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Glama

write_week_plan

Destructive

Assign routines to weekdays to build your weekly training schedule; empty lists mark rest days, and date-specific overrides still take precedence.

Instructions

Set the routines planned on weekdays, e.g. { "Monday": [pushId], "Friday": [pushId, legsId] }. Several routines on one day make a combined session; an empty list makes the day a rest day. Weekdays not given are left as they are. Date overrides (write_day_plan) still win on their dates. In rotation mode the weekdays stay in force on top of the loop (routines that are in the loop are not repeated on the loop's day), and going back to the fixed week uses them as they are. openGym merges settings and the plan one setting and one day at a time: only a device that changes the same setting or day later, before it syncs, keeps its own value.

Input Schema

NameRequiredDescriptionDefault
daysYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already flag destructive/openWorld, and the description goes well beyond them: it discloses merge semantics ('one setting and one day at a time', last-writer-before-sync wins), the leave-as-is default, and rotation-mode interaction. This is rich behavioral context an agent could not infer from annotations alone.

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 core purpose and packs substantial information into one paragraph, but the trailing openGym/merge sentence is dense and hard to parse, and could be split or trimmed without losing meaning.

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 single-parameter destructive write with no output schema, the description covers the write semantics, defaults, precedence against write_day_plan, and concurrency behavior. Nothing an agent needs to invoke it correctly appears to be missing.

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 0%, so the description carries the burden, and it largely does: the inline example shows the map-of-weekday-to-routine-id-list shape, and it explains the empty-list and omitted-key semantics. It does not fully pin down the allowed weekday key vocabulary or the routine-id format, so it only partly compensates for the coverage gap.

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+resource ('Set the routines planned on weekdays') and immediately distinguishes itself from write_day_plan (date overrides win) and from the rotation flow. An agent can tell what this writes and how it differs from its nearest siblings without opening any schema.

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?

Explains the key selection conditions: unspecified weekdays are left as-is, empty list means rest day, and write_day_plan takes precedence on its dates. It stops short of explicitly routing the agent to write_rotation/write_schedule_mode for changing modes, but the interplay guidance is strong.

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