CoachSync

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

Annotations establish safety (readOnly, idempotent, non-destructive). Description adds crucial behavioral context: the specific exercise template (squat every session, alternating press/bench, deadlift-to-cleans progression) and output structure (week-by-week breakdown with coaching notes). No contradiction with annotations despite 'Generate' verb, as program generation here is computational/read-only.

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?

Four sentences with zero waste: sentence 1 establishes purpose and audience; sentence 2 details the specific programming model; sentence 3 covers inputs/outputs; sentence 4 provides attribution. Information is front-loaded with critical context (Starting Strength methodology) appearing early. No redundant or filler content.

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 8 parameters with full schema coverage and no output schema, the description adequately compensates by verbally describing the return structure ('week-by-week program with progression scheme and coaching notes'). Domain-specific details (Starting Strength model) provide necessary context for proper invocation, though an output schema would improve completeness further.

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?

With 100% schema coverage, baseline is 3. Description adds value by semantically grouping the 8 parameters into 'lifter profile' (sex, bodyweight, age, training days) and 'optional starting weights', helping the agent understand the conceptual structure. Reinforces the estimation behavior for omitted weights, aligning with schema descriptions.

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 explicitly states it generates a 'structured 4-week novice linear progression program' using specific verbs and resources. It clearly targets 'new or early-intermediate barbell trainees' and distinguishes itself from siblings (plate_loader, warmup_calculator) by focusing on program generation rather than calculation or loading assistance.

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?

Clearly identifies the target audience (new/early-intermediate trainees) and specifies the programming model (Starting Strength). Describes inputs and outputs sufficiently for an agent to determine applicability. However, lacks explicit 'when not to use' guidance or cross-references to sibling tools for alternative use cases.

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

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

Annotations already establish read-only, idempotent, non-destructive safety. The description adds crucial behavioral context that the calculation determines plates 'on each side of the barbell' (bilateral loading), which is not evident from the parameter schema alone. It also notes custom inventory support, hinting at flexibility in calculation logic.

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 front-loaded with the core purpose in the first sentence, followed by feature elaboration. It is appropriately sized at three sentences. The final attribution ('Powered by CoachSync.io') adds no functional value for tool selection but does not significantly detract from clarity.

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 100% schema coverage and comprehensive annotations (readOnly, idempotent, etc.), the description successfully fills the remaining gaps by explaining the per-side calculation logic. Without an output schema, noting that plates are calculated 'on each side' is essential contextual completeness for understanding return values.

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?

With 100% schema description coverage, the baseline is appropriately met. The description adds semantic mapping by referencing 'custom bar weights' (barWeight) and 'custom plate inventories' (availablePlates), reinforcing their purpose, but does not add syntax details or constraints beyond the schema.

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 opens with a specific action verb ('Calculate') and clearly defines the resource ('plates to load on each side of the barbell') to reach a target weight. It distinguishes from siblings 'novice_lp_generator' (program generation) and 'warmup_calculator' (warmup sets) by focusing specifically on plate loading arithmetic.

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 implied usage context by mentioning support for 'home gyms' with custom equipment, suggesting when this tool is valuable. However, it lacks explicit when-to-use guidance or contrasts with sibling tools (e.g., it doesn't clarify to use this for equipment setup vs. the others for programming).

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

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

Annotations declare readOnly/idempotent safety, allowing the description to focus on domain-specific behavior. Adds valuable context about output structure ('structured set of warmup sets... with decreasing reps as weight increases') and methodology provenance that annotations don't cover. 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?

Well-structured with purpose front-loaded in sentence 1, followed by output description and methodology. Three substantive sentences effectively convey the tool's function. Minor deduction for 'Powered by CoachSync.io' which provides no functional value to the agent.

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?

With no output schema provided, the description adequately explains the return value ('structured set of warmup sets'). Good annotations cover safety/behavioral traits. Could mention edge cases (e.g., what happens if workWeight is less than barWeight) but generally complete for a 4-parameter calculation 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?

Schema has 100% description coverage (barWeight includes units and common values), establishing baseline 3. The description adds domain context ('barbell', 'work weight') that aligns with parameters but doesn't provide additional parameter-specific guidance (e.g., 'workWeight should be your top working set weight, not 1RM').

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?

States specific verb ('Calculate') and resource ('barbell warmup ramp'). The phrase 'warmup ramp' clearly distinguishes this from sibling 'plate_loader' (which loads plates for a single weight) and 'novice_lp_generator' (which generates programs), establishing this tool's unique domain of calculating progressive warmup sets.

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?

Provides methodological context ('Based on standard barbell warmup methodology used in Starting Strength coaching') that implies usage context, but lacks explicit when-to-use guidance or differentiation from siblings. Does not state prerequisites or when to prefer this over 'plate_loader' for single-weight calculations.

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