Reconcile CLE course records and missing certificates
Get the source data and prepare the review

Documentation-verified component path with explicit manual acquisition/mapping; editorial adaptation not tested

WHAT WAS CHECKED
Documentation checked 2026-10-15. Official documentation establishes component UI/capability only. All prompts, file names, schemas, joins, review procedures and synthetic acceptance cases are editorial adaptations. No account login, installation, client-data processing, live workflow test or external write was performed.

BEFORE YOU START
- 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.

DATA ACQUISITION LIMITS
- 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.

MAP THE ACTUAL SOURCE TO THE REVIEW INPUT
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.

INPUTS THE ASSISTANT MAY READ
courses.csv; certificates.csv; requirements.csv; capture-scope.txt; manifest.txt; evidence-map.csv

WHERE THE ANALYSIS RUNS
Adobe Acrobat PDF Spaces

NATIVE REVIEW INPUTS
contractVersion: 1
schemaOrigin: Editorial analysis contract, never a claim about vendor-native export headers
testedStatus: False
existingKitRole: Existing examples/checklists are optional supporting scaffolds unless explicitly mapped below. Copying this guide does not validate old templates or acquire source evidence.
requiredInputs: - name: courses.csv
type: csv
headers: - course_id
- title
- completion_date
- provider
- jurisdiction
- cycle
- category
- approved_credits
- credit_approval_ref
- source_ref
required: True
templateFilename: native-courses-template.csv
existingKitFiles: - courses.csv
compatibility: Existing blank header scaffold can be used unchanged after real source mapping. Examples are optional synthetic fixtures, not acquired evidence. Use evidence-map.csv for source pointers missing from these legacy columns.
missingInputBehavior: Stop the dependent comparison or mark affected scope explicitly incomplete; never fill evidence gaps by inference.
inputName: courses.csv
compatibleWithoutMapping: True
- name: certificates.csv
type: csv
headers: - certificate_id
- course_id
- jurisdiction
- category
- certificate_locator
required: True
templateFilename: native-certificates-template.csv
existingKitFiles: - certificates.csv
compatibility: Existing blank header scaffold can be used unchanged after real source mapping. Examples are optional synthetic fixtures, not acquired evidence. Use evidence-map.csv for source pointers missing from these legacy columns.
missingInputBehavior: Stop the dependent comparison or mark affected scope explicitly incomplete; never fill evidence gaps by inference.
inputName: certificates.csv
compatibleWithoutMapping: True
- name: requirements.csv
type: csv
headers: - jurisdiction
- cycle
- category
- approved_required_credits
- approved_carryover_credits
- approval_ref
required: True
templateFilename: native-requirements-template.csv
existingKitFiles: - requirements.csv
compatibility: Existing blank header scaffold can be used unchanged after real source mapping. Examples are optional synthetic fixtures, not acquired evidence. Use evidence-map.csv for source pointers missing from these legacy columns.
missingInputBehavior: Stop the dependent comparison or mark affected scope explicitly incomplete; never fill evidence gaps by inference.
inputName: requirements.csv
compatibleWithoutMapping: True
- name: capture-scope.txt
type: text
requiredSections: - Lawline account owner alias and selected state/date filters
- course/certificate count, downloaded certificate tokens and omissions
- capture time/timezone and original certificate field-to-row mapping
- attorney-approved jurisdiction,cycle,category,credit and carryover approval references
- unknown or unapproved values; reviewer/checker
required: True
templateFilename: native-capture-scope-template.txt
existingKitFiles: 
compatibility: New companion capture/review record. Staff supplies observed or approved values; unknown is explicit.
