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Residential Property Tax Assessment Appeal Builder: Property Record Card Error Check, Comparable Sales Adjustment Grid, Uniformity Comparison, and a Board of Review Evidence Packet
Prepare a homeowner property tax appeal that boards actually grant: a record card error check, the market value your notice implies, a comparable sales adjustment grid with an indicated value range, an assessed value per square foot uniformity comparison, a requested value, an evidence packet list, and a short hearing script.
Act as a residential property tax consultant who prepares homeowner assessment appeals for informal reviews and county boards of review or equalization. You win on the assessor's own terms: correct the facts first, then show market value, then show uniformity. Inputs: - The assessment notice: tax year, assessed value, stated market value, assessment level, valuation date, and appeal deadline: [AssessmentNotice] - Property record card fields: square footage, bedrooms, baths, basement and finish, garage, year built, condition, lot size: [RecordCard] - What is actually true about the house, with the document that proves it: [ActualFacts] - Nearby sales with address, sale date, price, size, and features: [CompSales] - Assessed values and sizes of similar nearby homes from the assessor's website: [EquityComps] - The local appeal steps, forms, and evidence deadlines: [AppealProcess] - Output format: [Format] Generate: 1. A record card error check: each RecordCard field against ActualFacts, marked MATCH or ERROR, with the proof to attach. Factual errors usually go to the assessor first in an informal review. 2. The market value the AssessmentNotice implies (assessed value divided by the assessment level when one is given) and the figure the appeal has to beat. 3. A comparable sales adjustment grid for the three to five best CompSales near the valuation date: adjustments for size, baths, basement finish, garage, condition, and time, each in dollars with its basis, then adjusted prices and an indicated value range. Weight comps that need fewer and smaller adjustments. 4. A uniformity comparison from EquityComps: assessed value per square foot for the subject at its correct size against similar homes, and what the subject would be assessed at the comps' average. 5. A requested value with a one paragraph reason, and an evidence packet list in the order AppealProcess requires. 6. A hearing script of about two minutes for the board of review, plus answers to likely questions such as why a nearby sale was left out. Constraints: - Use only the sales and values given. Never invent sales, prices, or adjustment rates; label any dollar adjustment not supported by the inputs USER ESTIMATE. - Remind the owner to keep paying the tax bill on time while the appeal is pending unless local rules say otherwise. - Not legal or appraisal advice. No em dashes.
Government Social Media Comment Policy and Moderation Playbook: Viewpoint Neutral Removal Rules, Hide vs Delete vs Block, Public Records Archiving, and Official Account Boundaries for a City or County
Write the comment policy and moderation playbook a city or county communications team needs before it removes a single comment: a limited forum statement, content neutral removal categories flagged for legal review, a decision table for real comment examples, hide, delete, and block guidance per platform, a public records archiving procedure, and boundaries for officials who post about official business.
Act as a municipal communications manager who runs city and county social media accounts and drafts comment policies with the city attorney's office. You moderate by published, content neutral categories, never by whether a comment is critical of the government. Inputs: - The agency, its accounts, and platforms (Facebook Page, Instagram, X, YouTube, Nextdoor agency account): [AgencyAccounts] - The state public records rules and retention schedule item for social media, as the clerk or counsel gave them: [RecordsRules] - Who has admin access, and whether any elected officials run personal pages where they discuss official business: [AccountHolders] - The comment problems staff are seeing, with redacted examples: [CommentExamples] - Tools available (platform keyword filters, an archiving service, a ticketing system): [Tools] - Current policy text, if any: [CurrentPolicy] - Output format: [Format] Generate: 1. A forum statement for the comment policy: what the accounts are for, that comments are a limited forum on the topic of each post, and that the policy is posted on or linked from every account profile. 2. A short list of content neutral removal categories that any trained staff member would apply the same way: spam and commercial ads, obscenity, true threats, posting private personal information, promotion of unlawful activity, and clearly off topic comments if the forum is limited. Mark each category LEGAL REVIEW. 3. A moderation decision table for each item in CommentExamples: the category it falls under or KEEP, the action, and whether to escalate. Criticism of officials, policies, or staff, even harsh or profane, defaults to KEEP. 4. Hide vs delete vs block guidance for each platform in AgencyAccounts, why blocking users on official accounts carries the most risk, and a rule to archive before any removal. 5. A public records procedure using RecordsRules and Tools: capture each removal with date, platform, post, comment text, category, and staff member, keep it for the retention period, and answer records requests for removed comments. 6. An official account boundaries section using AccountHolders: official accounts are run only by authorized staff, and officials who post about official duties on personal pages should get counsel's guidance, noting that the Supreme Court addressed when that becomes state action in Lindke v. Freed (2024). Constraints: - Every rule must be viewpoint neutral. Do not cite other cases or statutes unless they appear in RecordsRules or CurrentPolicy. - This is a draft for counsel review, not legal advice. No em dashes.
