{"call_id":"call_1bed354b","run_id":"20261015T171122Z-suite-causcibench_real-baseline-4f971b/causcibench_real.q127/e1a1","step":"analysis","kind":"llm","name":"llm.analyst.baseline","version":"","code_version":"2925aeab2262","inputs":{"tools":["calc__annuity","calc__breakeven","calc__combine","calc__discount","calc__fiscal_impact","core__atkinson","core__equivalent_variation","core__fgt","core__gini","core__indirect_incidence","core__kakwani","core__mvpf","core__palma","core__quantile_shares","core__reynolds_smolensky","core__scale_effect","core__theil","core__welfare_change","data__cite","data__describe","data__siconfi","data__sidra","evidence__pool_dl","infer__ate","infer__density_test","infer__did_2x2","infer__did_staggered","infer__event_study","infer__fe","infer__fisher_exact","infer__iv_2sls","infer__linear_hypothesis","infer__mde","infer__neyman","infer__ols","infer__power","infer__randomization_inference","infer__rdd","infer__sample_size","infer__twfe","infer__wald_late","submit_answer"],"exemplars":[]},"input_digest":"","dataset_digests":{},"result":null,"outputs":null,"output_digest":"","params_versions":[],"sources":[],"started_at":"2026-10-15T17:11:24.840495Z","duration_ms":0.0,"error":null,"decided_by":"model","rationale":"","cached":false,"informed_by":[],"model":"rules-1","prompt":"# Role\nYou are MAGI's economist. A municipal analyst in Brazil asks a question; you answer it by choosing registered tools and their arguments. The tools compute every number. Your job is to recognise how the data were generated, pick the tool whose design matches, read what it reports, and say what the result means for the analyst.\n\n# Rules\n1. You never compute a number. Every number in your answer must have been stated by a tool call in this run (a figure, its standard error or interval, a diagnostic, a table cell) or written in the question. No mental arithmetic: for a ratio, difference, sum, product, percent change or share of figures already computed, call calc.combine; to restate a log-point coefficient as a percent or an effect in standard deviations, call core.scale_effect.\n2. Before estimating, work out the design: how units came to be treated (a lottery, an offer with partial take-up, a threshold of a running variable, a policy that started on one date or on different dates, self-selection), what a row is, and which columns hold the outcome, treatment, unit, time, running variable, instrument, cluster and survey weight. Call data.describe when the columns are unclear. Then choose the tool whose \"Use when\" matches and heed its \"Avoid when\".\n3. Read the diagnostics, warnings and \"Check after\" items a result returns before you trust a figure. If a diagnostic says the design fails — a weak instrument, sorting at the cutoff, few clusters, non-parallel pre-trends — say so plainly and do not present the estimate as causal.\n4. If no tool fits the design, or the data cannot identify what is asked, decline and say what is missing. Never invent a design, a column or a number.\n5. A tool that errors or declines returns its reason; fix the arguments and call again, or choose another tool.\n6. Before each tool call, write one sentence on why this tool and these arguments fit the design. It is recorded as your rationale.\n7. Finish with submit_answer. Write the answer in the language of the question (Portuguese: decimal comma), short and direct: the estimate with its uncertainty, the design that identifies it, and what could undermine it. List in figure_refs every figure you quote, as '<call_id>:<key>' (each tool result carries its call_id), and put diagnostics that limit the conclusion in caveats. Write numbers as the tools stated them; do not quote rule-of-thumb thresholds as numbers.\n\n# Datasets\nPass a dataset's id as the `dataset` argument.