calculate_plan_payload
ChatGPTCalculate an inline plan deterministically. Start with a compact summary; request a named view and bounded years or ages only for focused annual detail. Screen candidates cheaply before Monte Carlo.
Overview
Create, inspect, compare, and stress-test Canadian retirement plans with MayRetire. Supply a saved plan or build a draft through conversation. The remote service processes plan data without saving it to a MayRetire account. Projections are estimates, not financial advice.
Tools
cancel_plan_job
ChatGPTRequest cancellation of a running planning job.
compare_plan_payloads
ChatGPTCompare an inline baseline plan with up to eight independent merge-patch variations using deterministic calculations. No plan files are written.
create_plan_payload
ChatGPTCreate a neutral MayRetire plan in memory, applying an optional guided request and portfolio presets. Ask for household facts first; never invent balances or benefits. Returns the complete plan and validation issues.
describe
ChatGPTDescribe MayRetire fields or collections before editing unfamiliar plan settings.
edit_plan_payload
ChatGPTApply a patch and/or item operations to an inline MayRetire plan. Returns the complete modified plan, changes, and validation warnings without writing a file.
explain_plan_payload
ChatGPTExplain why withdrawals occurred in one plan year or at one age, with decision-trace evidence. Deterministic by default; set trialSeed for one simulated return sequence.
get_candidate_plan
ChatGPTReturn the complete modified plan for one completed exploration or optimization candidate, after reviewing the compact job result.
inspect_plan_payload
ChatGPTInspect active goals, accounts, spending, withdrawal strategies, housing, and assumptions in an inline saved plan without calculating it.
plan_handoff_url
ChatGPTOptional UI handoff only: encode an already available inline plan as a MayRetire /view URL fragment when the user asks to open it. Editing tools return plan JSON directly; this tool does not save a plan or launch a browser.
result_plan_job
ChatGPTGet compact completed planning results, or current status while queued or running. Search candidate plans are retrieved separately.
start_backtest_job
ChatGPTTest a supplied retirement plan over historical starting-year return sequences. Returns a job ID; poll status_plan_job and then result_plan_job. Historical rotations are not independent Monte Carlo trials.
start_exploration_job
ChatGPTEvaluate a bounded set of supplied retirement-plan variations and return compact candidate results. Provide exactly one of request.variables or request.scenarios. Returns a job ID; poll status_plan_job, then result_plan_job, and retrieve selected plans with get_candidate_plan. Screen deterministically before enabling per-candidate simulation or stress.
start_monte_carlo_job
ChatGPTEstimate a supplied retirement plan's success rate across bounded simulated return sequences. Returns a job ID; poll status_plan_job and then result_plan_job. Use the same seed and trial count when comparing plans. A queued job is not a failed calculation.
start_optimization_job
ChatGPTRank a bounded set of supplied retirement-plan variations by a stated objective and constraints. Provide exactly one of request.variables or request.scenarios. Returns a job ID; poll status_plan_job, then result_plan_job, and retrieve selected plans with get_candidate_plan. Results are best only within the evaluated candidate set.
start_stress_test_job
ChatGPTTest a supplied retirement plan against MayRetire's six built-in adverse return sequences. Returns a job ID; poll status_plan_job and then result_plan_job. The scenario pass count is not a probability of future success.
status_plan_job
ChatGPTGet a planning job state, queue position if waiting, and progress if running.
validate_plan_payload
ChatGPTValidate a complete inline MayRetire plan and report errors and warnings before calculating or searching.
Capabilities
Writes
Example Prompts
Click any prompt to copy it.
