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vikranthviki

Causal Decision Agent

by vikranthviki

rdsummary

Read-only

Run regression discontinuity diagnostics: produces bandwidth estimates, covariate balance tests, and plots, highlighting violations and suggesting next steps.

Instructions

One-stop RD diagnostic battery.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cNoCutoff.
pNop parameter (int).
xYesOutcome and running variable.
yYesOutcome and running variable.
covsNoPre-treatment covariates for balance test.
fullNoRun extended diagnostics (honest CI, power, placebos).
plotNoGenerate a multi-panel diagnostic plot.
alphaNoSignificance level for confidence intervals and tests.
fuzzyNoTreatment variable for fuzzy RD.
detailNoPayload depth: 'minimal' (~150 tokens) for sub-step calls where only the point estimate is needed; 'standard' (~1K tokens) for diagnostics + coefficient table; 'agent' (~2K tokens, default) adds violations / next_steps / suggested_functions so the LLM can plan its next call without another round-trip.agent
kernelNoKernel function used for weighting or smoothing.triangular
verboseNoPrint formatted summary to console.
as_handleNoIf true, cache the fitted result on the server and return result_id + result_uri alongside the JSON payload so a subsequent tools/call can chain without re-running.
data_pathYesAbsolute path or URL to a data file. Supported: .csv / .tsv / .txt (delimited), .parquet / .pq, .feather / .arrow, .xlsx / .xls, .dta (Stata), .json / .jsonl. Schemes: file://, s3://, gs://, https://.
result_idNoOptional handle to a previously-fitted result (returned by an earlier call when as_handle=true). Tools that operate on a fitted object accept this in place of re-supplying data_path + columns.
data_columnsNoOptional column projection. Parquet/Feather/Stata loaders honour this for fast partial reads.
data_sample_nNoOptional uniform random subsample size (seed=0, deterministic) — useful on huge panels.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.3/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations already convey read-only safety, but the description adds no concrete behavioral context beyond the vague idea of a battery. It does not say what the battery includes, whether output can be large, or how as_handle caching changes behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The text is short and has no filler, but it is a tagline rather than a structured description. For a 17-parameter tool, this is under-specification rather than economical completeness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The rich parameter schema and output schema carry some burden, but the description omits the central decision of which RD diagnostics are included and when to choose this aggregator over a single-purpose sibling. This is a critical gap in a large specialized sibling set.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is high, giving a baseline, but the required x and y parameters are both documented as 'Outcome and running variable,' leaving an agent unable to tell which is the running variable and which is the outcome. The tool description adds no clarification, and p remains unhelpful as 'p parameter (int).'

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The phrase identifies the domain as RD diagnostics and signals a bundled battery, but it lacks an explicit verb and does not say which diagnostics are included. It also fails to differentiate rdsummary from single-purpose RD siblings such as rdsensitivity or rd_dashboard.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use or when-not-to-use guidance and no named alternative. The word 'one-stop' only weakly implies comprehensive use, which is insufficient among the many RD-specific sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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