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list_related_tasks

Read-onlyIdempotent

Poll for tasks tied to your work plus NEW human comments on them. Use this in your loop to react to feedback: a human commenting on a task you created can't call your session back, so you check here. scope: 'created_by_conversation' (default - tasks you created this session), 'created_by_persona' (tasks you created in ANY past session - use this to pick up comments on yesterday's tasks from a fresh run), 'mentioned_me' (tasks where a human @mentioned you - how they pull you into a task you didn't create), or 'assigned_to_me'. Pass includeCommentsSince = the polledAt from your last call so you only see new comments. Your own (agent) comments are excluded. limit max 50.

Input Schema

NameRequiredDescriptionDefault
limitNoDefault 25, max 50.
scopeNoDefault 'created_by_conversation'.
includeCommentsSinceNoISO-8601 timestamp. Only comments newer than this are returned. Default: 24h ago. Pass the previous response's polledAt to advance.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already cover readOnly/idempotent/openWorld/destructive, yet the description adds operational behavior beyond them: cursor advancement via the previous response's polledAt, exclusion of the agent's own comments, a 24h default window, and the limit ceiling. This is meaningful polling semantics, not restatement.

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?

Front-loads the core purpose and the loop rationale before enumerating scopes, and every sentence maps to a distinct decision an agent must make. It is dense but occasionally long-winded in the scope list; trimming would lose little but the length is mostly justified.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a stateless polling tool with no output schema, the description covers the missing pieces an agent needs: cursor handling (polledAt), self-comment exclusion, and default windowing. It stops short of describing the response shape or what fields each returned task carries, which is the only notable gap.

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, but the description adds genuine meaning: it explains the intent behind each scope enum (past-session pickup, @mention pull-in) and the intended usage pattern for includeCommentsSince (pass last polledAt) rather than just its format.

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 ('Poll for tasks tied to your work plus NEW human comments on them'), and the added 'NEW human comments' framing clearly separates it from list_tasks, list_my_tasks, and list_mentions. An agent can identify the distinct purpose without opening the schema.

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 prescribes when to call it ('Use this in your loop to react to feedback') and explains why (a human commenting cannot call the session back). Each scope value is given a condition for use, including the fresh-session case for 'created_by_persona' versus the default 'created_by_conversation'.

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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