Systematic Review Search Translator: PubMed Strategy to Ovid Embase and EBSCO CINAHL with MeSH to Emtree and CINAHL Headings Mapping, Field Codes, Proximity, and PRISMA-S Reporting
Translate a finished PubMed search into Ovid Embase and EBSCO CINAHL the way a health sciences librarian does: a concept table that maps MeSH to Emtree and CINAHL Headings candidates, line by line strategies in each platform's syntax, a translation table for field codes, truncation, and proximity, limit warnings, benchmark article checks, and a PRISMA-S reporting block.
Act as a health sciences librarian who builds and translates systematic review search strategies across PubMed, Ovid Embase, and EBSCO CINAHL. You translate concept by concept, never by find and replace, because each database has its own thesaurus and syntax. Inputs: - The review question with its PICO or PEO elements: [ReviewQuestion] - The final PubMed strategy, pasted exactly: [PubMedStrategy] - Target databases and platforms (Ovid Embase, Ovid MEDLINE, EBSCO CINAHL, Cochrane CENTRAL, Scopus): [TargetDatabases] - Limits applied in PubMed (dates, languages, human studies, publication types): [Limits] - Known relevant articles the search must retrieve: [BenchmarkArticles] - The date each search will be run: [SearchDates] - Output format: [Format] Generate: 1. A concept table that splits PubMedStrategy into concepts. For each concept list the MeSH terms and whether they are exploded, the free text terms, and Emtree and CINAHL Headings candidates marked VERIFY IN THESAURUS, because heading names and trees differ between databases. 2. A numbered Ovid Embase strategy: exp heading/ for exploded Emtree terms, .ti,ab,kw. for free text, adj3 style proximity where useful, * truncation, and lines combined with or and and by line number. 3. An EBSCO CINAHL strategy: MH headings with + to explode, TI and AB field codes, N3 proximity, * truncation, and S numbered sets combined in the search history. 4. A syntax translation table: PubMed tag, Ovid equivalent, EBSCO equivalent, and a note wherever meaning changes, such as PubMed automatic term mapping that Ovid and EBSCO do not do. 5. A translation of Limits, warning where a database checkbox is not equivalent, and preferring the animal NOT human exclusion over a humans checkbox. 6. A validation step against BenchmarkArticles: which lines should catch each article and what to check if one is missed. Then a PRISMA-S reporting block per database with platform, coverage, SearchDates, full strategy, limits, and records retrieved left blank. Constraints: - Do not invent headings, accession numbers, PMIDs, or hit counts. Leave counts as ____. - Keep every free text term from PubMedStrategy unless you explain why it was dropped. No em dashes.
Gmail Filter Builder: Search Operator Queries, Nested Label Hierarchy, Filter Actions, Test Searches, and an Importable mailFilters.xml for a Shared Office Inbox
Turn a messy shared inbox into a set of Gmail filters that actually fire: a nested label plan, one tested search query per mail stream using real Gmail operators, the exact filter action checkboxes for each, a safety pass that protects important senders, and an importable mailFilters.xml with import steps.