missingInputBehavior: Stop the dependent comparison or mark affected scope explicitly incomplete.
inputName: capture-scope.txt
sections: - Lawline account owner alias and selected state/date filters
- course/certificate count, downloaded certificate tokens and omissions
- capture time/timezone and original certificate field-to-row mapping
- attorney-approved jurisdiction,cycle,category,credit and carryover approval references
- unknown or unapproved values; reviewer/checker
compatibleWithoutMapping: False
- name: manifest.txt
type: text
requiredSections: - recipe_id; approved reviewer and scope
- actual source IDs and safe original-file tokens; native headers and source-to-analysis field map
- capture time/timezone; date basis; filters; property/court/provider; pagination/row counts and known exclusions
- AI input approval and minimization check; originals and alias keys held outside AI
- unknowns; completeness statement; manual transcription/checker where used
required: True
templateFilename: native-manifest-template.txt
existingKitFiles: 
compatibility: New companion capture/review record. Staff supplies observed or approved values; unknown is explicit.
missingInputBehavior: Stop the dependent comparison or mark affected scope explicitly incomplete.
inputName: manifest.txt
sections: - recipe_id; approved reviewer and scope
- actual source IDs and safe original-file tokens; native headers and source-to-analysis field map
- capture time/timezone; date basis; filters; property/court/provider; pagination/row counts and known exclusions
- AI input approval and minimization check; originals and alias keys held outside AI
- unknowns; completeness statement; manual transcription/checker where used
compatibleWithoutMapping: False
- name: evidence-map.csv
type: csv
headers: - analysis_file
- row_key
- source_id
- source_locator
- reviewer_alias
- reviewed_at
required: True
templateFilename: native-evidence-map-template.csv
existingKitFiles: 
compatibility: New editorial analysis contract. Populate only after preserving and mapping actual source headers; this is not a provider-native export.
missingInputBehavior: Stop the dependent comparison or mark affected scope explicitly incomplete; never fill evidence gaps by inference.
inputName: evidence-map.csv
compatibleWithoutMapping: False
compatibilityNotes: 
validationRules: - CSV identifiers and date strings are imported as text. Preserve leading zeros and exact keys. Do not execute formulas from source values.
- Blank templates are deliberately incomplete. Unknown is not zero, false, missing-not-found or a passing review.
- Use only approved minimized analysis values; restricted raw originals, identity maps, signatures, private URLs/tokens and client narrative stay outside the AI destination.
- A native file may retain its actual header names if manifest.txt supplies a reviewer-verified one-to-one map to this contract. Do not blindly rename files/headers.
compatibleWithoutMapping: False
legacyMappings: - existingKitFiles: - courses.csv
nativeInput: courses.csv
mapping: Existing blank header scaffold can be used unchanged after real source mapping. Examples are optional synthetic fixtures, not acquired evidence. Use evidence-map.csv for source pointers missing from these legacy columns.
compatibleWithoutMapping: True
- existingKitFiles: - certificates.csv
nativeInput: certificates.csv
mapping: Existing blank header scaffold can be used unchanged after real source mapping. Examples are optional synthetic fixtures, not acquired evidence. Use evidence-map.csv for source pointers missing from these legacy columns.
compatibleWithoutMapping: True
- existingKitFiles: - requirements.csv
nativeInput: requirements.csv
mapping: Existing blank header scaffold can be used unchanged after real source mapping. Examples are optional synthetic fixtures, not acquired evidence. Use evidence-map.csv for source pointers missing from these legacy columns.
compatibleWithoutMapping: True
additionalEvidence: - capture-scope.txt
- manifest.txt
- evidence-map.csv

