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bjornj12

golf-coach

session_analysis

Classify and analyze your Trackman golf session as warm-up, practice, or game, compute key metrics, and compare with prior sessions to track progress and spot weaknesses.

Instructions

Per-session analysis (deterministic classification + metrics, stored locally).

Actions:

  • analyze (needs activity_id): fetch a session, classify it (warm-up vs serious practice vs game), compute metrics, normalize vs prior stored sessions, store the record (last 30 kept), and return it.

  • get (needs activity_id): return one stored analysis record.

  • list: return the index of stored analyses (most recent first).

Drive this with the trackman-session-analyzer prompt.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYes
activity_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

The description discloses key behaviors beyond annotations: it stores records locally, keeps only the last 30, and mentions deterministic classification. This adds context to the non-read-only annotation by explaining side effects, though it could be richer (e.g., permissions, error behavior).

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 a concise bullet list of actions. The final instruction about the prompt adds some ambiguity but the overall length and organization are effective and mostly earn their place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema and clear action structures, the description provides sufficient context for a two-parameter tool. It covers storage behavior, action variants, and parameter requirements, though it could mention how to obtain activity_id or handle errors.

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?

With 0% schema description coverage, the description compensates by explaining the 'action' enum values and specifying that analyze and get require 'activity_id'. It could further define what activity_id represents, but the usage context is reasonably clear.

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 it performs per-session analysis with specific actions (analyze, get, list). It explicitly describes the classification task and storage of results, which distinguishes it from sibling tools like gamebook or training_plan.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for session analysis but does not explicitly state when to use this tool versus alternatives. It mentions driving with a specific prompt, but provides no exclusions or comparisons with sibling tools.

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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