findings and final results to a report file in plans/reports/ — prevents context loss and serves as deliverable.

Evidence Gate: MANDATORY IMPORTANT MUST ATTENTION — every claim, finding, and recommendation requires file:line proof or traced evidence with confidence percentage (>80% to act, <80% must verify first).

AI Mistake Prevention — Failure modes to avoid on every task:

Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.

MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

Prompt-Enhance Closing Anchors

IMPORTANT MUST ATTENTION follow declared step order for this skill; NEVER skip, reorder, or merge steps without explicit user approval IMPORTANT MUST ATTENTION for every step/sub-skill call: set in_progress before execution, set completed after execution IMPORTANT MUST ATTENTION every skipped step MUST include explicit reason; every completed step MUST include concise evidence IMPORTANT MUST ATTENTION if Task tools unavailable, maintain an equivalent step-by-step plan tracker with synchronized statuses

Closing Reminders

MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting. MANDATORY IMPORTANT MUST ATTENTION validate decisions with user via AskUserQuestion — never auto-decide. MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality.

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.

[IMPORTANT] Analyze how big the task is and break it into many small todo tasks systematically before starting — this is very important.