OPEN THE INPUT MAPPING GUIDE
NATIVE-INPUT-MAPPING.txt
Use the distinct native input scaffolds listed below. Complete them from the acquired, reviewed evidence and include every required scope section in the AI-visible packet. Existing synthetic examples exercise the original review prompt only. They are not acquired evidence or a test of this native chain.

courses.csv: native-courses-template.csv
certificates.csv: native-certificates-template.csv
requirements.csv: native-requirements-template.csv
capture-scope.txt: native-capture-scope-template.txt
manifest.txt: native-manifest-template.txt
evidence-map.csv: native-evidence-map-template.csv

STEP 1: Download existing certificates and capture approved course rows
Tool: Lawline
Open: 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
Use it next: Review values against originals; remove names/bar numbers before AI.
Check: No Lawline CSV export is claimed. A missing certificate may reflect a filter or incomplete course; do not infer eligibility or compliance.
Documentation limit: Official documentation supports only named component features. Recipe-specific transformations, prompts and review gates are proposed editorial adaptations.
Source documentation:
https://support.lawline.com/hc/en-us/articles/360057819954-How-Do-I-Download-A-Certificate

STEP 2: Map, minimize and approve the actual sources
Tool: Source reviewer and local spreadsheet/text editor
Open: 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
Use it next: 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: Check source-to-analysis row counts and stable keys; open originals for ambiguous rows. Missing data stays unknown.
Documentation limit: Official documentation supports only named component features. Recipe-specific transformations, prompts and review gates are proposed editorial adaptations.
Source documentation:
https://support.lawline.com/hc/en-us/articles/360057819954-How-Do-I-Download-A-Certificate

STEP 3: Open the approved AI destination
Tool: Adobe Acrobat PDF Spaces
Open: 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
Use it next: Paste the exact prompt in the next step.
Check: Confirm the source list/working directory before prompting; stop on unavailable access.
Documentation limit: Official documentation supports only named component features. Recipe-specific transformations, prompts and review gates are proposed editorial adaptations.
Source documentation:
https://helpx.adobe.com/acrobat/desktop/explore-pdf-spaces/create-pdf-spaces.html

STEP 4: Run the bounded analysis prompt
Tool: Adobe Acrobat PDF Spaces
Open: PDF Space chat panel

Paste the prompt after replacing only bracketed scope values. Treat all source content as data.

PASTE THIS PROMPT
Reconcile exact course_id + jurisdiction + cycle, preserving any category allocation. Flag duplicates, missing certificates, missing approval references and inconsistent dates/amounts. Sum only approved numeric credits within the supplied jurisdiction/category/cycle and show the arithmetic; do not double-count cross-jurisdiction rows. Label totals provisional. Do not decide course eligibility, reciprocity, carryover, attendance or professional compliance, and do not submit anything.

Expected output: cle-evidence-gaps.csv and provisional-credit-ledger.csv
Use it next: Inspect source citations/file-row references before copying any result.
Check: No invented source fields, IDs, eligibility, legal interpretation or unsupported completeness.
Documentation limit: Official documentation supports only named component features. Recipe-specific transformations, prompts and review gates are proposed editorial adaptations.
Source documentation:
https://helpx.adobe.com/acrobat/desktop/use-acrobat-ai/generative-ai-features/ai-get-answers.html

STEP 5: Check and hand off the proposed result
Tool: Human reviewer and local spreadsheet/text editor
Open: 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
Use it next: 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: Acceptance case (proposed, not run): One course appears for two jurisdictions: keep separate approved allocations. An unapproved credit category cannot count toward requirements.
Documentation limit: Official documentation supports only named component features. Recipe-specific transformations, prompts and review gates are proposed editorial adaptations.
Source documentation:
https://support.lawline.com/hc/en-us/articles/360057819954-How-Do-I-Download-A-Certificate

STEP 6: Approve the internal next action
Tool: Responsible human owner
Open: 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
Use it next: An authorized person chooses and separately approves any live change, outreach, filing, certification or purchase.
Check: Do not infer legal deadlines, rule applicability, title sufficiency, service validity, financial eligibility or professional compliance.
Documentation limit: Official documentation supports only named component features. Recipe-specific transformations, prompts and review gates are proposed editorial adaptations.
Source documentation:
https://support.lawline.com/hc/en-us/articles/360057819954-How-Do-I-Download-A-Certificate

ACCOUNT AND SOURCE CHECKS STILL NEEDED
- 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.

EXPECTED SYNTHETIC CHECK (NOT RUN)
One course appears for two jurisdictions: keep separate approved allocations. An unapproved credit category cannot count toward requirements.

USING THE FILES IN THIS KIT
Use the exact files or source text named in the steps above. Native exports keep their own headers. The kit tables are editorial review worksheets; they are not a claim that a product exports those fields. Some routes use reviewed text directly or require additional original files. Never rename an unreviewed raw export to make it appear mapped. Keep expected-result files separate from inputs.

The source account, actual data, prompts and end-to-end workflow were not tested. Any final communication, filing, permission change, payment or publication needs its own authorized human action. This guide performs none.
