Resilient Research Workflow

Resilient Research-to-Spreadsheet Workflow

Use this skill when you must gather web-based information AND produce verified Excel workbooks, with particular emphasis on handling tool failures gracefully and proving final outputs against explicit criteria.

This skill combines:

• Phase A: Resilient web research with automatic failure detection and shell_agent delegation
• Phase B: Research data validation before spreadsheet integration
• Phase C: Anchored spreadsheet proof gate for workbook creation/editing
• Cross-phase gates: Explicit handoff criteria between research and spreadsheet phases

This is an end-to-end workflow skill. It requires:

• autonomous retry logic for web research (via shell_agent when needed)
• direct Python verification of research outputs
• deterministic spreadsheet proof methodology before finalizing

When to use

Use this skill when ANY of the following are true:

Research-phase triggers:

• You need current web-based data (prices, market info, competitor analysis, etc.)
• Prior search_web calls have failed or returned inconsistent results
• The task requires multi-step data collection from multiple sources
• You need resilient data gathering that can adapt to tool instability

Spreadsheet-phase triggers:

• You must create or modify an Excel workbook based on research data
• The user requires exact sheet names, columns, counts, or samples
• Prior summaries are inconsistent or not trustworthy
• Exact post-edit workbook state matters
• You must prove that mandatory criteria were satisfied

Both phases:

• A delegated agent may perform parts of the work
• Tool instability has been observed in the task context
• The task has failed previously due to tool errors

Core rules

Rule 1: Detect and escalate research failures

When search_web returns errors like:

• "unknown error"
• Empty or incomplete results
• Consistent failures across multiple queries (>2 failures)

Immediately delegate to shell_agent rather than retrying the same failing tool.

Rule 2: Never finalize from narrative summary alone

A spreadsheet task is only complete when:

1. The target workbook was identified from the anchored workspace path
2. Pre-edit structure matched the intended operation
3. The edit was performed on the correct file
4. The saved workbook was directly re-read from disk
5. Every requested criterion was checked in a deterministic verification report
6. Each criterion is marked as one of: PASS, FAIL, or UNAVAILABLE-IN-SOURCE
7. Any non-pass result is explicitly reconciled before finalizing

Rule 3: Workspace anchoring is absolute

All discovery, reads, writes, and verification must be anchored to the exact workspace path provided for the task.

• Treat the provided workspace path as the authoritative root
• Resolve workbooks to exact paths under that root
• Do not silently switch to similarly named files elsewhere
• Do not trust delegated tool reports without independent confirmation
• If the anchored file cannot be found, stop rather than guessing

Rule 4: Research criteria flow into spreadsheet criteria

The data you gather in Phase A becomes part of the verification criteria in Phase C. Track:

• What data was required vs. what was obtained
• Which sources were used
• Which data points could not be obtained (and why)
• How missing data affects spreadsheet requirements

Outcome contract

Your output should be based on proof, not inference.

For every task using this workflow, maintain these artifacts internally:

1. Research inventory: sources tried, data obtained, failures encountered
2. Pre-edit audit checklist: workbook structure before modification
3. Post-write proof checklist: deterministic verification of every spreadsheet criterion

The post-write proof checklist is decisive for spreadsheet claims. The research inventory is decisive for data coverage claims.

Workflow

Phase A: Resilient Web Research

Step A1: Attempt direct search

First, try search_web with your primary query:

search_web(query="your specific query with date/context")

Step A2: Detect failure patterns

Monitor for these failure signals:

• Return error messages ("unknown error", "connection failed", etc.)
• Empty results or clearly incomplete data
• Repeated failures on related queries

Failure threshold: If search_web fails 2+ times on the same or related queries, escalate to shell_agent.

Step A3: Delegate to shell_agent on failure

When failure threshold is reached, create a comprehensive shell_agent task:

shell_agent(
    task="""
    Gather [SPECIFIC DATA TYPE] for [SPECIFIC PURPOSE].
    
    Required information:
    1. [Item 1 with specificity - e.g., "Current WTI crude oil price as of today"]
    2. [Item 2]
    3. [Item 3]
    
    Success criteria:
    - Data from at least 2 independent sources
    - Timestamp for when data was collected
    - Source URLs for verification
    
    Handle errors by trying alternative approaches (different APIs, direct URL fetching, etc.)
    Provide structured output with source citations.
    """,
    timeout=300
)

Key task formulation principles:

• Specify the what (data needed) not the how (specific tools to use)
• Include explicit success criteria and output format expectations
• Allow sufficient timeout for multi-step execution (300+ seconds typical)
• Let shell_agent decide whether to use Python, curl, requests, or other approaches

Step A4: Verify research results

Check shell_agent output for:

• Complete data collection (not partial results)
• Multiple sources cited (indicates thorough searching)
• Structured, usable output format
• Evidence of error handling (mentions of retry attempts, alternatives tried)

Gate A: Do not proceed to Phase B until you have verified research results OR have explicitly documented what data could not be obtained and why.

Phase B: Research Data Validation

Before using research data in spreadsheet work, validate it:

Check B1: Data completeness

For each required data point:

• Was it obtained? If yes, mark PASS. If no, mark UNAVAILABLE-IN-SOURCE with reason.
• Is the data recent enough for the task requirements?
• Are the sources credible and verifiable?

Check B2: Data consistency

If multiple sources were used:

• Do the values align within reasonable tolerance?
• If there are discrepancies, which source takes precedence?
• Document any reconciliation decisions.

Check B3: Map to spreadsheet criteria

Translate research data into explicit spreadsheet criteria:

• Which sheets will contain this data?
• Which columns need to be populated?
• What formulas or calculations derive from this data?
• What validation rules apply?

Gate B: Do not proceed to Phase C until you have a clear mapping from research data to spreadsheet criteria.

Phase C: Spreadsheet Proof Gate

Step C1: Discover candidate workbooks

Search under the exact workspace root for plausible Excel files:

• .xlsx, .xlsm, .xls

Prefer files that:

• Match names mentioned by the user
• Live in likely data/output/project folders
• Have relevant modification times
• Contain expected sheet names

If several files are plausible, inspect all before choosing.

Step C2: Build explicit criteria list

Before editing, convert requirements into checkable criteria:

Possible criterion types:

• required-sheet: <name> exists
• required-column: Sheet <name> has column "<column>"
• data-populated: Column <X> in Sheet <Y> has values for all data rows
• formula: Column <Z> contains formulas for all populated rows
• row-count: Sheet <name> has exactly N data rows
• preservation: Source sheet <name> still exists
• research-derived: Data from <source> appears in <location>

Good examples:

• required-sheet: Summary exists
• required-column: Sheet Sample has column "Selected"
• row-count: exactly 25 marked rows in Sample
• research-derived: WTI price from shell_agent appears in Summary!B2

Bad examples:

• workbook looks right
• sampling seems okay
• most tabs present

Step C3: Pre-edit audit

Before any write, inspect the workbook structure:

1. Confirm exact anchored path
2. List all sheet names
3. Identify target sheets
4. Inspect headers
5. Count relevant rows
6. Note formulas, merged cells, tables, filters, protections, or macros if relevant
7. Confirm whether required columns exist already or must be created
8. Confirm whether the planned edit is structurally safe

Identity consistency check: If you inspect the workbook multiple times or with multiple tools, the inspections must agree on path, sheet names, row counts, and headers. If they disagree, treat workbook identity as unconfirmed.