Find missing fields in active matter records
Compare active matters with practice-specific approved field rules.
Tools for the documented steps
Practice relevance
Cross-practice idea · Useful supporting administrative method; no claim of practice-specific legal instructions.
Scope: Clio custom-field configuration; firm-approved completeness rules, not jurisdictional filing requirements.
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 & evidence
Proposed / not tested. The public source describes the problem. Documentation supports only the stated method components; no result from this recipe has been verified.
What’s been verified
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.
What to measure: In a synthetic pilot, count correctly found exceptions, false alarms, and unresolved inputs. No time or cost saving is assumed.
- Pain evidence: 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: Clio custom fields ↗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. We wrote these prompts. The adapted workflow hasn’t been tested.
Suggested approach
Start when: Weekly data-quality review
- compare active matter records with an approved per-practice field checklist
- Keep source references and report unknowns instead of filling gaps.
- The responsible reviewer checks the report before any separately approved action.
Limits and review
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.
Who reviews it: 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.
What you need
Your firm-approved AI assistant · prepared files
- 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.
Check access and setup
- Actual account access, plan and source-data completeness have not been tested.
Read the actual matter fields
Clio Manage · 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.
Map the observed records to the starter input
Excel and authorized staff · 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.
Review the bounded evidence with Copilot
Excel Copilot, optional · 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.
- 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.
Approve the review result
Final human reviewResponsible staff reviewer · 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.
What you’ll 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.
Inputs and a sample test Synthetic example · not a measured result
Input files
- 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
M1: required field missing M2: optional field blank M3: requirement belongs to another practice
Expected output
M1: exception with rule ID M2: no required-field exception M3: rule does not apply
Test a failure
Matter owner confirms corrections. Test optional fields, a stale status and a requirement that applies only to another practice area.
Try with the sample files
Follow the tool steps above and use the inputs named in each step. Where provided, native-* files are blank scaffolds and NATIVE-INPUT-MAPPING explains their fields. Original examples and the optional full review prompt use a separate prepared-input schema. Keep them separate unless the mapping explicitly connects them. Downloading a kit does not connect accounts or prove the workflow works.
Download inputs and checklist 10 files
Instructions, blank templates and separate synthetic examples; these files do not install an automation. Blank templates still need verified source data.
- Download starter kit All inputs, synthetic examples and review notes in one ZIP. No automation is installed.
- Start here: get the sources and prepare the review Documentation-checked acquisition, explicit manual mapping, exact prompts and human review limits
- matters.csv Blank input template with exact recipe headers.
- matters.example.csv Separate synthetic fixture input. Do not mix these rows into real exports.
- field-rules.csv Blank input template with exact recipe headers.
- field-rules.example.csv Separate synthetic fixture input. Do not mix these rows into real exports.
- scope.txt Blank text input worksheet. Fill its fields with approved evidence; no default assumptions are supplied.
- scope.example.txt Separate synthetic text input fixture; use with the example CSV files only.
- Expected fixture findings Read-only expected output and failure conditions for the included synthetic input files.
- Setup and review checklist Recipe-specific prerequisites, file mapping, prompt, setup steps, checklist and limits.
Optional full review prompt for prepared inputs
Prepared-input review prompt with Your firm-approved AI assistant · prepared files
Proposed / not tested · editorial prompt. This prompt uses the original prepared-input schema shown in the sample test. Step prompts may use different tables. Follow NATIVE-INPUT-MAPPING where supplied; do not mix the original examples with native-step inputs without mapping and checking every field.