list_musclesList all muscles tracked in the wger database. Returns each muscle's numeric ID, English name, and whether it is located on the front of the body.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| count | Yes | Total number of muscles in the database | |
| muscles | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful context beyond annotations: it states the tool returns all muscles with specific attributes (numeric ID, English name, front/back location) and covers the entire wger database. No contradictions with annotations.
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 concise sentences front-loaded with the primary action. Every word serves a purpose—scope, return fields, and location attribute. No redundancy or filler.
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?
For a simple list tool with no parameters and comprehensive annotations, the description fully covers purpose, scope, and return fields. The presence of an output schema further reduces the need for additional explanation.
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 provides no parameter details (none exist) and focuses on return values, which is appropriate for a parameterless tool.
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 states a specific verb ('List') and resource ('all muscles tracked in the wger database'). It also specifies the returned fields (numeric ID, English name, front-of-body flag), making it distinct from sibling list tools like list_exercises and list_equipment.
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?
The description makes the usage context clear—listing all muscles—but does not explicitly mention when to use this tool versus alternatives (e.g., get_exercise). Use case is implied, not explicitly contrasted.
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.
Many tools have detailed, differentiated roles, but there are several overlapping clusters: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer natural-language data questions, and ask_pipeworx_beta is currently identical to ask_pipeworx. Onboarding/discovery and Polymarket edge tools also blur together, so an agent can easily select the wrong entry point.
Names are uniformly snake_case and readable, with coherent subfamilies like ask_pipeworx*, polymarket_*, and list_*. But conventions are mixed across the set: bare verbs (remember, forget, subscribe), noun phrases (entity_profile, recent_changes), and adjective-led names (recent_alerts) exist alongside verb_noun names, so there is no consistent pattern.
35 tools is already in the 'too many' range, and only four (get_exercise, list_exercises, list_equipment, list_muscles) belong to a wger fitness server. The remaining ~31 tools are unrelated Pipeworx/prediction-market/memory utilities, making the count inappropriate for the apparent domain.
As a wger fitness server, the surface is a read-only reference slice: exercise, equipment, and muscle lookups, with no workout routine management, user data, or create/update/delete operations for any wger resource. Even ignoring the unrelated Pipeworx tools, the fitness domain has severe gaps that would block most real usage.