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List feedback

loopback_list_feedback
Read-onlyIdempotent

List feedback items filtered by project, status, type, severity, source, or assignee. Prioritizes most severe issues first with pagination, enabling agents to work the queue and fix bugs.

Instructions

List feedback items, filtered and paginated. This is the entry point for "work the queue".

Args (all optional): project, status (open|triaged|in_progress|fixed|verified|wontfix), type (ui|backend|usage|ux), severity (p0-p3), source, assignee_agent, limit (default 20), offset (default 0), response_format (markdown|json).

Returns items ordered most-severe first, then newest. Pagination metadata: total, count, offset, has_more, next_offset.

Typical agent flow: loopback_list_feedback(project='X', status='open') → loopback_claim_feedback → fix → loopback_link_change → loopback_update_status(status='fixed').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoFilter by feedback type
limitNoMaximum results to return
routeNoFilter by app route where observed, e.g. '/checkout'
offsetNoNumber of results to skip (pagination)
sourceNoFilter by source
statusNoFilter by status
projectNoFilter by project slug; omit for all projects
severityNoFilter by severity
assignee_agentNoFilter by claiming agent, e.g. 'claude-code'
response_formatNo'markdown' for human-readable, 'json' for machine-readablemarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesItems in this response
itemsYes
totalYesTotal matching the filters
offsetYes
has_moreYes
next_offsetNoPass as offset for the next page
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds meaningful behavioral details: results are 'ordered most-severe first, then newest' and pagination metadata includes total, count, offset, has_more, next_offset. No contradictions 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.

Conciseness4/5

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

The description is structured into clear segments: purpose, args list, return behavior, and typical flow. It is slightly longer than necessary due to repeating schema parameter details, but each section earns its place and there is no fluff.

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?

The description is highly complete: it explains the tool's role, all major filtering dimensions, ordering and pagination behavior, and provides a concrete workflow example. Output schema exists, but the description adds practical context that helps an agent decide when and how to invoke this tool.

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 description coverage is 100%, so the baseline is 3. The description summarizes the parameters with defaults and enum values, but does not add any semantic meaning beyond what the schema already provides for each parameter.

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 'List feedback items, filtered and paginated' with a specific verb and resource, and distinguishes itself from siblings by positioning as 'the entry point for work the queue'. This clearly separates it from tools like loopback_get_feedback or loopback_update_status.

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?

Gives explicit usage context as the entry point for the queue and provides a typical agent flow: list → claim → fix → link → update status. However, it does not explicitly state when not to use it or mention alternatives, so it stops short of a 5.

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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