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by io.github.Onplana
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resource_leveler_analyze

Destructive

Analyze resource allocation for a project. Returns per-user, per-week overallocations and suggested task reschedules to flatten the load. Deterministic (no AI call), fast and free to call on every plan that includes resourceMgmt (PRO+). Use mode="preview" (default) to inspect suggestions before committing; use mode="apply" to capture a baseline and apply all suggested reschedules immediately (requires project Owner or Manager role). Use this before leveling_narrative to get the raw data, or directly to answer "who is overloaded and by how much this week?"

Input Schema

NameRequiredDescriptionDefault
modeNopreview (default): return analysis without writing. apply: capture a baseline then apply all reschedule suggestions. Requires project Owner or Manager role.preview
projectIdYesID of the project to analyze for resource overallocation.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / mode
      Added value: +{
+  "default": "preview",
+  "description": "preview (default): return analysis without writing. apply: capture a baseline then apply all reschedule suggestions. Requires project Owner or Manager role.",
+  "enum": [
+    "preview",
+    "apply"
+  ],
+  "type": "string"
+}
  2. Added

TDQS

A4.6/5.0
Behavior5/5

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

Adds substantial context beyond the annotations: determinism (no AI call), cost profile (fast and free to call), the fact that apply captures a baseline and mutates immediately, and the Owner/Manager role requirement. This clarifies that only mode=apply is destructive, which the destructiveHint annotation alone cannot 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?

Front-loads the purpose and then the mode guidance; every sentence is doing work, though the mode explanation partially duplicates the schema. Appropriately sized with no filler.

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 two-parameter tool with no output schema, the description supplies the return contents, cost/determinism expectations, mutation semantics, and permission requirements, so an agent has everything needed to invoke it correctly.

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 coverage is 100% and the schema already documents both mode and projectId in detail, so the description mainly restates the preview/apply semantics. Baseline 3 is appropriate when the schema carries the parameter detail.

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 ('Analyze resource allocation for a project') and describes the return shape ('per-user, per-week overallocations and suggested task reschedules'). It is clearly distinguishable from the narrative-oriented sibling leveling_narrative.

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 covers when to use each mode (preview to inspect before committing, apply to capture baseline and commit) and routes the agent relative to an alternative ('Use this before leveling_narrative to get the raw data, or directly to answer...').

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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