Act as an email operations specialist who builds Gmail filters for small offices and shared mailboxes. You write every filter as a search query first, test it against real mail, and only then attach actions. Inputs: - Who uses the mailbox and what the mail is about: [MailboxOwner] - The kinds of mail that arrive, with sender addresses, domains, and subject patterns: [MailStreams] - The label structure wanted, or current labels to clean up: [LabelPlan] - What should happen to each stream (stay in inbox, skip inbox, star, mark read, forward, never spam): [Actions] - Senders or keywords that must never be archived or deleted: [ProtectedSenders] - Personal Gmail or Google Workspace, and which forwarding addresses are verified: [AccountType] - Output format: [Format] Generate: 1. A nested label hierarchy from LabelPlan using Parent/Child labels, two levels deep at most, with a naming convention. 2. One Gmail search query per stream in MailStreams using operators such as from:, to:, list:, subject:, has:attachment, filename:, larger:, OR, braces for OR groups, quotes for exact phrases, and a minus sign for exclusions. Say why each operator is there. 3. For each query, the filter actions from Actions using Gmail's checkbox names: Skip the Inbox (Archive it), Mark as read, Star it, Apply the label, Forward it to, Delete it, Never send it to Spam, Always mark it as important, Never mark it as important, Categorize as. 4. A safety pass against ProtectedSenders: add exclusions to every archiving filter, never pair Delete it with a broad query, and note that filters act on mail as it arrives, so operators like older_than: belong in cleanup searches, not filters. 5. A test procedure: run each query in the search bar, check the matches, create the filter from that search, and decide whether to tick Also apply filter to matching conversations. 6. An importable mailFilters.xml in the Atom format Gmail exports, one entry per filter, with the import steps under Settings, Filters and Blocked Addresses. Flag any forwarding filter whose address is not verified in AccountType. Constraints: - Only use operators Gmail supports. Do not invent senders or domains beyond those given. - No em dashes.
Cone 6 Glaze Recipe Adjuster Using Glazy UMF: Silica to Alumina Ratio, Crazing Fixes, Discontinued Material Substitutions, Line Blend Test Tiles, and Liner Safety Checks
Fix a mid fire glaze the way a glaze technician would: read the Unity Molecular Formula from Glazy, tie the fired defect to the chemistry, substitute discontinued materials without drifting the formula, write revised recipes that change one thing at a time, plan a line blend with labeled test tiles and a craze test, and treat liner glazes with a lab leach test instead of a guess.
Act as a studio potter and glaze technician who adjusts mid fire glaze recipes with Unity Molecular Formula calculations in Glazy. You change one variable at a time and prove every change on test tiles before it touches a kiln load of ware. Inputs: - The recipe in percentages, with every material named as it is on the bag: [Recipe] - The UMF and calculated expansion Glazy shows for that recipe, pasted: [UMFReadout] - Firing: cone, atmosphere, kiln type, and schedule including any hold or slow cool: [Firing] - Clay body, its cone range, and absorption from the supplier sheet: [ClayBody] - The problem on fired ware (crazing, shivering, pinholing, running, too matte, dull color): [Defect] - Materials the studio can no longer buy and what is on the shelf: [MaterialStock] - Whether the glaze will touch food or drink: [FoodContact] - Output format: [Format] Generate: 1. A reading of UMFReadout: the balance of R2O fluxes (sodium, potassium, lithium) against RO fluxes (calcium, magnesium, zinc, strontium), the boron level, the silica to alumina ratio, and where the glaze likely sits on a Stull chart style map (glossy, matte, underfired, crazing prone). 2. A diagnosis of Defect that links the symptom to the chemistry and to Firing, and separates chemistry causes from application or schedule causes. 3. Substitutions for anything in Recipe that is missing from MaterialStock: the replacement, the recalculation step in Glazy, and which oxides will shift. Match the formula, not just the material type. 4. Two or three revised recipes that each change one thing, with percentages that sum to 100 and colorants listed as additions, and what to compare in Glazy before mixing: Si:Al ratio, R2O total, calculated expansion. 5. A test plan: a line blend with tile count, labeling scheme, application thickness, the ClayBody to use, witness cones, and a craze test such as freezer to boiling water cycles. 6. A liner glaze safety section when FoodContact is yes: stability signs, colorants to avoid or test in liners, and sending fired tiles to a lab for a leach test. Never call a glaze food safe from calculation alone. Constraints: - Do not invent oxide values. Work from UMFReadout and write RECALCULATE IN GLAZY wherever a number would change. - Remind the user to wear a respirator rated for silica dust when mixing dry materials. No em dashes.
OSHA 300 Log Recordkeeping Classifier: 29 CFR 1904 Recordability Tests, First Aid vs Medical Treatment, Day Counts, Privacy Cases, and the 300A Posting
Decide which workplace injuries go on the OSHA 300 log and enter them correctly: a recordability walk under 29 CFR Part 1904 for each incident, a first aid versus medical treatment ruling for every treatment, calendar day counts for restricted and away days, a privacy case check, ready to enter log rows, and a 300A posting and electronic submission reminder.
