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sweep

Runs a grid of cached fits across AR orders, cases, and estimation windows around the current VEC, optionally adding rank tests/bootstrap to compare specifications and fill results as cells finish.

Instructions

C7 — Robustness: a grid of fits over the same files, one CACHED JOB per cell, around the current VEC (its r, restrictions and normalisation). p: AR orders, e.g. "1,2,3"; case: "2, 3, pre, trend" (trend, case 4, for a single fit only); estwin: subsamples, rows 1..E of nabla Y ("60, 70, 80"; the recursive estimate). Empty: the current one. B > 0 adds a rank test per (p, case) cell, with its bootstrap (jobs too). The table — logL, parameters, the stopping criterion, theta and alpha per cell; r-hat for the rank cells — fills as the cells finish: call it again with the same grid (the cells are cached). It claims nothing beyond its cells: what it preserves is the list of what was run, and why, in the guion.

At C1, before any VEC (prepare_vec's specification, B required, no estwin): the RANK over p, each order its own bootstrap — what rank_test offers when n / (M p) is small and the verdict can flip with p.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>"
    },
    "name": "sweep"
  }
}

Input Schema

Name	Required	Description	Default
`B`	No
`p`	No
`case`	No
`name`	Yes
`wait`	No
`estwin`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Oct 30, 2026

TDQS

C2.8/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses caching behavior ('one CACHED JOB per cell', 'the cells are cached'), job spawning for boots, and the partial table that fills as cells finish. It does not state whether it is read-only or destructive, nor what permissions or side effects to expect.

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 purpose is front-loaded, but the text is dense and runs through unexplained abbreviations and domain-specific shorthand. The parameter explanations are packed into long clauses rather than structured in a scannable way.

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 complex tool with six parameters and no annotations, the description leaves too much unexplained: 'C7', 'nabla Y', 'guion', the required 'name', and 'wait'. It tries to cover caching and output behavior but remains insufficient for an unfamiliar agent to call it confidently.

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 description coverage is 0%, so the description must define parameters. It explains p, case, estwin, and B with examples and behavior, but leaves the required 'name' and the 'wait' parameter entirely undocumented.

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 description states a specific action: a grid of fits over the same files with one cached job per cell around the current VEC. However, terms like 'C7', 'nabla Y', and 'guion' are unexplained, and the distinction from siblings such as estimate_vec or rank_test is only partially addressed in a narrow C1 scenario.

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

Usage Guidelines3/5

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

It gives a specific usage case at C1 before any VEC, framing itself as an alternative to rank_test when n/(M p) is small. General guidance on when to use sweep versus estimate or estimate_vec for robustness checks is only implied by the phrase 'Robustness'.

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