\n{\n \"id\": \"keele_do_term_limits\",\n \"rows\": 1363,\n \"description\": \"This dataset contains state-level panel data examining fiscal policy outcomes across U.S. states during a period of significant variation in legislative term limits. The data spans multiple decades, capturing the adoption and subsequent repeal of term limits across states. The term limits movement began in 1990 with California, Colorado, and Oklahoma, followed by a major wave in 1992 when eight additional states adopted restrictions. By 2000, twenty-one states had implemented term limits on state legislators. However, several states later repealed these limits through court decisions or legislative action. Currently, fifteen states maintain active term limits while six have repealed previously enacted restrictions.\\n\\nVariable description:\\nexp_real_pc: real per capita expenditure\\ntl_onset: whether a term limit was active in that year\\npopulation: population\\npopgrowth: relative population growth with respect to the previous year\\npopulationdensity: population density\\ngrants_real_pc: federal grants per capita\\ngsp_real_inc: real gross state product per capita\\nfedempciv_pc: federal employment per capita\\nfedempmil_pc: federal military employment per capita\\ngovtempsandl_pc: state and local employment per capita\\nseats_house: number of seats in the house of representatives\\nseats_senate: number of seats in the senate\\nunemployment: unemployment rate\\ngopshare: share of votes for the republican party\\ndemcontrol: whether the state is controlled by the democratic party\\ndividedgov: whether the state has a divided government\\nsquire_score: squire score\\ninitiatives: number of initiatives\\ntel: whether the state has implemented tax and expenditure limitations\\ndebtlimit: whether the state has a debt limit\\nyear: year\\nfips: state code (Federal Information Processing Standards code)\\nstate: state name, may contain spelling errors\",\n \"columns\": {\n  \"year\": \"int64\",\n  \"state\": \"str\",\n  \"yearstate\": \"str\",\n  \"fips\": \"int64\",\n  \"yearx\": \"int64\",\n  \"tl_onset\": \"int64\",\n  \"house_delay\": \"int64\",\n  \"sen_delay\": \"int64\",\n  \"comb_delay\": \"int64\",\n  \"repeal\": \"int64\",\n  \"standardpoors\": \"str\",\n  \"sp25\": \"float64\",\n  \"moodys\": \"str\",\n  \"m25\": \"float64\",\n  \"fitch\": \"str\",\n  \"f19\": \"float64\",\n  \"grants\": \"float64\",\n  \"igr\": \"float64\",\n  \"gopshare\": \"float64\",\n  \"totalrevenue\": \"float64\",\n  \"total_general_revenue\": \"str\",\n  \"totalexp\": \"float64\",\n  \"deficit\": \"float64\",\n  \"general_revenue_from_taxes\": \"str\",\n  \"fullfaithandcredit\": \"float64\",\n  \"nonguaranteeddebt\": \"float64\",\n  \"totallongtermdebt\": \"float64\",\n  \"squire_score\": \"float64\",\n  \"debtlimit\": \"int64\",\n  \"bsf_deposit\": \"int64\",\n  \"bsf_withdrawal\": \"int64\",\n  \"bsf_size\": \"int64\",\n  \"tel\": \"int64\",\n  \"income\": \"int64\",\n  \"unemployment\": \"float64\",\n  \"schoolagepopulation\": \"float64\",\n  \"over65population\": \"float64\",\n  \"gsp\": \"int64\",\n  \"popgrowth\": \"float64\",\n  \"population\": \"int64\",\n  \"populationdensity\": \"float64\",\n  \"exp_highways\": \"float64\",\n  \"exp_welfare\": \"float64\",\n  \"exp_education\": \"float64\",\n  \"handh\": \"float64\",\n  \"govdem\": \"float64\",\n  \"dividedgov\": \"int64\",\n  \"demcontrol\": \"int64\",\n  \"termlimits_governor\": \"int64\",\n  \"termlimits_house\": \"int64\",\n  \"termlimits_senate\": \"int64\",\n  \"termlimits_e\": \"int64\",\n  \"seats_house\": \"int64\",\n  \"seats_senate\": \"int64\",\n  \"initiatives\": \"int64\",\n  \"cpi\": \"float64\",\n  \"v57\": \"float64\",\n  \"grants_total\": \"float64\",\n  \"emptot\": \"int64\",\n  \"empwagesalary\": \"int64\",\n  \"emppriv\": \"int64\",\n  \"totempgovt\": \"int64\",\n  \"fedempciv\": \"int64\",\n  \"fedempmil\": \"int64\",\n  \"govtempsandl\": \"int64\",\n  \"totalexpipolated\": \"float64\",\n  \"highwaysipolated\": \"float64\",\n  \"welfareipolated\": \"float64\",\n  \"educationipolated\": \"float64\",\n  \"handhipolated\": \"float64\",\n  \"exp_real\": \"float64\",\n  \"exp_highways_real\": \"float64\",\n  \"exp_welfare_real\": \"float64\",\n  \"exp_education_real\": \"float64\",\n  \"handh_real\": \"float64\",\n  \"income_real\": \"float64\",\n  \"grants_real\": \"float64\",\n  \"igr_real\": \"float64\",\n  \"gsp_real\": \"float64\",\n  \"totallongtermdebt_i\": \"float64\",\n  \"nonguaranteeddebt_i\": \"float64\",\n  \"total_debt_real\": \"float64\",\n  \"nong_debt_real\": \"float64\",\n  \"exp_real_pc\": \"float64\",\n  \"exp_highways_real_pc\": \"float64\",\n  \"exp_welfare_real_pc\": \"float64\",\n  \"exp_education_real_pc\": \"float64\",\n  \"exp_handh_real_pc\": \"float64\",\n  \"income_real_pc\": \"float64\",\n  \"grants_real_pc\": \"float64\",\n  \"gsp_real_inc\": \"float64\",\n  \"fedempciv_pc\": \"float64\",\n  \"fedempmil_pc\": \"float64\",\n  \"govtempsandl_pc\": \"float64\",\n  \"exp_inc\": \"float64\",\n  \"total_debt_real_pc\": \"float64\",\n  \"nong_debt_real_pc\": \"float64\",\n  \"_Iyear_1980\": \"int64\",\n  \"_Iyear_1981\": \"int64\",\n  \"_Iyear_1982\": \"int64\",\n  \"_Iyear_1983\": \"int64\",\n  \"_Iyear_1984\": \"int64\",\n  \"_Iyear_1985\": \"int64\",\n  \"_Iyear_1986\": \"int64\",\n  \"_Iyear_1987\": \"int64\",\n  \"_Iyear_1988\": \"int64\",\n  \"_Iyear_1989\": \"int64\",\n  \"_Iyear_1990\": \"int64\",\n  \"_Iyear_1991\": \"int64\",\n  \"_Iyear_1992\": \"int64\",\n  \"_Iyear_1993\": \"int64\",\n  \"_Iyear_1994\": \"int64\",\n  \"_Iyear_1995\": \"int64\",\n  \"_Iyear_1996\": \"int64\",\n  \"_Iyear_1997\": \"int64\",\n  \"_Iyear_1998\": \"int64\",\n  \"_Iyear_1999\": \"int64\",\n  \"_Iyear_2000\": \"int64\",\n  \"_Iyear_2001\": \"int64\",\n  \"_Iyear_2002\": \"int64\",\n  \"_Iyear_2003\": \"int64\",\n  \"_Iyear_2004\": \"int64\",\n  \"_Iyear_2005\": \"int64\",\n  \"_Iyear_2006\": \"int64\",\n  \"_Iyear_2007\": \"int64\",\n  \"_Ifips_4\": \"int64\",\n  \"_Ifips_5\": \"int64\",\n  \"_Ifips_6\": \"int64\",\n  \"_Ifips_8\": \"int64\",\n  \"_Ifips_9\": \"int64\",\n  \"_Ifips_10\": \"int64\",\n  \"_Ifips_12\": \"int64\",\n  \"_Ifips_13\": \"int64\",\n  \"_Ifips_16\": \"int64\",\n  \"_Ifips_17\": \"int64\",\n  \"_Ifips_18\": \"int64\",\n  \"_Ifips_19\": \"int64\",\n  \"_Ifips_20\": \"int64\",\n  \"_Ifips_21\": \"int64\",\n  \"_Ifips_22\": \"int64\",\n  \"_Ifips_23\": \"int64\",\n  \"_Ifips_24\": \"int64\",\n  \"_Ifips_25\": \"int64\",\n  \"_Ifips_26\": \"int64\",\n  \"_Ifips_27\": \"int64\",\n  \"_Ifips_28\": \"int64\",\n  \"_Ifips_29\": \"int64\",\n  \"_Ifips_30\": \"int64\",\n  \"_Ifips_32\": \"int64\",\n  \"_Ifips_33\": \"int64\",\n  \"_Ifips_34\": \"int64\",\n  \"_Ifips_35\": \"int64\",\n  \"_Ifips_36\": \"int64\",\n  \"_Ifips_37\": \"int64\",\n  \"_Ifips_38\": \"int64\",\n  \"_Ifips_39\": \"int64\",\n  \"_Ifips_40\": \"int64\",\n  \"_Ifips_41\": \"int64\",\n  \"_Ifips_42\": \"int64\",\n  \"_Ifips_44\": \"int64\",\n  \"_Ifips_45\": \"int64\",\n  \"_Ifips_46\": \"int64\",\n  \"_Ifips_47\": \"int64\",\n  \"_Ifips_48\": \"int64\",\n  \"_Ifips_49\": \"int64\",\n  \"_Ifips_50\": \"int64\",\n  \"_Ifips_51\": \"int64\",\n  \"_Ifips_53\": \"int64\",\n  \"_Ifips_54\": \"int64\",\n  \"_Ifips_55\": \"int64\",\n  \"_Ifips_56\": \"int64\"\n }\n}\n\n# Question\nWhat is the effect of term limits on state expenditure per capita?","response":"submit_answer({\"answer\": \"Pelas regras deste roteador não identifiquei um desenho que responda à pergunta; nenhuma estimativa foi feita.\", \"figure_refs\": [], \"caveats\": 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