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list_actionable

List actionable items with epic context, including epic goals and story coverage, to identify what to do next.

Instructions

List what can be acted on right now, with epic context.

Returns the epic's goals, story coverage, and a table of actionable items. Always show the full table to the user first, then add your recommendation below it. The table is the primary output — the user needs to see all options to make their own call.

After showing the table, recommend what to do next:

  1. Check whether the stories cover the epic's goals. If goals are uncovered, recommend more planning (create_story) before execution.

  2. Urgent items (unverified or in-progress tasks) should usually be finished before starting new work.

  3. For the remaining items, read the tickets that look relevant (get_ticket) and recommend based on impact — what unblocks the most work, what aligns with current momentum, why now.

  4. If several items are genuinely equal, say so and explain why.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.4

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses what the tool returns (goals, story coverage, actionable items table) and prescribes presentation behavior (show the full table first, add recommendation below). It does not discuss side effects, but 'List' and 'Returns' imply a read-only operation.

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 front-loaded with the core purpose and output summary, then uses a clear numbered checklist for recommendations. It is longer than strictly necessary, but each section earns its place by guiding the agent's behavior after invoking the tool.

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?

For a zero-parameter listing tool with no annotations, the description is remarkably complete. It explains the output, the required presentation order, how to interpret coverage, when to recommend planning, how to prioritize urgent items, and how to handle ties.

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?

The tool has zero parameters, so the baseline is 4. There is no parameter semantic burden for the description to carry, and it appropriately focuses on output and usage behavior instead.

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 starts with a specific verb and resource: 'List what can be acted on right now, with epic context.' It clearly differentiates this from a generic ticket listing by emphasizing epic goals, story coverage, and an actionable table. The output contents are enumerated, making the tool's purpose concrete.

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?

The description gives strong context on how to use the tool's output: present the table first, then recommend next steps, and it names related tools like create_story and get_ticket for follow-up actions. It does not explicitly contrast itself with list_tickets or say when not to use it, so it falls short of full exclusion guidance.

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