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Get feedback

feedback_get
Read-onlyIdempotent

Get a single feedback item with its full reply thread. element_id is the item's id, as feedback_list, recent_activity, search or wait_for_feedback return it. Use it when an item has replies (feedback_list gives reply_count, not the replies) or to read one item again; to list an asset's feedback use feedback_list. Returns the item's text body (for recordings: the AI-organized feedback), tags (by name), author, posted_by_agent, video timestamp, the recording (recording_type voice, camera or screen; its full verbatim transcript; pipeline_status - the transcript is final once it is complete), visual_references (the pointing phrases - "this", "over here" - with the recording time each was spoken), visuals (the drawings and images), and all replies (each with reply_to = this item's id). content is Markdown: 0:26 links a moment of the video (S in #t=S is video seconds, a range is #t=S,E), and this marks a phrase spoken at recording time 15.7s (the same values as recording.visual_references). An item with something to see carries visuals (a recording, the images in the body, has_drawing: true for a drawing made on the asset) - call get_annotated_frames(id) once per such item: it shows every #rt link, drawing and image.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
element_idYesFeedback item ID to retrieve: the id field of an item from feedback_list, recent_activity, search or wait_for_feedback

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already cover readOnly/idempotent/non-destructive, and the description layers on substantive behavior the annotations cannot convey: the full return shape, that pipeline_status means the transcript is final only once complete, and the Markdown conventions (#t=S for video seconds, #rt=S for spoken phrases) that an agent must parse.

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?

Purpose and usage are front-loaded before the long return-value enumeration, and with no output schema that enumeration earns its space. The single dense paragraph and the redundant restatement of element_id provenance are the only waste.

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?

No output schema exists, so the description must carry the return contract — and it does, enumerating text, tags, author, recording fields, transcript status, visual_references, visuals and replies. It also closes the loop by telling the agent when a follow-up get_annotated_frames call is required.

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 description already says element_id comes from an item in feedback_list, recent_activity, search or wait_for_feedback. The description restates that same provenance rather than adding new meaning (e.g. format, edge cases for cross-asset ids), so the schema does the heavy lifting and baseline 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?

States a specific verb and resource — 'Get a single feedback item with its full reply thread' — which immediately separates it from feedback_list (which lists) and from feedback_post. The distinction is reinforced later by naming feedback_list as the listing alternative.

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?

Gives explicit when-to-use conditions: 'Use it when an item has replies (feedback_list gives reply_count, not the replies) or to read one item again', plus an explicit when-not with the alternative ('to list an asset's feedback use feedback_list'). It also prescribes the follow-up call to get_annotated_frames for items carrying visuals.

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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