Read controlled rules and profile memory with their hashes. Goals and results are available only through get_editable_goals_results. Use the returned hash as previousHash before previewing a rules/profile change.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral burden. It discloses that goals/results are excluded, the read returns hashes, and the hashes feed the preview workflow. This adds useful non-obvious context, though it could more explicitly state permission requirements or the read-only safety profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tightly written sentences with no wasted words. The first sentence states the purpose and return value; the second gives a crucial usage rule. Information is front-loaded and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema and no parameters, the description covers what is returned (hashes), what is not included (goals/results), and how to use the result in the preview workflow. This is a complete picture for a simple read tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description adds context about what data is read, which is sufficient since there are no parameters to clarify.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Read' and identifies the exact resources: 'controlled rules and profile memory' plus what is returned (hashes). It explicitly says goals/results are not available here, distinguishing it from sibling tools like get_editable_goals_results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It names get_editable_goals_results as the alternative for goals/results, and gives a concrete workflow instruction: use the returned hash as previousHash before previewing a rules/profile change. This clearly communicates when and how to use the tool relative to preview/commit siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource and action: plan events vs note events, goals/results vs profile sections, preview vs commit, history vs current sections. The boundaries are clearly defined in descriptions, so an agent can reliably select the right tool for a given task.
All tool names follow a predictable verb_noun snake_case pattern with consistent verbs (create, delete, get, preview, commit, read, restore, save). The use of 'get' for data retrieval and 'read' for profile-specific history/sections is internally consistent.
At 20 tools, the set is slightly above the typical 3-15 range, but the complexity of the coaching domain justifies the count. The preview/commit pairs and distinct resource types (goals, profile, plan, notes) each earn their place, though the set could be streamlined by merging some read tools.
The tool surface covers the main coaching workflows: reading athlete state, managing training plan and notes, editing goals/results, maintaining profile memory, and saving strategy. Minor gaps exist around explicit creation/deletion of goals and profile sections, which are not clearly supported outside the preview/commit flow.
