# Find missing fields in active matter records

Canonical page: https://agents.paretoid.com/workflows/find-missing-fields-in-active-matter-records/

Category: Operations & Reporting

Practice relevance: cross-practice. Useful supporting administrative method; no claim of practice-specific legal instructions.

Jurisdiction/provider scope: Clio custom-field configuration; firm-approved completeness rules, not jurisdictional filing requirements.

Compare active matters with practice-specific approved field rules.

Status: Proposed / not tested. The public source describes the problem. Documentation supports only the stated method components; no result from this recipe has been verified.

Verification: Source methods and reported problems have been reviewed. We have not run the adapted workflow. The sample below describes expected behavior on synthetic data, not a customer result.

## The problem

Compare active matters with practice-specific approved field rules.

Why it matters: Missing or inconsistent fields can disrupt reporting and later handoffs. A rule-linked exception list directs the data owner to the affected records without guessing values or changing matter status.

## Sources and evidence

- pain: [Pain evidence: Cut our losses and dump case management software?](https://www.reddit.com/r/LawFirm/comments/1tukoq5/cut_our_losses_and_dump_case_management_software/)
  Cut our losses and dump case management software?, 2026-06-02, older. In a five-lawyer firm, partial adoption leaves party details, status, tasks and other data unfilled even though the system is used for time and invoices.

- method: [Method: Clio custom fields](https://help.clio.com/hc/en-us/articles/9285496802331-Create-Custom-Fields-in-Clio-Manage)
  Clio custom fields supports custom field sets and required/default fields. Administrators control configuration; this recipe audits exported records rather than changing requirements live.

Source checked: October 15, 2026. Pain accounts are self-reported. Documentation supports components; this adapted recipe and prompt have not been tested.

## Suggested approach

Start when: Weekly data-quality review

1. compare active matter records with an approved per-practice field checklist

2. Keep source references and report unknowns instead of filling gaps.

3. The responsible reviewer checks the report before any separately approved action.

## What you need

- Authorized view of selected Clio Manage matters and their Custom Fields.

- Practice/status-specific required-field rules approved by the firm, with rule version and scope.

- Firm-approved Excel; optional Copilot entitlement and tenant approval for the exact minimized data. Native Excel analysis can be done manually if Copilot is absent.

- Keep raw exports and identifying source pointers in a separate restricted location. The AI workbook contains only approved alias-based tables and visible policy/scope text, never raw client records on another tab.

- Use synthetic inputs first. Keep real data in firm-approved accounts and processing, with appropriate access, confidentiality and retention controls. Aliases alone do not anonymize records. Never paste credentials, API keys or unnecessary client details.

## How to use

Documentation-checked proposed route; source collection and human approval required

- Current official matter documentation supports the Dashboard and Custom Fields views. The older Filter/Export/Convert article now redirects to Convert Matters; this route does not rely on its stale cached export menu.

- This is manual capture of a bounded matter set, not a firm-wide data-quality certificate. Blank, hidden, not applicable and inaccessible are distinct.

Access and setup:

- Actual account access, plan and source-data completeness have not been tested.

### 1. Read the actual matter fields

Tool: Clio Manage

Location: Matters > chosen matter > Dashboard Details and Custom Fields

For each matter in the approved scope, inspect status, practice area, responsible owner and each field named in the approved rules. Record the observed value and source location; if hidden/inaccessible, record that condition rather than a blank. No editing is needed.

Expected output: Observed field values for the explicitly enumerated matter set.

Next step: Create the long-form alias-based matter table in Excel.

Check before continuing: Check that every in-scope matter and applicable field was visited. Missing visibility is a coverage gap.

Execution status: Official documentation checked 2026-10-15; account and workflow not personally tested

Step documentation: https://help.clio.com/hc/en-us/articles/9285920226075-Get-Started-With-Matters

### 2. Map the observed records to the starter input

Tool: Excel and authorized staff

Location: Separate analysis workbook > Home > Format as Table

Create matters.csv one row per matter_alias/field_name, copying practice_type,owner_alias,status,field_value and a stable source_row reference. From the approved policy create field-rules.csv with rule_id,practice_type,applicable_status,field_name,required,allowed_values,rule_version. Paste scope.txt into Scope, including inaccessible fields and whether blanks mean absent or unobserved. Create named tables for Matters and FieldRules. Put the policy and review scope in visible worksheets or paste them into the next prompt.

Expected output: Matters and FieldRules tables matching the kit; values are manually observed, not generated by AI.

Next step: Check the mapping against each original source before using AI.

Check before continuing: Aliases and missing policy fields are staff-created; do not relabel a native export as the kit schema. Unknown stays blank/unknown, not false or zero.

Execution status: Official documentation checked 2026-10-15; account and workflow not personally tested

Step documentation: https://support.microsoft.com/en-us/excel/tutorial-import-data-into-excel-and-create-a-data-model

### 3. Review the bounded evidence with Copilot

Tool: Excel Copilot, optional

Location: Approved analysis workbook > Copilot icon at lower right > Chat only

Use Chat only and submit the prompt. Without Copilot: filter by practice/status applicability and compare each observed value to the approved rule.

Prompt:

```text
Apply FieldRules to Matters within Scope. Return matter_alias, field_name, rule_id/version, observed_value, issue and source_row. Flag applicable required blanks, disallowed values and contradictory duplicate records. Separate not applicable and unobserved/inaccessible from truly missing. Do not invent field values, choose matter status, decide legal requirements or edit records. List untested matters/fields.
```

Expected output: Rule-linked data-quality exceptions with explicit coverage.

Next step: Copy the draft exception list to the reviewer; retain row references.

