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by io.github.Onplana
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leveling_narrative

Read-onlyIdempotent

Generate a prose summary of a project's resource leveling situation. Runs the deterministic overallocation analysis first, then asks the AI to explain WHY the suggested moves were chosen and what the trade-offs are. Returns a 2-3 sentence overall summary and a per-suggestion hint for each recommended task move. Feature: resourceMgmt (PRO+). Use this after resource_leveler_analyze when the user wants a plain- language explanation of the results, not just the raw numbers.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "projectId": "<projectId>"
    },
    "name": "leveling_narrative"
  }
}

Input Schema

NameRequiredDescriptionDefault
projectIdYesID of the project to narrate leveling results for.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false, openWorldHint=false), so the bar is lower, yet the description still adds real context: it discloses a two-stage internal pipeline (deterministic analysis first, then AI explanation), the shape of the return (2-3 sentence overall summary plus per-suggestion hints), and a licensing constraint ('Feature: resourceMgmt (PRO+)'). It stops short of noting AI-call cost or failure modes, so not a full 5.

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?

Four sentences, front-loaded with the purpose before the mechanics and the routing guidance. Each sentence contributes (purpose, internal behavior, return shape, usage/feature gate), though the return-shape and 'explain WHY' sentences overlap slightly.

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?

With no output schema, the description must describe returns, and it does so concretely (overall summary plus per-suggestion hint). For a low-complexity, single-required-parameter, read-only tool with annotations present, nothing an agent needs in order to call it correctly is missing.

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% for the single projectId parameter, so the schema already carries the meaning. The description adds no syntax, format, or constraint detail beyond it, which is the expected baseline for a fully documented single-param tool.

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 ('Generate a prose summary of a project's resource leveling situation') and immediately distinguishes itself from the sibling resource_leveler_analyze by framing itself as the explanatory layer on top of that analysis. An agent can tell it apart from other narrative tools (compose_evm_narrative, critical_path_narrative, summarize_project) by the resource-leveling subject matter.

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?

Explicit sequencing and selection criteria: 'Use this after resource_leveler_analyze when the user wants a plain-language explanation of the results, not just the raw numbers.' It names the prerequisite tool and the condition that selects this one over it.

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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