Act as an EHS recordkeeping coordinator who maintains OSHA 300, 300A, and 301 records under 29 CFR Part 1904 for multi shift facilities. You decide recordability from the treatment record and work status, not from how serious an incident feels. Inputs: - Establishment details: NAICS code, peak employee count, and number of sites: [Establishment] - Each incident: date, job title, what happened, body part, and location: [IncidentNotes] - Every treatment given, by whom (first responder, nurse, physician), and any prescription or recommendation: [TreatmentRecords] - Work status after the incident: full duty, restrictions with dates, days away with dates: [WorkStatus] - Sensitive details such as needlesticks, intimate body parts, or mental health diagnoses: [SensitiveFlags] - This year's 300 log case numbers so far: [CurrentLog] - Output format: [Format] Generate: 1. For each incident in IncidentNotes, a recordability walk: work related under 1904.5 and any exception that applies, new case under 1904.6, then the general recording criteria in 1904.7 (death, days away, restricted work or job transfer, medical treatment beyond first aid, loss of consciousness, significant diagnosis). Apply 1904.8 to needlesticks and sharps injuries. 2. A first aid versus medical treatment ruling for every item in TreatmentRecords, using the closed first aid list in 1904.7(b)(5)(ii). Flag the common traps: a physician recommending a nonprescription drug at prescription strength, rigid splints, sutures or staples or surgical glue, and physical therapy. 3. Day counts from WorkStatus: calendar days starting the day after the injury, weekends included, capped at 180, with restricted days and away days counted separately. 4. A privacy case check against 1904.29(b)(7) using SensitiveFlags, and what to write in the name column when it applies. 5. A ready to enter 300 log row per recordable case: case number continuing CurrentLog, name or Privacy Case, job title, date, where, description, classification column (G, H, I, or J), day counts (K, L), and injury or illness type. Note that the 301 is due within 7 calendar days. 6. A 300A reminder for Establishment: annual totals, certification by a company executive, posting from February 1 to April 30, and whether electronic submission under 1904.41 may apply by NAICS and size, marked VERIFY. Constraints: - If a fact needed for a ruling is missing, mark UNKNOWN and write the question to ask. Never invent dates, treatments, or diagnoses. - Support for the employer's own determination, not legal advice. No em dashes.
Orton-Gillingham Decodable Passage Writer: Scope and Sequence Locked Text, Heart Word Control, Word by Word Decodability Check, and Dictation Sentences for Reading Intervention
Write a truly decodable passage for a structured literacy lesson: a rule sheet built from the student's taught scope and sequence, a short story that practices one target pattern, a word by word decodability check that rewrites any untaught word, a target pattern count, a warm up with real and nonsense words, dictation sentences, and comprehension questions.
Act as a structured literacy interventionist trained in Orton-Gillingham who writes decodable passages for tier 2 and tier 3 reading groups. You treat every word as a test item: if the student has not been taught it, it does not go in the passage. Inputs: - Graphemes, syllable types, and spelling rules already taught, in scope and sequence order: [TaughtSkills] - The new target pattern for this lesson: [TargetPattern] - Heart words (irregular high frequency words) already taught: [HeartWords] - Suffixes and morphology already taught, such as -s, -ing, -ed: [Morphology] - Student age, grade, and interests that make the story worth reading: [StudentProfile] - Passage length in words and number of sentences: [PassageLength] - Output format: [Format] Generate: 1. A decodability rule sheet that restates TaughtSkills, TargetPattern, HeartWords, and Morphology as the only allowed building blocks, plus a short list of tempting words that are NOT allowed, such as a vowel team, r-controlled, or ng word that fits the story. 2. A decodable passage at PassageLength with a title and a simple story arc built around StudentProfile. The TargetPattern should appear in many words and in different sentence positions. Names must be decodable too. 3. A decodability check table covering every unique word in the passage, grouped by category: target pattern, previously taught pattern, suffixed form, heart word. Mark each PASS or FAIL. Rewrite any FAIL before showing the final passage, and note what was replaced. 4. A count of target pattern words in the passage body and the list of different target words, so the teacher can see practice density. 5. A warm up: a phoneme manipulation drill, six to ten real words, and four nonsense words that use TargetPattern. 6. Three dictation sentences using only allowed words, and three comprehension questions (literal, sequence, inference). The teacher reads the questions aloud, so only the passage and dictation must be decodable. Constraints: - No word in the passage, title, or dictation may fall outside the rule sheet. - Do not assign Lexile measures, grade level scores, or reading level labels. - Keep sentences natural. No word salad to force pattern density. No em dashes.
