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Glama

Elicitly Pro

by ai.elicitly

Fetch a decided elicitation's outcome

elicit_result
Idempotent

Fetch the outcome of a decided request (poll elicit_status or block on elicit_await first — this errors while the request is still pending, after it expires undecided, or if it was canceled via elicit_cancel; repeatable reads are fine afterward). Returns { status: 'consumed', decision, context, formSubmission } plus per-tool overlays: elicit_selection adds selectedIds (the chosen option ids); elicit_proposal adds, on submit, values (only the fields the reviewer included).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
elicitationIdYesThe `elicitationId` returned by the creating tool (elicit_approval, elicit_selection, or elicit_proposal).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYesThe outcome has been read at least once.
valuesNoelicit_proposal only, on submit: the proposed values for just the fields the reviewer included.
contextYesThe caller's original `context`, echoed verbatim (null if none was supplied).
decisionYesThe reviewer's choice: submitted = approved/filled in, declined = explicit no.
selectedIdsNoelicit_selection only, on submit: the chosen option ids.
formSubmissionYesThe reviewer-filled field values keyed by requestedSchema property name; null in json mode or on decline.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • addedInput schema / properties / elicitationId / description
      Added value: +"The `elicitationId` returned by the creating tool (elicit_approval, elicit_selection, or elicit_proposal)."
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "context": {
+      "description": "The caller's original `context`, echoed verbatim (null if none was supplied)."
+    },
+    "decision": {
+      "description": "The reviewer's choice: submitted = approved/filled in, declined = explicit no.",
+      "enum": [
+        "submitted",
+        "declined"
+      ],
+      "type": "string"
+    },
+    "formSubmission": {
+      "description": "The reviewer-filled field values keyed by requestedSchema property name; null in json mode or on decline."
+    },
+    "selectedIds": {
+      "description": "elicit_selection only, on submit: the chosen option ids.",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "status": {
+      "const": "consumed",
+      "description": "The outcome has been read at least once.",
+      "type": "string"
+    },
+    "values": {
+      "additionalProperties": {},
+      "description": "elicit_proposal only, on submit: the proposed values for just the fields the reviewer included.",
+      "propertyNames": {
+        "type": "string"
+      },
+      "type": "object"
+    }
+  },
+  "required": [
+    "status",
+    "decision",
+    "context",
+    "formSubmission"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already mark the tool as idempotent and non-destructive, but the description adds valuable behavioral context: error conditions, repeatable-read reassurance, and the exact return shape including per-tool overlays. 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.

Conciseness5/5

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

A single dense sentence front-loads the core purpose, then efficiently packs lifecycle conditions, error semantics, and return format without filler. Every clause earns its place.

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?

For a single-parameter tool with an output schema, the description fully covers preconditions, error states, idempotency, and the return shape with per-tool overlays. An agent has everything needed to call it correctly.

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% and the schema already clearly describes elicitationId as returned by the creating tool. The description adds no additional parameter meaning beyond the schema, so the baseline of 3 applies.

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 states a specific verb and resource: 'Fetch the outcome of a decided request'. It also distinguishes itself from siblings by explicitly referencing elicit_status, elicit_await, and elicit_cancel, making its role in the elicitation lifecycle clear.

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

Usage Guidelines5/5

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

It explicitly instructs the agent to poll elicit_status or block on elicit_await first, and explains when this tool errors: while pending, after expiring undecided, or after cancellation. This gives clear when-to-use and when-not-to-use guidance relative to sibling tools.

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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TDQS

A4.1/5.0
Disambiguation3/5

Most tools have distinct roles in the elicitation lifecycle, but elicit_approval's form mode heavily overlaps with elicit_form, and elicit_confirm is explicitly a wrapper over elicit_form, creating real selection ambiguity. Status, await, result, cancel, and history are clearly separated, so the confusion is limited to a couple of closely related tools.

Naming Consistency4/5

All tools share the elicit_ prefix and use snake_case, which makes the namespace predictable and easy to scan. However, the second token mixes nouns (approval, form, proposal, status) with verbs (await, cancel, confirm, ping), and elicit_doctor is a non-obvious metaphor, so the pattern is not perfectly uniform.

Tool Count5/5

Twelve tools is within the ideal scope for a specialized elicitation server: creation variants, status polling, blocking wait, result retrieval, cancellation, history, and diagnostic helpers all have a place. The count feels purposeful rather than padded, and it fits the domain without becoming unwieldy.

Completeness4/5

The lifecycle is well covered: agents can create varied elicitations, check status, block on decisions, fetch results, cancel pending requests, and review history, plus diagnostic and connectivity tools. The main gap is the inability to update or extend a pending elicitation after creation, but agents can work around this by canceling and recreating.

Resources