Draco Research Promptgen

DRACO Research Prompt Generator

Transform vague research requests into prompts that maximise deep research agent performance, based on the DRACO benchmark methodology.

Core Principle: The Three Pillars

Every generated prompt MUST satisfy all three criteria simultaneously:

1. OBJECTIVITY

Clear, measurable success criteria where multiple experts would converge on what constitutes a correct answer.

Indicators of objectivity:

• Specific metrics, dates, or verifiable facts
• Named authoritative sources
• Documented information vs. opinions
• Deterministic outcomes

Red flags (make subjective):

• "Best", "should", "compelling", "interesting"
• Speculative future predictions
• Undefined quality judgments

2. BOUNDED/CONSTRAINED

Natural limits preventing endless expansion. Clear point where a complete answer has been given.

Good constraints:

• Specific number limits with objective ranking metrics ("top 5 by AUM", "3 most-cited papers")
• Time constraints ("2022–2025", "since Q3 2024")
• Geographic/domain limits ("in the EU", "for e-commerce")
• Named entities (not "top approaches" but "LoRA, full fine-tuning, and instruction tuning")

Pseudo-constraints to AVOID:

• Ungrounded "Top N" without objective metric ("top 5 challenges" — subjective)
• "Cite at least N sources" (different experts choose different sources)
• "Multiple studies" without naming which ones

3. CHALLENGING

Difficulty from complexity or synthesis, NOT from volume or tedium.

Good challenge sources:

• Synthesis across multiple named sources
• Multi-step reasoning or analysis
• Finding specific hard-to-locate information
• Domain expertise requirements

Bad (tedious, not challenging):

• Listing many items without analysis
• Kitchen-sink queries with 8+ deliverables
• Simple factual recall

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The Six Augmentation Dimensions

Apply systematically to transform vague queries:

CONTEXT Dimensions

| Dimension | Action | Example | |-----------|--------|---------| | Persona | Add professional role context | "As a buy-side analyst conducting due diligence..." | | Output | Specify deliverable format | "financial analysis research report", "comparative brief" | | Source | Add retrieval specificity | "Pull from SEC proxy statements", "based on WHO GLASS reports" |

SCOPE Dimensions

| Dimension | Action | Example | |-----------|--------|---------| | Temporal | Expand/bound time scope | "NVIDIA financials" → "NVIDIA financials 2022–2025" | | Cross-entity | Add comparative requirements | "CEO compensation at Google" → "CEO compensation at Google, Meta, and Apple" | | Geography | Expand/specify geographic scope | "AI landscape" → "global AI landscape, focusing on US and China" |

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Prompt Generation Workflow

Step 1: Parse the Request

Identify:

• Core research question
• Implicit constraints (if any)
• Domain/subject area
• Apparent depth requirement

Step 2: Apply Augmentation Checklist

For each dimension, determine if augmentation is needed:

□ PERSONA: Does specifying a professional role add clarity?
□ OUTPUT: Is the expected deliverable format clear?
□ SOURCE: Should specific authoritative sources be named?
□ TEMPORAL: Is timeframe bounded appropriately?
□ CROSS-ENTITY: Would comparison improve depth?
□ GEOGRAPHY: Is geographic scope clear and appropriate?

Step 3: Validate Three Pillars

Before finalising, verify:

□ OBJECTIVITY: Would two experts agree on what counts as correct?
□ BOUNDED: Is there a clear stopping point? Are "Top N" grounded?
□ CHALLENGE: Does difficulty come from synthesis, not volume?
□ DELIVERABLES: 3–5 focused items maximum, not kitchen-sink

Step 4: Structure the Output

Organise the prompt following this pattern:

[PERSONA CONTEXT if applicable]

[CORE RESEARCH QUESTION with all constraints]

[SPECIFIC REQUIREMENTS numbered 1–4, maximum 5]

[SOURCE SPECIFICITY — named authoritative sources]

[OUTPUT SPECIFICATION — format, structure expectations]

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Output Format

Present generated prompts in a clean, copy-ready format:

## Generated Research Prompt

[The optimised prompt]

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### Augmentations Applied
- [List which dimensions were added]

### Validation Notes
- Objectivity: [How verified]
- Boundedness: [Constraints applied]
- Challenge: [Source of complexity]

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Anti-Patterns to Avoid

| ❌ Avoid | Why | ✓ Instead | |----------|-----|-----------| | "Top 5 challenges" | Subjective ranking | "Top 5 challenges by regulatory citation frequency" | | "Cite at least 3 studies" | Non-deterministic | "Compare findings from [Study A] and [Study B]" | | "Analyse all aspects of X" | Unbounded | "Analyse [specific aspect 1], [aspect 2], [aspect 3]" | | "What's the best approach" | Subjective | "Compare approaches A, B, C on metrics X, Y, Z" | | Lists of 8+ deliverables | Volume, not challenge | Focus on 3–5 core elements | | "Recent research shows" | Vague temporality | "Research published 2023–2025 shows" |

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Example Transformations

Before: "Research private credit funds"

After: "Identify the top 5 private credit funds by AUM in North America as of Q4 2025. For each fund, document: (1) minimum investment threshold, (2) management fee structure, (3) target IRR range, and (4) primary sector focus. Source data from fund prospectuses, Preqin, and SEC filings."

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Before: "How is AI affecting healthcare?"

After: "Compare how computer vision systems have been adapted for automated breast cancer detection in mammography across FDA-cleared products (2020–2025). Report: (1) sensitivity/specificity thresholds required by FDA and EU MDR, (2) clinical trial results from at least 3 named trials, (3) current deployment scale in US hospital systems. Prioritise sources: FDA 510(k) clearance documents, peer-reviewed clinical validation studies, and manufacturer regulatory submissions."

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See references/transformation-examples.md for more domain-specific examples. See references/domain-patterns.md for domain-specific augmentation templates. See references/validation-checklist.md for the full quality validation checklist.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: ciaransaunders
• Source: ciaransaunders/Skills-Public
• License: MIT

Install and usage instructions live in the source repository linked above.