Skip to main content
Glama
vikranthviki

Causal Decision Agent

by vikranthviki

postestimation_report

Read-only

Get post-estimation diagnostics and recommended next steps for a fitted result, enabling informed causal decisions.

Instructions

Return the post-estimation actions supported by result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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
resultYesFitted StatsPAI result, estimator, or compatible object.
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_pathNoAbsolute 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.
include_diagnosticsNoInclude scalar diagnostics from ``model_info`` / ``diagnostics``.

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?

The annotations already declare readOnlyHint=true and openWorldHint=false, so the no-side-effects aspect is covered. The description adds no further behavioral detail beyond the purpose, such as whether the tool actually executes the actions or only lists them, which would be marginally useful. Since annotations cover the main safety profile, a 3 is appropriate.

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, well-formed sentence with no filler. It front-loads the verb and resource, and every word contributes to the core purpose. Perfectly concise and structured for quick comprehension.

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?

While the tool is relatively simple and the output schema exists, the description lacks any elaboration on what 'post-estimation actions' entails or how the result parameter should be supplied. The rich parameter schema and annotations compensate, but the description alone would leave an agent without context on when or how to apply this tool effectively.

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 provides 100% coverage for all 8 parameters, each with descriptive text, so the schema already explains parameter meaning and usage. The description adds nothing about parameters beyond the schema, so the baseline 3 is appropriate.

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 ('Return') and resource ('post-estimation actions supported by *result*'), making the primary purpose clear. It does not explicitly distinguish from siblings like postestimation_contract, but the resource is sufficiently specific to convey intent.

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 guidance on when to use this tool versus alternatives, nor any mention of prerequisites or contexts. The description only states what it returns, not under what circumstances an agent should invoke it, leaving the agent to infer usage from the name and schema.

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

Deploy Server

Other Tools