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DreamAgent

by io.github.nivethaug

dreamagent_get_edit_progress

Read-only

Check the latest AI edit progress for a project using its project identifier — no session key needed: the project id retrieves the session holding the latest edit. Use when the user asks whether their edit is finished, when the session key isn't available (e.g. a new conversation), and BEFORE starting any new edit.

Returns (actual fields): 'session_key=' (the identifier of the session this progress comes from), 'edit_active=', 'run_status=', 'chunks=' (output size so far), optional 'recent_output (tail):', and a terminal 'result:' line: finished (with the final output tail), 'the edit was NOT started: ' (rejected early, e.g. HTTP 402 insufficient credits), 'stream error', or 'no run is currently active'. run_status values: queued | running | cancel_requested | completed | failed | cancelled | interrupted | unknown.

Distinct from dreamagent_get_project_status: project status = creation/deployment state (creating/ready/failed); edit progress = current AI modification state; chat status (dreamagent_get_chat_status) monitors one specific session by its session key. If edit_active is true, do NOT launch another edit for the same project.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesthe project being edited.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observed

TDQS

A5/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description explains that no session key is needed, how the project id maps to the latest session, details the return fields (session_key, edit_active, run_status, chunks, result), and enumerates run_status values and possible result outcomes. This is rich 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.

Conciseness5/5

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

The description is well-structured: purpose first, then usage, return fields, status enum, sibling differentiation, and a caution. Every sentence contributes valuable information without redundancy, making it dense but not verbose.

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?

With one parameter and an output schema, the description covers purpose, usage context, full return format, run_status values, and an operational constraint. This provides enough information for an agent to select and invoke the tool correctly without confusion.

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

Parameters5/5

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

The schema only describes project_id as 'the project being edited.' The description adds crucial meaning: 'the project id retrieves the session holding the latest edit' and explicitly notes 'no session key needed,' which substantially clarifies how the parameter is used.

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 'Check the latest AI edit progress for a project using its project identifier' — a specific verb and resource. It also distinguishes itself from dreamagent_get_project_status and dreamagent_get_chat_status, making the tool's unique scope unambiguous.

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?

Explicitly provides when to use: 'Use when the user asks whether their edit is finished, when the session key isn't available... and BEFORE starting any new edit.' It also contrasts sibling tools and warns against launching another edit when edit_active is true, giving clear guidance on alternative selection.

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

A4.6/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: project creation, listing, status checks, edit progress, session management, and integration queries. The status tools (get_chat_status, get_edit_progress, get_project_status) are carefully differentiated by their input and purpose, so there is no real ambiguity.

Naming Consistency5/5

All tool names follow a consistent pattern of 'dreamagent_' plus a verb_noun structure (e.g., create_project, list_sessions, get_edit_progress). This makes the entire set predictable and easy to navigate.

Tool Count5/5

With 12 tools, the set is well-scoped for managing DreamAgent projects and edits. Each tool covers a necessary operation without redundancy or bloat, staying comfortably within the ideal range.

Completeness4/5

The tool set comprehensively covers project creation, listing, status monitoring, AI editing, session management, and integration inspection. The notable gap is the lack of an update or delete project operation, but the core lifecycle and editing workflows are well covered.

Resources