accounting-finance-system-research

Research and solve "how do I do this?" questions inside accounting and finance software systems (ERP, GL, AP/AR, billing, close, and reporting tools). Use when a user needs operational steps, setup guidance, or troubleshooting help in a specific system and wants the result documented as a quick memo or simple Q-and-A DOCX.

Safety Notice

This listing is from the official public ClawHub registry. Review SKILL.md and referenced scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "accounting-finance-system-research" with this command: npx skills add ChipmunkRPA/accounting-finance-system-skill

Accounting And Finance System Research

Overview

Follow a fixed process for system-how-to support: collect facts, ask clarifying questions, confirm output format, confirm understanding, research external guidance, analyze the best path, and generate a DOCX deliverable.

Required Behavior

  • Ask clarifying questions before proposing a solution.
  • Confirm whether output should be quick memo or simple q-and-a.
  • Restate understanding and wait for confirmation before web research.
  • Research the internet after confirmation, prioritizing official vendor guidance.
  • Separate source-backed guidance from assumptions or inference.
  • Include source links and accessed dates in the deliverable.
  • Generate a DOCX report in the user-selected format.

Workflow

1) Intake And Scope

  • Capture the user objective in one sentence.
  • Confirm system name and version/edition (for example: NetSuite, SAP S/4HANA Cloud, Dynamics 365 Finance, QuickBooks).
  • Confirm module or workflow area (for example: AP, AR, close, reconciliations, reporting).
  • Confirm role/permission constraints and any deadline pressure.

2) Clarification Questions (Mandatory)

  • Use references/clarification-question-bank.md.
  • Ask only missing critical questions; avoid redundant prompts.
  • Pause solutioning until enough facts are available.
  • If facts remain unknown, continue with explicit assumptions and conditional guidance.

3) Output Format Confirmation (Mandatory)

  • Ask the user to choose one:
  • quick memo: concise professional summary with recommendation and steps.
  • simple q-and-a: direct answer format with numbered actions.
  • Default to quick memo only when user gives no preference.

4) Understanding Confirmation (Mandatory)

  • Restate:
  • problem statement
  • system context
  • open questions or assumptions
  • chosen output format
  • Ask for explicit confirmation before researching.

5) Research External Guidance

  • Follow source ranking in references/source-priority.md.
  • Gather at least two relevant sources where possible.
  • Include at least one official vendor source when available.
  • Track per-source metadata: title, publisher, URL, updated/published date if available, accessed date.
  • Prefer current version-specific guidance over older generic content.

6) Analyze And Build Recommendations

  • Translate research into concrete user actions.
  • Provide prerequisites and permissions needed for each action.
  • Add fallback steps when primary path is blocked.
  • Include validation checks to confirm completion.
  • Call out risks and unresolved dependencies.

7) Generate DOCX Deliverable

python scripts/build_system_guidance_docx.py \
  --input-json <analysis.json> \
  --output-docx <system-guidance.docx> \
  --format <memo|q-and-a>
  • Map quick memo to memo.
  • Map simple q-and-a to q-and-a.
  • Confirm the document includes:
  • request summary and system context
  • clarifications and assumptions
  • guidance sources with URLs
  • recommended steps
  • validation checks
  • risks and open items

8) Quality Check

  • Verify recommendations are consistent with cited guidance.
  • Verify assumptions are explicit and easy to review.
  • Verify deliverable format matches user request.
  • Verify every source has a URL and accessed date.
  • Verify output file is .docx and readable.

Resources

Dependency

Install once if needed:

python -m pip install --user python-docx

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

Research

Ontology Engineer

Extract candidate ontology models from enterprise business systems AND build/maintain personal knowledge graphs from any file system. Use when: ontology extr...

Registry SourceRecently Updated
Research

alias

Use this skill to write complete, formatted academic graduation research papers and projects for the College of Computer Science and Mathematics at Tikrit Un...

Registry SourceRecently Updated
Research

competitive analysis

Provides a systematic competitive analysis framework based on Zhang Zaiwang's methodology, guiding goal-driven, structured market and product competitor eval...

Registry SourceRecently Updated
70Profile unavailable
Research

test

Contract clause analysis, risk flagging, renewal tracking, and obligation extraction for business agreements. Use when you need to review vendor contracts, s...

Registry SourceRecently Updated
380Profile unavailable