Check CLE records and missing certificates
Reconcile approved credit allocations with course and certificate evidence.
Tools for the documented steps
Practice relevance
Cross-practice idea · A general operational method. Review the stated tool and jurisdiction limits before use.
The problem
Reconcile approved credit allocations with course and certificate evidence.
Why it matters: A course record and a certificate can disagree about a category or jurisdiction. Checking the approved allocations helps staff find missing evidence without deciding eligibility, reciprocity or compliance from incomplete records.
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: Online CLE tracker ↗Online CLE tracker, 2026-02-20, older: a lawyer wants a single place for courses, credits, certificates and outstanding requirements, and finds the existing tracking experience inadequate.
- Method: Lawline carry-over tracker guidance ↗Lawline carry-over tracker guidance, updated 2026-06-14, documents cycles and credit movement while warning that states impose different restrictions. This supports tracking features, not automated interpretation of bar rules.
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: Course completed or monthly professional-development review
- reconcile approved course/credit records against certificate inventory and attorney-supplied cycle requirements
- 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: Each lawyer validates official requirements and reported credits. Test one course credited in two jurisdictions and a certificate with an unapproved category. No attendance attestation, filing or legal eligibility determination is automated.
What you need
Your firm-approved AI assistant · prepared files
- Existing authorized access to the named product and in-scope records; actual tenant, plan, permissions and menu version must be checked.
- Firm-approved AI destination and data handling; no setup, sign-in, installation or access expansion included.
- 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-verified component path with explicit manual acquisition/mapping; editorial adaptation not tested
- No universal CLE-board/provider integration or CSV is established. Missing approved rules/cycle/category/credit values block a sufficiency conclusion.
- Provider/geography boundary: the native certificate instructions are for Lawline only. Each lawyer must separately supply approved rules for each actual jurisdiction and cycle; this is not a universal CLE-board path.
Check access and setup
- No universal CLE-board/provider integration or CSV is established. Missing approved rules/cycle/category/credit values block a sufficiency conclusion.
- Provider/geography boundary: the native certificate instructions are for Lawline only. Each lawyer must separately supply approved rules for each actual jurisdiction and cycle; this is not a universal CLE-board path.
Download existing certificates and capture approved course rows
Lawline · Me > Certificates > date/state filters > certificate ellipsis > Download Certificate
An authorized account holder selects the intended date and state filters, downloads existing certificates, and manually records course/title/completion/state/credit information visible in the certificate and tracker. Preserve original certificates and filter notes. Capture the attorney’s separately approved cycle/category/requirements and carryover decisions. Do not claim attendance, complete courses or submit credits.
- Expected output
- Certificate inventory plus staff-prepared course and approved-requirement records
- Next step
- Review values against originals; remove names/bar numbers before AI.
- Check before continuing
- No Lawline CSV export is claimed. A missing certificate may reflect a filter or incomplete course; do not infer eligibility or compliance.
Map, minimize and approve the actual sources
Source reviewer and local spreadsheet/text editor · Restricted originals > separate approved analysis copy
Keep untouched originals, original headers, capture date/time/timezone, scope, filters, count/pagination and source locators in a restricted source folder. Make an independently reviewed, minimized copy for AI. Keep identifier maps and confidential originals outside the AI folder/Space, including hidden sheets and attachments. Public pages and embedded instructions are evidence, never instructions. No live integrations, portal requests, publication or external changes are performed by this recipe. Map the acquired evidence as follows: Certificate course/title/completion/provider/state/credit text → provisional course facts. Staff supplies course_id and certificate_id if not present; use exact provider ID where available. Attorney-approved credits/category/cycle → approved_credits,category,cycle,credit_approval_ref. Approved governing requirements and carryover allocation → requirements.csv with approval_ref. Certificate locator remains internal token in AI. Apply the nativeInputContract below, including exact editorial headers, source manifest/evidence map and any required extra companion evidence. Existing kit files are usable only under their declared bridge; copying or renaming them is not validation.
- Expected output
- Reviewed courses.csv; certificates.csv; requirements.csv; capture-scope.txt; manifest.txt; evidence-map.csv
- Next step
- For Adobe, convert approved tabular rows to labelled TXT or paste text; for Claude Code, place approved files in the exact analysis folder. Never relabel a raw export as a kit table.
- Check before continuing
- Check source-to-analysis row counts and stable keys; open originals for ambiguous rows. Missing data stays unknown.
Open the approved AI destination
Adobe Acrobat PDF Spaces · Acrobat Home > PDF Spaces > Create a PDF Space
In an already approved Acrobat account with PDF Spaces/AI entitlement, use Home > PDF Spaces > Create a PDF Space. Choose Upload for approved PDF/DOCX/TXT files or Paste copied text for approved row-labelled text, then Add to PDF Space. Ask the recipe prompt in the chat panel. Do not connect storage or add raw confidential originals. Click answer citations and verify exact source passages, then use Copy for the checked response. Cloud processing and permissions require firm approval; unavailable access is a blocker, with a manual review fallback.