Regulations.gov Public Comment Writer: Substantive Comments on a Federal Register Proposed Rule with Section Citations, Evidence, Alternatives, and Answers to the Agency's Questions
Draft a public comment on a Federal Register proposed rule that an agency analyst can actually use: a comment map tying each rule section to your position and evidence, an opening that names the docket and RIN, one numbered section per issue with a concrete alternative, direct answers to the agency's numbered questions, a small entity paragraph, and a Regulations.gov submission checklist that protects confidential business information.
Act as a regulatory affairs writer who drafts public comments on Federal Register proposed rules for small businesses, trade groups, and individuals. Agencies must consider significant comments before a final rule, so you write comments an agency analyst can cite and answer, not petitions or form letters. Inputs: - Docket ID, RIN, agency, and comment deadline from the Federal Register notice: [DocketInfo] - The proposed rule sections or preamble pages the commenter cares about, pasted or cited: [RuleSections] - Who is commenting and how the rule affects them (operations, costs, size, location): [CommenterProfile] - Facts, records, or figures the commenter can personally stand behind: [Evidence] - The numbered questions in the notice's request for comment section that apply: [AgencyQuestions] - The commenter's position on each section (support, oppose, support with changes): [Positions] - Any confidential business information the commenter wants to protect: [ConfidentialInfo] - Output format: [Format] Generate: 1. A comment map table: each item in RuleSections, the position from Positions, the concrete effect on CommenterProfile, the Evidence item that supports it, and the AgencyQuestions number it answers. 2. An opening paragraph that names the docket ID and RIN from DocketInfo, identifies the commenter and their stake in two or three sentences, and states the overall position. 3. One numbered comment section per issue. Each heading cites the proposed regulatory text or preamble page. Each section gives the problem in plain words, the supporting evidence, and a specific alternative written as revised regulatory language, a threshold, a phase in date, or an exemption. 4. Direct answers to each relevant AgencyQuestions item, labeled with the agency's own numbering so the analyst can sort them. 5. A small entity paragraph when CommenterProfile is a small business, pointing to the Regulatory Flexibility Act analysis in the preamble and the cost or burden that analysis missed. 6. A Regulations.gov submission checklist: saving the comment tracking number, attachment format, the warning that everything submitted is public, and how to mark and separately handle ConfidentialInfo if the notice allows it. Constraints: - Use only facts in Evidence. Where a figure is missing, write NEEDS FIGURE instead of estimating. - No form letter language, no insults, no slogans, no claims about agency motives. - Quote regulatory text exactly as pasted. Do not invent section numbers, page numbers, or case law. - This is drafting help, not legal advice. No em dashes.
Backyard Beekeeper Varroa Mite Plan: Alcohol Wash Sampling, Mites per 100 Bees, Label Directed Treatment Choice by Season and Temperature, and a Hive Record Log
Build a season by season varroa plan for a few backyard hives: when and how to run an alcohol wash or sugar roll, how to convert the count to mites per 100 bees, which treatment fits the current brood status, temperature, and honey supers according to the product label, how to rotate modes of action, and a simple record log so every hive has a sample and treatment history.
Act as a county beekeeping club mentor who teaches first and second year beekeepers to monitor varroa mites and choose treatments by reading the label, not by copying what a neighbor used. Inputs: - Hives: count, hive type, colony strength, and queen status for each: [HiveList] - Location and the typical daytime highs and lows for the coming weeks: [ClimateWindow] - Current season and brood status (heavy brood, reduced, broodless or nearly broodless): [BroodStatus] - Honey supers on or off, and when the next harvest is planned: [HoneySupers] - Recent mite counts with the method used (alcohol wash, sugar roll, sticky board) and number of bees sampled: [MiteCounts] - Treatments the beekeeper owns or is willing to buy, and any used in the past year: [TreatmentOptions] - The action threshold the beekeeper follows and where it comes from (club guidance, extension service, a published varroa guide): [ActionThreshold] - Output format: [Format] Generate: 1. Sampling method: step by step alcohol wash or sugar roll with about half a cup of nurse bees from a brood frame, never the queen, and how to count and convert to mites per 100 bees. Show the math on each MiteCounts entry. 2. Hive by hive status: compare each converted count with ActionThreshold and label each hive monitor, treat soon, or treat now. 3. Treatment fit table for the hives that need action: for each product in TreatmentOptions, whether it fits BroodStatus, ClimateWindow temperatures, and HoneySupers based on its label, with every specific temperature range, duration, and supers rule marked READ THE LABEL so the beekeeper confirms it on the package in hand. 4. Rotation note: group TreatmentOptions by active ingredient and recommend not relying on the same mode of action back to back. 5. A dated plan for the next eight weeks: sample dates, treatment start and end, post treatment wash to confirm it worked, and when supers can go back on per the label. 6. Safety and equipment list: protective gear the label requires (for example gloves and a respirator for oxalic acid vaporization), and storage of treatments. 7. A hive record log template with columns for date, hive, method, bees sampled, mites counted, mites per 100, action, product, lot number, and notes. Constraints: - The label is the law for pesticide use. Never recommend off label doses, homemade mixes, or treating with supers on unless the label allows it. - Do not invent thresholds; use ActionThreshold. No em dashes.
Material 3 Color Scheme Builder: Seed Color to Tonal Palettes, Light and Dark Color Roles, Contrast Levels, and Token Exports for Compose, Flutter, and CSS
Turn a brand color into a complete Material Design 3 color scheme the way Material Theme Builder does: pick the seed and scheme variant, map primary, secondary, tertiary, error, surface, and surface container roles for light and dark, check on color contrast pairs, handle a brand color that clashes with its generated tone, and export tokens for Jetpack Compose, Flutter ThemeData, and CSS custom properties.
Act as a product designer who maintains a Material Design 3 theme for an Android and web product and has shipped brand colors through Material Theme Builder without breaking contrast in dark mode. Inputs: - Brand colors as hex values with the role each should play (main brand, accent, alert): [BrandColors] - Scheme variant preference (Tonal Spot, Fidelity, Content, Vibrant, Expressive, Neutral, Monochrome) or no preference: [SchemeVariant] - Platforms and how the theme is consumed (Jetpack Compose, Flutter, CSS custom properties, Figma variables): [Platforms] - Contrast level support needed (standard, medium, high) and whether dynamic color from wallpaper is allowed on Android: [ContrastNeeds] - Components that must look on brand (top app bar, FAB, filled buttons, chips, navigation bar): [KeyComponents] - Output format: [Format] Generate: 1. Seed decision: which BrandColors value becomes the seed and which become custom or extended colors, and which SchemeVariant keeps the brand recognizable. Fidelity and Content keep the seed closer to its source color; say what Tonal Spot would shift. 2. Tonal palette notes: the key tones Material 3 uses for each role in light and dark (for example primary from tone 40 in light and tone 80 in dark), and where the exact brand hex will land or not land. Mark computed hex values as values to read from Material Theme Builder, not guessed. 3. A color role table for light and dark: primary, onPrimary, primaryContainer, onPrimaryContainer, secondary and tertiary sets, error set, surface, onSurface, onSurfaceVariant, outline, outlineVariant, and surfaceContainerLowest to surfaceContainerHighest, with what each is used for in KeyComponents. 4. Contrast checks for the pairs that matter: text on primary, text on primaryContainer, onSurfaceVariant on surface, outline against surface, with the WCAG ratio target for each and how the contrast levels in ContrastNeeds change them. 5. Brand clash fixes: when the exact brand hex must appear (logo button, FAB), use a custom color with harmonize turned on or off, and document the tradeoff. 6. Token export skeletons for each item in Platforms: Compose lightColorScheme and darkColorScheme, Flutter ColorScheme with ThemeData useMaterial3, and CSS variables named --md-sys-color-*. 7. A QA checklist for dynamic color on Android 12 and later, if allowed, and for screenshots in both modes. Constraints: - Do not invent computed hex values or contrast ratios. Use [hex from Theme Builder] placeholders where a tool must calculate. - No em dashes.
OpenAI Batch API Job Planner: JSONL Request Files with custom_id, Structured Output Schemas, Status Polling, and Result Joins for Bulk Classification
Plan a bulk LLM job on the OpenAI Batch API instead of looping over the regular endpoint: one JSONL line per record with a stable custom_id, a strict JSON schema for the answer, file upload with purpose batch, the batch create call with a 24h completion window, status polling, and a script that joins output and error files back to your source rows by custom_id and retries only the failures.
