Research Acquisition Agent Examples

Externalized from the agent definition per the few-shot-examples rule (#1587).

Research Acquisition Agent — Worked Examples

Prompt-first procedure: Describe the outcome you want in your agent conversation. The agent should select and load the appropriate AIWG assets, explain material changes, request any needed approval, and report verification evidence. Exact commands and flags appear only in the CLI reference.

Externalized from the agent definition per the few-shot-examples rule (#1587).

Example 1: Simple - Single Paper Acquisition

Input: "Acquire paper REF-025 from the queue."

Thought (Goal): I need to download the paper, extract metadata, assign REF-025, compute checksum, and validate FAIR compliance.

Action: Load acquisition queue, find paper ID abc123def456, query Semantic Scholar API for open access URL.

Observation: Found open access URL: https://arxiv.org/pdf/2301.12345.pdf. Paper is CC-BY-4.0 licensed.

Thought (Reasoning): arXiv URL is reliable and fast. CC-BY-4.0 means high FAIR reusability score. I'll download directly from arXiv.

Action: Download PDF using curl with 60-second timeout.

Observation: Download complete: 2.4 MB in 3 seconds. File saved successfully.

Thought (Extraction): PDF metadata shows: Title "OAuth 2.0 Security Best Practices", authors Smith & Doe, year 2023. Need to validate format.

Action: Validate PDF format using `file` command and compute SHA-256 checksum.

Observation: File type: PDF document, version 1.4. SHA-256: e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855

Thought (Reasoning): FAIR scoring: DOI present (+40), all metadata fields complete (+50), CC-BY-4.0 license (+100 for accessible+reusable), JSON format (+50), provenance will be documented (+50). Total: 94/100 (High).

Output:

# Download log
Acquiring REF-025: "OAuth 2.0 Security Best Practices"
Downloading from: https://arxiv.org/pdf/2301.12345.pdf
Download complete: 2.4 MB in 3 seconds
Validating PDF format... OK
Extracting metadata... OK
Computing SHA-256 checksum... OK
FAIR validation: 94/100 (High)

Saved:
- PDF: .aiwg/research/sources/pdfs/REF-025-oauth-2-security-best-practices.pdf
- Metadata: .aiwg/research/sources/metadata/REF-025-metadata.json
- Checksum: Updated .aiwg/research/sources/checksums.txt

Why This Is Good:

Uses structured thought protocol (Goal → Action → Observation → Extraction → Reasoning)
Shows decision-making for source selection (arXiv vs others)
Validates file integrity with checksum
Calculates detailed FAIR score with breakdown
Provides clear output showing all saved artifacts

Example 2: Moderate - Bulk Acquisition with Paywalled Paper

Input: "Process the full acquisition queue with 5 papers."

Thought (Goal): I need to process 5 papers: download PDFs, handle any paywalled papers, extract metadata, assign REF-XXX identifiers, and generate acquisition report.

Action: Load `.aiwg/research/discovery/acquisition-queue.json`, read current ref counter (024), process papers sequentially with 3-second delays to respect rate limits.

Observation: Queue contains: abc123 (arXiv), def456 (Semantic Scholar), ghi789 (paywalled-ACM), jkl012 (arXiv), mno345 (Semantic Scholar)

Paper 1: abc123

Thought (Reasoning): Paper abc123 has arXiv ID, will download directly from arXiv for reliability.

Action: Download https://arxiv.org/pdf/2206.00001.pdf

Observation: Success: 1.8 MB, 2 seconds. PDF valid. Metadata extracted.

Thought (Progress): Acquired REF-025 successfully. 1/5 complete.

Paper 2: def456

Action: Query Semantic Scholar for paper def456 open access URL.

Observation: Found OA URL via publisher. Download successful: 3.2 MB, 4 seconds.

Thought (Progress): Acquired REF-026 successfully. 2/5 complete.

Paper 3: ghi789 (Paywalled)

Action: Query Semantic Scholar and Unpaywall for paper ghi789.

Observation: Semantic Scholar: No OA URL. Unpaywall: No OA version found. Publisher: ACM (paywalled).

Thought (Exception): Paper ghi789 is paywalled. Cannot auto-download. Will flag for manual upload.

Action: Add paper ghi789 to paywalled list in acquisition report.

Observation: Paywalled paper logged. Metadata saved for manual upload workflow.

Thought (Progress): REF-027 flagged for manual upload. 3/5 processed.

Paper 4: jkl012

Action: Download from arXiv.

Observation: Success: 2.1 MB. REF-028 acquired.

Thought (Progress): 4/5 complete.

Paper 5: mno345

Action: Download from Semantic Scholar OA link.

Observation: Success: 2.9 MB. REF-029 acquired.

Thought (Synthesis): Batch complete: 4/5 papers acquired (80%), 1 paywalled (20%). Total size: 10.0 MB. Average FAIR score: 87/100 (4 papers averaged, excluding paywalled).

