Skip to main content
Glama

Clueso

by io.clueso
OverviewDiscussionsAdmin

Get comments

get_comments
Read-only

Read the review comments on a project — the other half of add_comment, which could post but never read.

Comments are how a human reviewer tells you what is wrong with a video: a note pinned to a clip and a moment inside it. Read them before an editing pass so you act on what was actually asked for, and read them again after a build if a reviewer has seen it.

Threads come back nested: each top-level comment carries its replies. Reply into a thread with add_comment(parent_comment_id=...) rather than posting a new top-level note — a reviewer reading their own thread is how they see that their point was handled.

Resolved threads are hidden by default, so a plain read is "what still needs attention".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
clip_idNoOnly comments pinned to this clip. Omit for every comment on the project, project-level ones included.
project_idYesThe project (guide) ID
include_resolvedNoInclude threads already marked resolved (default false). Turn it on to see history; leave it off to see the work outstanding.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • removedInput schema / properties / context
      Removed value: -{
-  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
-  "type": "string"
-}
    • removedInput schema / properties / conversation_id
      Removed value: -{
-  "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
-  "type": "string"
-}
    • removedInput schema / properties / llm_model
      Removed value: -{
-  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
-  "type": "string"
-}
    • changedInput schema / required
      Previous value: -[
-  "project_id",
-  "context",
-  "llm_model"
-]New value: +[
+  "project_id"
+]
  2. Changed4 schema fields changed
    • addedInput schema / properties / context
      Added value: +{
+  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
+  "type": "string"
+}
    • addedInput schema / properties / conversation_id
      Added value: +{
+  "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
+  "type": "string"
+}
    • addedInput schema / properties / llm_model
      Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[
-  "project_id"
-]New value: +[
+  "project_id",
+  "context",
+  "llm_model"
+]
  3. Added

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already mark this as readOnly and non-destructive, and the description adds meaningful behavior beyond that: comments come back nested with replies, resolved threads are hidden by default, and a plain read represents outstanding work. This gives the agent accurate expectations about response shape and filtering behavior with no contradiction.

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?

Every sentence earns its place: the opener defines the tool, the middle sentences give usage context, and the closing sentence clarifies default behavior. It is front-loaded with the core purpose and contains no filler.

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?

There is no output schema, so the description carries the burden of explaining the return shape; it states that threads are nested with replies and that resolved threads are hidden by default. Combined with full parameter documentation and clear annotations, an agent has sufficient context to invoke this tool correctly.

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 coverage is 100%, so the baseline is 3. The description adds value beyond the schema by explaining the practical meaning of include_resolved: history versus outstanding work, and by clarifying that omitted clip_id means project-level comments are included. project_id is not further enriched, but the additional context for the other parameters justifies the higher score.

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: "Read the review comments on a project." It also explicitly distinguishes itself from add_comment, naming it as the sibling that posts but never reads. An agent can immediately determine what this tool does and how it differs from nearby tools.

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?

The description gives explicit when-to-use guidance: read before an editing pass, and again after a build if a reviewer has seen it. It also names the alternative action for replying to a thread, add_comment(parent_comment_id=...), and warns against creating a new top-level note.

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

All Clueso toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources