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baatjie-mcp-server

by dantalan

What Can Actually Be Started Now

baatjie_next_actions
Read-onlyIdempotent

List todos that are ready to start (all blockers done), ranked by downstream unblocking impact, to answer 'what should I do next?'

Instructions

Return the todos that are genuinely startable right now — every blocker done — ranked by how much each one unblocks downstream.

This is the tool to reach for when asked "what should I do next", "what's the priority", or "what's blocking us". A raw todo list hides the fact that most items cannot be started; this one answers the question the list is standing in for.

Args:

  • track ('A' | 'B' | 'SPINE' | 'TODAY', optional): Restrict to one workstream. A = agency business, B = payroll housing rail, SPINE = shared infrastructure, TODAY = time-boxed launch-day items

  • priority ('critical' | 'high' | 'medium' | 'low', optional): Minimum priority

  • include_blocked (boolean): Also list blocked items with their blocker counts (default: false)

  • limit (number): Max items (default: 25)

  • response_format ('markdown' | 'json'): Output format

Returns: { "startable": [{ "id","title","priority","track","wave","effort","unblocks" }], "blocked_count": number, "roots": [...], // startable items that unblock the most "summary": { "total","startable","blocked","by_priority": {...} } }

Examples:

  • "What should I work on?" -> no args

  • "What's next on the housing rail?" -> track='B'

  • "Show me everything including what's stuck" -> include_blocked=true

Error Handling:

  • Returns an empty startable list with an explanation if every open item is blocked, which itself signals the roots need attention first

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum rows to return (1-200, default 25)
trackNoRestrict to one workstream
priorityNoMinimum priority to include
include_blockedNoAlso return blocked items
response_formatNoOutput format: 'markdown' for human-readable, 'json' for machine-readablemarkdown
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds valuable behavioral context beyond that: it explains ranking by how much each todo unblocks downstream, how blocked items are handled (included only if include_blocked=true), and the error behavior when all items are blocked (returns empty list with explanation). It also discloses the return structure in detail. There is no contradiction 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 well-structured with clear sections: purpose, usage context, parameters, return structure, examples, and error handling. The opening sentence is concise and informative, front-loading the core purpose. While it is longer than minimal, every section earns its place and there is no redundant filler. The use of a JSON example for returns and example queries improves scannability.

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?

Given that there is no output schema, the description fully compensates by specifying the return structure with an example JSON object, including fields like startable, blocked_count, roots, and summary. It also covers error handling (empty startable list explanation) and provides practical examples for different use cases. Combined with the annotations and schema, the description leaves no significant gaps for an agent to invoke the 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 description coverage is 100%, so the baseline is 3, but the description adds meaningful semantics beyond the schema. For example, it expands the track enum values ('A = agency business, B = payroll housing rail, SPINE = shared infrastructure, TODAY = time-boxed launch-day items') and clarifies include_blocked as 'also list blocked items with their blocker counts' rather than just 'also return blocked items'. This additional context helps the agent select the correct parameter values.

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 clearly states the tool's function: 'Return the todos that are genuinely startable right now — every blocker done — ranked by how much each one unblocks downstream.' This is a specific verb+resource with a distinct scope (startable todos) and a clear ranking behavior, which distinguishes it from a raw todo list. The title 'What Can Actually Be Started Now' reinforces the purpose. It effectively differentiates from sibling tools like baatjie_list_todos by emphasizing the filtering and ranking of startable items.

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 explicitly tells users when to use this tool: 'This is the tool to reach for when asked "what should I do next", "what's the priority", or "what's blocking us"' and contrasts it with a 'raw todo list' that hides startability. While it identifies the alternative conceptually, it doesn't name the specific sibling tool (e.g., baatjie_list_todos), which would make the guidance more actionable. Examples also illustrate common use cases with specific arguments, but it doesn't explicitly state when not to use it beyond the raw list contrast.

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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