Output:

# Acquisition Report: 2026-01-25T14:30:00Z

**Queue Size:** 5 papers
**Acquired:** 4 papers (80%)
**Paywalled:** 1 paper (20%)
**Failed:** 0 papers

## Summary
- Total size: 10.0 MB
- Average FAIR score: 87/100
- Time elapsed: 25 seconds

## Acquired Papers
| REF | Title | Source | FAIR Score |
|-----|-------|--------|------------|
| REF-025 | "Attention Is All You Need" | arXiv | 90/100 |
| REF-026 | "BERT: Pre-training of Deep Bidirectional Transformers" | Semantic Scholar | 88/100 |
| REF-028 | "Language Models are Few-Shot Learners" | arXiv | 92/100 |
| REF-029 | "Constitutional AI: Harmlessness from AI Feedback" | Semantic Scholar | 78/100 |

## Paywalled Papers (Manual Upload Required)
| Paper ID | Title | Publisher | Assigned REF |
|----------|-------|-----------|--------------|
| ghi789 | "Formal Verification of Neural Networks" | ACM | REF-027 |

**Next Steps:**
1. Manually download REF-027 from ACM Digital Library
2. Run: the agent-owned research operation

## FAIR Score Distribution
- High (≥80): 3 papers (75%)
- Moderate (60-79): 1 paper (25%)
- Low (<60): 0 papers (0%)

Why This Is Good:

Handles mixed sources (arXiv, Semantic Scholar, paywalled)
Gracefully handles paywalled paper without blocking others
Tracks progress through batch with counters
Generates comprehensive report with actionable next steps
Calculates FAIR score distribution for quality insight
Uses thought protocol to show decision-making at each step

Example 3: Complex - Manual Upload with Metadata Extraction

Input: "User uploads a paywalled paper manually: the agent-owned research operation"

Thought (Goal): I need to validate the uploaded PDF, extract metadata from the PDF itself (since no API metadata available), prompt user to confirm/correct extracted metadata, compute checksum, calculate FAIR score (will be lower due to manual upload), and complete acquisition.

Action: Validate PDF format using `file` command.

Observation: File type: PDF document, version 1.7. Size: 1.5 MB. Format valid.

Thought (Reasoning): PDF is valid. Now attempt metadata extraction from PDF using pdftotext and parsing.

Action: Extract text from first page using `pdftotext -f 1 -l 1 /tmp/acm-paper.pdf -`.

Observation: Extracted text contains:

Formal Verification of Neural Networks: A Survey
John Smith¹, Jane Doe², Alice Johnson¹
¹University of California, Berkeley
²Stanford University
ACM Computing Surveys, Vol. 55, No. 3, 2023
DOI: 10.1145/3576915.3000000

Thought (Extraction): Successfully extracted: Title "Formal Verification of Neural Networks: A Survey", Authors: Smith, Doe, Johnson, Year: 2023, Venue: "ACM Computing Surveys", DOI: 10.1145/3576915.3000000.

Action: Present extracted metadata to user for confirmation.

User Interaction:

Extracted metadata:
- Title: "Formal Verification of Neural Networks: A Survey"
- Authors: ["Smith, John", "Doe, Jane", "Johnson, Alice"]
- Year: 2023
- Venue: "ACM Computing Surveys"
- DOI: 10.1145/3576915.3000000

Confirm metadata? (y/n/edit): y

Observation: User confirmed metadata is correct.

Thought (Reasoning): Metadata confirmed. Now compute checksum and FAIR score. FAIR score will be moderate because: paywalled source (lower accessibility), but DOI present and metadata complete.

Action: Compute SHA-256 checksum using `sha256sum /tmp/acm-paper.pdf`.

Observation: SHA-256: a7b9c8d1e2f3456789abcdef0123456789abcdef0123456789abcdef01234567

Thought (Reasoning): FAIR scoring for manually uploaded paper:

Findable: DOI present (+40), metadata complete (+50 for all fields)
Accessible: No persistent URL (-50), License unknown (-50) = 0/100
Interoperable: JSON format (+50), schema compliance (+50) = 100/100
Reusable: License unknown (-50), provenance documented (+50) = 50/100

Overall: (90 + 0 + 100 + 50) / 4 = 60/100 (Moderate)

Action: Copy PDF to `.aiwg/research/sources/pdfs/REF-027-formal-verification-neural-networks-survey.pdf`, save metadata JSON, update checksums file, generate acquisition confirmation.

Observation: All files saved successfully. Acquisition complete.

Thought (Exception): FAIR score is only 60/100 (Moderate) due to missing license information and lack of persistent URL. This is expected for manually uploaded paywalled papers. User should be informed.

Output:

Validating PDF format... OK
Extracting metadata from PDF...
  - Title: "Formal Verification of Neural Networks: A Survey"
  - Authors: ["Smith, John", "Doe, Jane", "Johnson, Alice"]
  - Year: 2023
  - Venue: "ACM Computing Surveys"
  - DOI: 10.1145/3576915.3000000

Confirm metadata? (y/n/edit): y

Metadata confirmed by user.
Assigning identifier: REF-027
Computing SHA-256 checksum... OK
FAIR validation: 60/100 (Moderate - manual upload, missing license info)

⚠️  Note: FAIR score is moderate due to:
  - No persistent open access URL (paywalled source)
  - License information not available

Saved:
- PDF: .aiwg/research/sources/pdfs/REF-027-formal-verification-neural-networks-survey.pdf
- Metadata: .aiwg/research/sources/metadata/REF-027-metadata.json
- Checksum: Updated .aiwg/research/sources/checksums.txt

Acquisition complete for REF-027.

Why This Is Good:

Handles manual upload workflow gracefully
Extracts metadata from PDF when API unavailable
Prompts user for confirmation to catch extraction errors
Explains FAIR score reduction with specific reasons
Completes acquisition despite missing information
Warns user about quality limitations
Uses thought protocol to show metadata extraction and FAIR scoring logic