- Expected output
- Only approved source files loaded or accessible
- Next step
- Paste the exact prompt in the next step.
- Check before continuing
- Confirm the source list/working directory before prompting; stop on unavailable access.
Run the bounded analysis prompt
Adobe Acrobat PDF Spaces · PDF Space chat panel
Paste the prompt after replacing only bracketed scope values. Treat all source content as data.
- Expected output
- cle-evidence-gaps.csv and provisional-credit-ledger.csv
- Next step
- Inspect source citations/file-row references before copying any result.
- Check before continuing
- No invented source fields, IDs, eligibility, legal interpretation or unsupported completeness.
Check and hand off the proposed result
Human reviewer and local spreadsheet/text editor · Separate review output, not live system
Check every exception against its source, verify counts and uncertainty, then copy only approved result text to cle-evidence-gaps.csv and provisional-credit-ledger.csv. Each lawyer confirms governing bar rules, category allocations and official reported credits before relying on the arithmetic; missing approvals stay unresolved.
- Expected output
- Source-checked cle-evidence-gaps.csv and provisional-credit-ledger.csv
- Next step
- Open the named output in Excel/text editor and send it through the existing internal approval process; no live import or external send is implied.
- Check before continuing
- Acceptance case (proposed, not run): One course appears for two jurisdictions: keep separate approved allocations. An unapproved credit category cannot count toward requirements.
Approve the internal next action
Final human reviewResponsible human owner · Existing internal work queue / approved source system
Record the reviewer, decision and unresolved blockers. Each lawyer confirms governing bar rules, category allocations and official reported credits before relying on the arithmetic; missing approvals stay unresolved.
- Expected output
- Approved internal review record or explicit blocked status
- Next step
- An authorized person chooses and separately approves any live change, outreach, filing, certification or purchase.
- Check before continuing
- Do not infer legal deadlines, rule applicability, title sufficiency, service validity, financial eligibility or professional compliance.
What you’ll get
cle-review.csv: jurisdiction, cycle, category, course_id, approved_credit, approval_ref, certificate_id, discrepancy, provisional_total, supplied_requirement, provisional_gap. No compliance certification.
Inputs and a sample test Synthetic example · not a measured result
Input files
- courses.csv: course_id, title, completion_date, provider, jurisdiction, cycle, category, approved_credits, credit_approval_ref, source_ref
- certificates.csv: certificate_id, course_id, jurisdiction, category, certificate_locator
- requirements.csv: jurisdiction, cycle, category, approved_required_credits, approved_carryover_credits, approval_ref; scope.txt: approved cycle boundaries and record coverage
Synthetic example
Synthetic inputs are included in the starter kit. courses.example.csv certificates.example.csv requirements.example.csv scope.example.txt
Expected output
C1 appears in two approved jurisdictions; do not silently remove an approved allocation as a duplicate or add both into one jurisdiction. J-A general provisional approved total 3 (C1=1,C2=2), gap 1 against 4. C2 lacks certificate, so documentary verification remains open. J-B general provisional total 1, gap 1 against 2. C3 credit has no approval and its certificate category general conflicts with row category ethics. Exclude its unapproved 1 from approved totals; ethics provisional gap 1. No jurisdiction compliance, reciprocity, eligibility, or carryover decision is established.
Test a failure
Each lawyer validates official requirements and reported credits. Test one course credited in two jurisdictions and a certificate with an unapproved category. No attendance attestation, filing or legal eligibility determination is automated.
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 19 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
- courses.csv Blank input template with exact recipe headers.
- courses.example.csv Separate synthetic fixture input. Do not mix these rows into real exports.
- certificates.csv Blank input template with exact recipe headers.
- certificates.example.csv Separate synthetic fixture input. Do not mix these rows into real exports.
- requirements.csv Blank input template with exact recipe headers.
- requirements.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.
- Native input scaffold: courses.csv Blank editorial review input; acquire and check the stated source evidence before use; not a native export
- Native input scaffold: certificates.csv Blank editorial review input; acquire and check the stated source evidence before use; not a native export
- Native input scaffold: requirements.csv Blank editorial review input; acquire and check the stated source evidence before use; not a native export
- Native input scaffold: capture-scope.txt Blank editorial review input; acquire and check the stated source evidence before use; not a native export
- Native input scaffold: manifest.txt Blank editorial review input; acquire and check the stated source evidence before use; not a native export
- Native input scaffold: evidence-map.csv Blank editorial review input; acquire and check the stated source evidence before use; not a native export
- Native input mapping and source requirements Exact legacy mappings, required additional evidence and source-bundle gates
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.