Causal Decision Agent

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cr3_jackknife_vcov

Read-only

Compute cluster-jackknife variance for clustered standard errors, delivering validated evidence for causal inference and decision-making.

Instructions

CR3 cluster-jackknife variance (delete-one-cluster). Validation: validated evidence tier (known-truth, reference, external-parity, or Monte Carlo artifact).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`X`	Yes	Feature matrix or covariate DataFrame.
`y`	Yes	Outcome variable column name or outcome array.
`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
`cluster`	Yes	Cluster identifier column for clustered standard errors.
`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`	No	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.
`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

B3.4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, so the description need not repeat safety. It adds the methodological detail of 'delete-one-cluster,' which is useful. It does not describe output format, but an output schema exists. No contradiction with annotations.

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

Conciseness3/5

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

The first sentence is concise and effective. The second sentence about validation evidence tier is tangential and may mislead an agent into thinking the tool is about validation rather than estimation. It adds noise without operational value, so the structure is only partially effective.

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?

Despite the rich schema and output schema, the description fails to explain when CR3 jackknife should be chosen over other cluster-robust or jackknife methods. With over 100 siblings, this omission is significant; an agent lacks decision guidance for tool selection.

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?

Schema coverage is 100% with detailed descriptions for all 9 parameters, including the 'detail' enum and as_handle behavior. The description's reference to 'delete-one-cluster' aligns with the cluster parameter but adds no new information beyond the schema, so the baseline of 3 is appropriate.

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

Purpose5/5

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

The description clearly states the tool computes CR3 cluster-jackknife variance using delete-one-cluster. This is specific enough to distinguish it from siblings like cr2_se, jackknife_se, and cluster_robust_se. The validation sentence is extraneous but does not obscure the core purpose.

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 guidance is provided on when to use this tool versus the many similar alternatives (cr2_se, jackknife_se, cluster_robust_se, multiway_cluster_vcov). An agent would have to infer the appropriate context from the name alone, which is insufficient given the large sibling set.

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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