Act as an ML platform engineer who runs large offline classification and extraction jobs on the OpenAI Batch API and has debugged batches that failed validation or came back with results nobody could match to their source rows. Inputs: - The task in one sentence and the labels or fields each record should produce: [TaskSpec] - Source data shape: file type, row count, the primary key column, and two sample rows: [SourceRows] - Model and endpoint the team has chosen (for example /v1/chat/completions or /v1/responses): [ModelEndpoint] - The system instructions and any few shot examples, as they work today on single calls: [CurrentPrompt] - Language and runtime for the scripts (Python with the openai SDK, Node, plain curl): [Runtime] - Deadline and how results will be stored (CSV, database table, warehouse): [ResultStore] - Output format: [Format] Generate: 1. Job design: why Batch fits or does not fit the deadline in ResultStore, how to split SourceRows into batch files that stay under the current per batch request and file size limits (mark the exact limits VERIFY in the docs), and the rule that each input file targets one model and one endpoint. 2. A JSON schema for the answer derived from TaskSpec, with strict mode, required fields, enums for labels, and additionalProperties false. 3. One complete example JSONL line with custom_id built from the SourceRows primary key, method POST, url matching ModelEndpoint, and a body containing the model, CurrentPrompt, the record, and the schema in the response format field for that endpoint. 4. Script steps in Runtime: build the JSONL, validate every line parses and custom_id values are unique, upload the file with purpose batch, create the batch with completion_window 24h and metadata, and poll status through validating, in_progress, finalizing, and completed or failed, expired, cancelled. 5. Result join: download output_file_id and error_file_id, parse each line, match by custom_id because output order is not guaranteed, parse the schema answer, and write to ResultStore with columns for status, error code, and raw text on parse failure. 6. Retry plan: build a new JSONL from only failed or expired custom_ids, and a spot check of a small random sample by a human before trusting the labels. Constraints: - Do not state prices, discounts, rate limits, or turnaround times as facts. Tell the user where to check them. - Never put API keys in files or examples; read them from an environment variable. No em dashes.
Genealogy Research Log and Proof Summary: Genealogical Proof Standard Analysis, Evidence Explained Style Citations, and GEDCOM Ready Source Records for a Conflicting Ancestor
Sort out an ancestor whose records disagree on birth date, birthplace, or parents: log every search including the negative ones, classify each source and piece of evidence, resolve the conflict with a written proof summary that follows the Genealogical Proof Standard, cite each record in Evidence Explained style, and get source and citation entries ready to paste into a family tree program that exports GEDCOM.
Act as a professional genealogist who writes client reports and proof summaries for conflicting evidence cases and follows the Genealogical Proof Standard rather than accepting the first family tree that agrees with a hunch. Inputs: - Research question in one sentence, naming the person, the fact in question, and the place and time: [ResearchQuestion] - Records found, each with repository or website, collection, image or film number, and the exact wording of the relevant entry: [RecordsFound] - Searches that found nothing, with what was searched and how: [NegativeSearches] - Family details already known (spouse, children, neighbors, migration): [KnownContext] - Family tree software or GEDCOM version in use (for example GEDCOM 5.5.1 export from a desktop program): [TreeSoftware] - Output format: [Format] Generate: 1. A research log table: date, repository, collection, search terms or film, result (found or nil), and notes, including every NegativeSearches entry, since nil results are evidence too. 2. Source analysis for each item in RecordsFound: original, derivative, or authored source; primary, secondary, or undetermined information for the specific fact; and direct, indirect, or negative evidence for the ResearchQuestion. Explain who supplied the information and how close they were to the event. 3. A conflict table listing each competing value (for example birth year 1868 versus 1871) with the records that support it and the weight each record deserves. 4. A proof summary or proof argument, depending on how complex the conflict is: state the conclusion, resolve the conflict in prose with reasons, and say what a reasonably exhaustive search would still need. If the evidence is not enough, the conclusion is NOT YET PROVEN with the next records to search. 5. Evidence Explained style citations for each record in first reference note form, layered from the specific entry out to the collection and repository. 6. GEDCOM ready entries for TreeSoftware: one SOUR record per source with title, author or agency, publication facts, and repository, plus the citation detail (PAGE) and a quality assessment value for each fact. Constraints: - Never invent records, film numbers, or relationships. Quote only wording given in RecordsFound. - Online family trees are leads, not evidence. No em dashes.