Barbell strength training tools for AI assistants. Warmup, plate loading, and LP.
Generate a structured 4-week novice linear progression program for a new or early-intermediate barbell trainee. Based on the Starting Strength model: squat every session, alternating press/bench, deadlift progressing to power cleans. Takes lifter profile (sex, bodyweight, age, training days) and optional starting weights. Returns a week-by-week program with progression scheme and coaching notes. Powered by CoachSync.io.
| Name | Required | Description | Default |
|---|---|---|---|
| age | Yes | Lifter's age in years | |
| sex | Yes | Biological sex, used for estimating starting weights and progression rates | |
| bodyweightLb | Yes | Lifter's bodyweight in pounds | |
| trainingDays | No | Training days per week. 3 is standard, 2 is an alternative for recovery-limited trainees. | |
| startingBench | No | Optional starting bench work weight. If omitted, estimated from bodyweight. | |
| startingPress | No | Optional starting press work weight. If omitted, estimated from bodyweight. | |
| startingSquat | No | Optional starting squat work weight. If omitted, estimated from bodyweight. | |
| startingDeadlift | No | Optional starting deadlift work weight. If omitted, estimated from bodyweight. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description confirms that it returns a program (read operation) and adds details about the output (week-by-week, progression scheme, coaching notes). No contradiction; description adds value beyond annotations by describing the return content.
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?
The description is four sentences, front-loaded with the primary action, and each sentence serves a distinct purpose (what, model, inputs/outputs, attribution). No redundant or vague language.
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?
The tool has 8 parameters, no output schema. The description explains the output format (week-by-week program with progression scheme and coaching notes) and covers input categories. It could provide more detail on return structure or limitations, but is adequate for an agent to understand what the tool does.
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?
Schema description coverage is 100% (all 8 parameters described). The description groups parameters as 'lifter profile' and 'optional starting weights', adding structural context. However, it does not add significant meaning beyond the schema, so score is baseline 3.
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 clearly states the verb 'Generate', the resource 'structured 4-week novice linear progression program', and the target audience 'new or early-intermediate barbell trainee'. It distinguishes from siblings (plate_loader, warmup_calculator) by specifying the program content and model (Starting Strength).
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 provides context for when to use the tool (for novice or early-intermediate barbell trainees) and what it is based on (Starting Strength model). It implies the tool is for program generation, not for loading plates or warmups. However, it does not explicitly state when not to use it or compare to other program generators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Calculate which plates to load on each side of the barbell to reach a target weight. Supports custom bar weights and custom plate inventories for home gyms. Powered by CoachSync.io.
| Name | Required | Description | Default |
|---|---|---|---|
| unit | No | Weight unit. Defaults to lb. | lb |
| barWeight | No | Bar weight. Defaults to 45 lb. | |
| targetWeight | Yes | The total target barbell weight (bar + plates) | |
| availablePlates | No | Optional list of available plate denominations. Defaults to standard plates [45, 25, 10, 5, 2.5]. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds no behavioral context beyond what the schema describes (e.g., it doesn't mention auth, rate limits, or side effects). Minor branding fluff does not detract but also doesn't add value.
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 that front-load the core purpose. The inclusion of 'Powered by CoachSync.io' is minor branding fluff but not harmful. Overall efficient with no unnecessary details.
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?
The description explains the general purpose but fails to describe the output format (e.g., list of plates per side) or handle edge cases. Since no output schema exists, the description should provide more context on what the tool returns. This leaves gaps for the agent.
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?
Schema description coverage is 100%, so each parameter is already documented clearly. The tool description reinforces the idea of custom bar weights and plate inventories but does not add new semantic meaning beyond the schema descriptions. Baseline of 3 is appropriate.
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 clearly states the tool calculates plate loading for a target weight, using specific verbs and resource (barbell plates). It mentions custom bar weights and plate inventories, which adds clarity. However, it does not explicitly differentiate from sibling tools like novice_lp_generator or warmup_calculator, so it's not a 5.
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 implies usage for calculating plate loads in home gyms with custom options, but does not provide explicit when-to-use or when-not-to-use guidance relative to alternatives. Usage context is inferred but not directly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Calculate a barbell warmup ramp for any lift. Returns a structured set of warmup sets leading up to the work weight, with decreasing reps as weight increases. Based on standard barbell warmup methodology used in Starting Strength coaching. Powered by CoachSync.io.
| Name | Required | Description | Default |
|---|---|---|---|
| liftType | Yes | The lift being warmed up for (e.g. squat, bench, press, deadlift) | |
| barWeight | No | Bar weight. Defaults to 45 lb (20 kg). Use 35 for a women's bar, 15 for a training bar. | |
| workWeight | Yes | The target work set weight in pounds (or kg if unit is kg) | |
| roundingIncrement | No | Round warmup weights to this increment. Default 5. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With annotations indicating read-only, idempotent, and non-destructive behavior, the description adds behavioral context about returning a structured set with decreasing reps. It does not disclose output format or edge cases, but this is acceptable for a simple calculation tool.
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 sentences efficiently convey purpose and methodology, though the 'Powered by CoachSync.io' is minor fluff. Well-structured and front-loaded.
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?
Given the simplicity of a calculator tool and no output schema, the description adequately explains what the tool does and how the warmup ramp is structured. It could mention the return format but is sufficient.
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?
Schema coverage is 100%, so the description does not need to explain parameters. It adds no new semantic detail beyond the schema, meeting the baseline.
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?
Description clearly states it calculates a barbell warmup ramp for any lift, distinguishing it from sibling tools that generate programs or load plates.
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 implies usage for warming up before a work set but does not provide explicit when-to-use, when-not-to-use, or comparisons with siblings like novice_lp_generator or plate_loader.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
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Each tool serves a clearly distinct purpose: program generation, plate calculation, and warmup calculation. No overlap or ambiguity.
All tool names follow a consistent pattern: noun_verb in snake_case, each ending with '-er' (generator, loader, calculator). Conventions are uniform.
With 3 tools, the set is on the smaller side but still covers core functionality for a barbell training assistant. The tools are well-scoped and non-redundant.
The set covers program generation, plate loading, and warmup calculation—core tasks for a Starting Strength coach. Minor gaps like progress tracking or deload calculation are absent but not critical for the stated purpose.
