Causal Decision Agent

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rdsensitivity

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Check how regression discontinuity estimates vary across window widths to assess robustness and choose a stable bandwidth.

Instructions

Sensitivity of RD estimates across different window widths.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`c`	No	RD cutoff value.
`p`	No	Polynomial order for adjustment.
`x`	Yes	Running variable name.
`y`	Yes	Outcome variable name.
`plot`	No	plot parameter (bool).
`seed`	No	Random seed.
`alpha`	No	Significance level.
`wlist`	No	Symmetric half-window widths to evaluate. If None, an evenly-spaced grid is generated automatically.
`detail`	No	Payload 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
`n_perms`	No	Number of permutations per window.
`nwindows`	No	Number of windows when ``wlist`` is None.
`as_handle`	No	If 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_path`	Yes	Absolute 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_id`	No	Optional 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.
`statistic`	No	Test statistic for inference.	diffmeans
`data_columns`	No	Optional column projection. Parquet/Feather/Stata loaders honour this for fast partial reads.
`data_sample_n`	No	Optional uniform random subsample size (seed=0, deterministic) — useful on huge panels.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 15, 2026

TDQS

C2.9/5.0

Behavior2/5

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

The description restates the tool's focus but adds no behavioral details beyond the annotated readOnlyHint and openWorldHint. It does not mention output structure, side effects, or required inputs—though the output schema covers returns. It does not contradict annotations.

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

Conciseness4/5

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

The description is a single concise phrase with no redundancy. It is front-loaded with the key concept, though it is a fragment rather than a full sentence, which slightly reduces its structural 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?

For a tool with 17 parameters and many RD siblings, the description is too short to orient an agent. It does not explain when to use this tool, how it differs from rdbwsensitivity or rd_robustness_table, or what workflow it fits into. The output schema covers returns, but the usage context is missing.

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

Parameters3/5

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

The schema description coverage is 100%, so the parameters are well-documented. The description adds no additional meaning to any parameter and does not compensate for any missing schema detail.

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

Purpose4/5

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

The description names the resource (RD estimates) and the variation (window widths), which conveys the core function. However, it is a noun phrase without a verb and does not explicitly distinguish it from closely related tools like rdbwsensitivity or rd_robustness_table.

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?

No mention of when to use this tool or when to prefer an alternative. The description is purely a statement of function and gives no criteria to select it over the many RD sensitivity siblings in the toolset.

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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