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List Study Evaluations

list_study_evaluations

Retrieve summaries of preserved study assessments for a run, including policy details, status, and evidence metadata. Optionally expand for full per-check report and paginate results.

Instructions

List preserved assessments as summaries: id, policy_id, policy_name, status, basis_hash, evidence_hash, created_at and summary (evaluated / total / required_unevaluated / evidence_sources: which values were supplied and which carried). A newer sparse report does not replace an earlier enriched one; decisions bind to a specific report id. Pass expand=["report"] for the full per-check report. Listing never records prediction access, with or without expand (jellyfish #837): a stored report carries window metadata and aggregate errors, not prediction rows. Paging is opt-in: pass limit (1-200) to receive a page and next_cursor; send that cursor back unchanged for the next page; null next_cursor means the end. Without limit every row is returned. Rows you cannot see are simply absent; no totals are promised.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No
`cursor`	No
`expand`	No
`run_id`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv0.6.1Sep 24, 2026

addedInput schema / properties / cursor

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Cursor"
+}

addedInput schema / properties / expand

Added value: +{
+  "anyOf": [
+    {
+      "items": {
+        "const": "report",
+        "type": "string"
+      },
+      "type": "array"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Expand"
+}

addedInput schema / properties / limit

Added value: +{
+  "anyOf": [
+    {
+      "type": "integer"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Limit"
+}

Addedv0.5.0Sep 20, 2026

TDQS

A4.6/5.0

Behavior5/5

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

The description goes well beyond the annotations by disclosing that newer sparse reports do not replace enriched ones, that decisions bind to a specific report id, and that listing never records prediction access. It also clarifies visibility semantics: 'Rows you cannot see are simply absent; no totals are promised.' This is rich, non-obvious behavioral context.

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 dense and somewhat long, but every sentence carries meaningful information about return shape, side effects, paging, or visibility. It is front-loaded with the summary fields and then covers caveats. The internal reference 'jellyfish #837' is slightly noisy but not harmful.

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

Completeness5/5

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

Given the output schema exists and the description already covers return fields, paging, expand behavior, side effects, and visibility semantics, an agent has everything needed to invoke this tool correctly. The only minor gap is run_id semantics, but that is inferable and not a real obstacle.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It explains limit, cursor, and expand in detail, including ranges, defaults, and cursor behavior. The required run_id parameter is not explicitly described, but its meaning is strongly implied by the tool name and context.

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 opens with a specific verb and resource: 'List preserved assessments as summaries' and enumerates the exact fields returned. This clearly distinguishes it from sibling tools like list_study_decisions or get_study_run by focusing on preserved evaluation summaries rather than decisions or full runs.

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

Usage Guidelines4/5

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

The description gives clear operational guidance: when to pass expand, how to page with limit and cursor, and that listing never records prediction access. It does not explicitly name alternatives or state when not to use this tool, but the context is strong enough for an agent to select it appropriately.

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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