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vikranthviki

Causal Decision Agent

by vikranthviki

rdplotdensity

Read-only

Plot density discontinuity at the RD cutoff to detect manipulation or sorting in the running variable.

Instructions

Boundary-adaptive density discontinuity plot at the RD cutoff.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cNoCutoff.
hNoBandwidth. If None, side-specific Silverman pilot.
pNoPolynomial order for the CDF regression (p=2 recommended; p=1 is faster but with worse boundary behavior).
xYesRunning variable.
axNoax parameter (Optional[Any]).
histNoOverlay histogram.
nbinsNoNumber of histogram bins per side.
titleNotitle parameter (Optional[str]).
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
n_gridNoGrid points per side for the density curve.
figsizeNofigsize parameter (Tuple[float, float]).
ci_levelNoConfidence level for CI bands.
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

B3.3/5.0
Behavior3/5

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

Annotations declare readOnlyHint=true and openWorldHint=false, indicating a safe read-only operation. The description adds the behavioral detail that this is a 'plot' tool, implying it generates a visual output. It does not describe side effects (e.g., file saving) or further behavioral specifics, but given the annotations already carry the safety profile, this is adequate. No contradiction with annotations is present.

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

Conciseness5/5

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

The description is a single, dense sentence: 'Boundary-adaptive density discontinuity plot at the RD cutoff.' Every word carries necessary meaning; there is no filler or repetition. It is appropriately sized and front-loaded, placing the key action ('plot') and object ('density discontinuity') first. This is a model of conciseness.

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

Completeness3/5

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

The tool has a rich schema (17 parameters, 2 required) and an output schema, so the description need not explain return values or parameter formats. However, it does not provide broader context about how this tool fits an RD analysis workflow (e.g., ordering with rddensity, interpretation of boundary-adaptive methods). The phrase 'Boundary-adaptive' is jargon and unexplained Lloyd. Given the complexity and the huge sibling set, the description is minimally complete but leaves contextual gaps.

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 input schema provides 100% parameter description coverage, so the baseline is 3. The tool description itself adds no parameter-level meaning beyond the schema. Every parameter (e.g., c, h, p, data_path) already has a dedicated description in the schema, and the one-sentence description does not enrich or clarify them. Thus the description does not compensate or add extra context.

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 states a specific verb-resource pair: 'density discontinuity plot at the RD cutoff'. It clearly indicates the tool produces a plot related to density at a regression discontinuity cutoff. However, it does not explicitly distinguish itself from sibling tools like rdplot or rddensity, which also deal with RD plots/density. The meaning is clear enough, but differentiation is left to the tool name and schema.

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?

The description gives no guidance on when to use this tool versus alternatives. It does not mention alternatives, conditions, or exclusions. For example, it does not say 'use this instead of rdplot when examining density at the cutoff' or contrast with rddensity. An agent is left to infer context from the tool name and schema, which is insufficient for decision-making among many RD-related siblings.

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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