Check before continuing: Check every flagged row and the scope. A fluent answer is not evidence of completeness; no automatic workbook or source-system edits.

Execution status: Official documentation checked 2026-10-15; account and workflow not personally tested

Step documentation: https://support.microsoft.com/en-us/excel/copilot/get-started-with-copilot-in-excel https://support.microsoft.com/en-us/excel/copilot/frequently-asked-questions-about-copilot-in-excel

### 4. Approve the review result

Tool: Responsible staff reviewer

Location: Reviewed local worksheet

The matter owner verifies each flagged field against the source and approves any correction separately. Keep unknown/inaccessible fields unresolved.

Expected output: Reviewed field-quality checklist and coverage note.

Next step: Any external message, source change, payment or deletion requires its own authorized process.

Check before continuing: An empty exceptions list means no issue found in the inspected fields, not that every matter is complete.

Execution status: Official documentation checked 2026-10-15; account and workflow not personally tested

Step documentation: https://support.microsoft.com/en-us/excel/tutorial-import-data-into-excel-and-create-a-data-model

## What you will get

matter-field-review.csv: matter_alias, field_name, rule_id, exception_type, observed_value, allowed_value_or_requirement, source_row, owner_alias, uncertainty. Distinguish missing, invalid and conflicting values; do not fill gaps.

## Human review and limits

Matter owner confirms corrections. Test optional fields, a stale status and a requirement that applies only to another practice area. This is ongoing record hygiene, distinct from A17 migration and G09 initial matter opening.

The assistant drafts or reports only. Check source records and review the output before a human performs any separately approved send or change. No automatic legal decision, money movement, account connection or publication is included.

What to measure: In a synthetic pilot, count correctly found exceptions, false alarms, and unresolved inputs. No time or cost saving is assumed.

## Original prepared-input schema

matters.csv: matter_alias, practice_type, owner_alias, status, field_name, field_value, source_row

field-rules.csv: rule_id, practice_type, applicable_status, field_name, required, allowed_values, rule_version; scope.txt: export cutoff, coverage and data-owner review

Synthetic example input:

```text
M1: required field missing
M2: optional field blank
M3: requirement belongs to another practice
```

Expected synthetic output:

```text
M1: exception with rule ID
M2: no required-field exception
M3: rule does not apply
```

Failure check: Matter owner confirms corrections. Test optional fields, a stale status and a requirement that applies only to another practice area.

## Starter files

Native blank scaffolds and original synthetic examples may use different schemas. Follow NATIVE-INPUT-MAPPING where supplied. These files do not connect accounts or install automation.

- [Download starter kit](https://agents.paretoid.com/assets/starter-kits/s07-starter-kit.zip) — All inputs, synthetic examples and review notes in one ZIP. No automation is installed.

- [Start here: get the sources and prepare the review](https://agents.paretoid.com/assets/starter-kits/s07/START-HERE.txt) — Documentation-checked acquisition, explicit manual mapping, exact prompts and human review limits

- [matters.csv](https://agents.paretoid.com/assets/starter-kits/s07/matters.csv) — Blank input template with exact recipe headers.

- [matters.example.csv](https://agents.paretoid.com/assets/starter-kits/s07/matters.example.csv) — Separate synthetic fixture input. Do not mix these rows into real exports.

- [field-rules.csv](https://agents.paretoid.com/assets/starter-kits/s07/field-rules.csv) — Blank input template with exact recipe headers.

- [field-rules.example.csv](https://agents.paretoid.com/assets/starter-kits/s07/field-rules.example.csv) — Separate synthetic fixture input. Do not mix these rows into real exports.

- [scope.txt](https://agents.paretoid.com/assets/starter-kits/s07/scope.txt) — Blank text input worksheet. Fill its fields with approved evidence; no default assumptions are supplied.

- [scope.example.txt](https://agents.paretoid.com/assets/starter-kits/s07/scope.example.txt) — Separate synthetic text input fixture; use with the example CSV files only.

- [Expected fixture findings](https://agents.paretoid.com/assets/starter-kits/s07/expected-fixture-result.txt) — Read-only expected output and failure conditions for the included synthetic input files.

- [Setup and review checklist](https://agents.paretoid.com/assets/starter-kits/s07/README.txt) — Recipe-specific prerequisites, file mapping, prompt, setup steps, checklist and limits.

## Optional original prepared-input prompt

Destination: Your firm-approved AI assistant · prepared files

This original prompt uses its own prepared-input schema. Do not mix it with native-step tables without the supplied mapping.

```text
Check this deidentified matter export against the supplied field requirements for each practice type. Return matter ID, field, rule violated, observed value, source row and assigned data owner. Distinguish missing, invalid and conflicting data. Do not fill gaps from guesses or public searches, decide case status, merge records or change the live system.

INPUTS
matters.csv: matter_alias, practice_type, owner_alias, status, field_name, field_value, source_row
field-rules.csv: rule_id, practice_type, applicable_status, field_name, required, allowed_values, rule_version; scope.txt: export cutoff, coverage and data-owner review

OUTPUT
matter-field-review.csv: matter_alias, field_name, rule_id, exception_type, observed_value, allowed_value_or_requirement, source_row, owner_alias, uncertainty. Distinguish missing, invalid and conflicting values; do not fill gaps.

Use only these synthetic or firm-approved inputs and preserve source row/page IDs. Keep missing or conflicting evidence unresolved. Return a draft for the named reviewer. Do not send messages, connect accounts, change records or permissions, move money, or make legal decisions. Keep source files unchanged. List missing prerequisites before continuing.
```

Proposed / not tested · editorial prompt

Published by Law Firm Agents. Proposed adaptation; not tested. Not legal advice.