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plan_turn

Read-onlyIdempotent

Route new coding tasks to the right starting point by combining code search, session memory, and framework-aware suggestions. Returns verdict, ranked targets, and next steps to avoid empty-result hallucinations.

Instructions

Opening-move router for new tasks. Combines BM25/PageRank search + session journal (negative evidence + focus signals) + framework-aware insertion-point suggestions + change-risk + turn-budget advisor into ONE call. Returns verdict (exists/partial/missing/ambiguous), confidence, ranked targets with provenance, scaffold hints when missing, and recommended next tool calls. Call this FIRST on a new task to break the empty-result hallucination chain. Read-only. For broader task context with source code use get_task_context instead. Returns JSON: { verdict, confidence, targets, scaffoldHints, nextSteps }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesNatural-language task description (e.g. "add a webhook endpoint for stripe payments")
intentNoOptional intent hint; auto-classified from task if omitted
skip_riskNoSkip change-risk assessment for the top target (default false)
max_targetsNoCap on returned targets (default 5)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv3.3.0
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
  2. Addedv1.41.0
  3. Removedv1.38.0
  4. Changed1 schema field changedv1.35.1
    • removedInput schema / additionalProperties
      Removed value: -false
  5. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already mark this read-only, idempotent, and non-destructive, and the description reinforces this with 'Read-only.' It adds behavioral context by explaining the tool's combined search/journal/risk mechanism and its role in preventing empty-result hallucinations, going beyond what annotations alone convey.

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 information-dense and mostly front-loaded, starting with the primary purpose and usage call-to-action. The long enumeration of combined capabilities and the slight redundancy between 'Returns...' and 'Returns JSON: {...}' keep it from being perfectly concise, but every sentence contributes needed context.

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?

Despite the absence of an output schema, the description states the JSON shape, the verdict values, the provenance of ranked targets, scaffold hints, and recommended next steps. Combined with the explicit usage instruction and alternative tool pointer, an agent has what it needs to invoke the tool correctly on a new task.

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%, and each parameter already has a clear description with defaults and constraints. The tool description does not meaningfully add parameter-level guidance, so it meets the baseline but does not exceed it.

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 opens with 'Opening-move router for new tasks' and lists a concrete deliverable set: verdict, confidence, ranked targets with provenance, scaffold hints, and recommended next tool calls. It also explicitly distinguishes itself from get_task_context, so an agent can select it correctly among siblings.

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?

The description states exactly when to use it: 'Call this FIRST on a new task to break the empty-result hallucination chain.' It also names the alternative, get_task_context, and the condition for preferring that instead ('broader task context with source code'), giving clear, actionable routing guidance.

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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