A
licenseA
qualityC
maintenancePre-execution cost estimation for LLM agent workflows, providing cost estimates before running tasks and improving accuracy over time through calibration.
6
72 PyPI
2
MIT
Swatch Ledger
Server Details
Fabric shrinkage from a swatch wash test, and how much fabric to buy before washing.
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- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
A4/5.0
Scored across 2 tools
Disambiguation5/5
The two tools have clearly distinct purposes: one computes shrinkage from before/after measurements, while the other plans purchase length using a shrinkage rate. An agent can easily tell which tool to use based on whether it needs measurement calculation or purchase-length planning.
Naming Consistency5/5
Both tool names follow a consistent snake_case verb_noun pattern: measure_fabric_shrinkage and plan_fabric_length. The shared fabric-related noun phrasing makes the set predictable.
Tool Count3/5
Two tools is thin for a server framed as a swatch ledger, though the count may be reasonable for a narrowly scoped fabric calculator. It sits at the borderline of being too few for the apparent domain.
Completeness2/5
The tools cover shrinkage measurement and fabric purchase planning, but a ledger domain would typically require creating, retrieving, listing, or updating swatch records. There is no persistence or history surface, which is a significant gap for a server named Swatch Ledger.
Available Tools
2 toolsmeasure_fabric_shrinkageMeasure fabric shrinkageARead-onlyIdempotentInspect
Calculates fabric shrinkage (or growth) from a swatch measured before and after washing and drying: length change along the selvedge, width change across the fabric, and the change in area. Use the same marked distances before and after, in one unit (cm or inches). Positive percentages are shrinkage, negative are growth.
| Name | Required | Description | Default |
|---|---|---|---|
| unit | No | Unit of the four measurements (only used to label the answer). Default cm. | |
| width_after | Yes | The same marked width after washing and drying. | |
| length_after | Yes | The same marked length after washing and drying. | |
| width_before | Yes | Marked width before washing (across the fabric), greater than 0. | |
| length_before | Yes | Marked length before washing (along the selvedge), greater than 0. |
TDQS
A4.5/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish that this is read-only, idempotent, non-destructive, and closed-world. The description adds important behavioral meaning by explaining that positive percentages mean shrinkage and negative percentages mean growth, which is not captured by the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three tight sentences, front-loads the calculation, then adds the essential input constraint and output interpretation. Every sentence adds useful information with no repetition or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although there is no output schema, the description explains the output in terms of shrinkage/growth percentages and area change. Combined with rich parameter descriptions and annotations, it contains everything needed to call and interpret this calculation tool correctly.
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?
Schema coverage is 100%, so the schema already documents all five parameters thoroughly. The description adds useful meaning beyond the schema by reinforcing consistent marked distances, one-unit measurement, and the shrinkage/growth sign convention.
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 states a precise verb and resource: it calculates fabric shrinkage or growth from before/after wash measurements. It specifies length along the selvedge, width across the fabric, and area change, which clearly separates it from the sibling planning tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives clear usage guidance: use the same marked distances before and after and keep all four measurements in one unit. It does not explicitly name when not to use it or compare against plan_fabric_length, so it is not a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
plan_fabric_lengthPlan fabric length to buyARead-onlyIdempotentInspect
Works out how much fabric to buy before washing so that the usable length needed remains afterwards: required length = (usable length + extra) ÷ (1 − lengthwise shrinkage), then rounded up to the shop’s selling increment. Works in metres or yards (any one unit). A negative shrinkage rate means growth.
| Name | Required | Description | Default |
|---|---|---|---|
| unit | No | Unit of the lengths (only used to label the answer). Default m. | |
| extra_length | No | Optional extra usable length after washing (default 0). Do not count an allowance the pattern already includes. | |
| usable_length | Yes | Length needed after washing (check the pattern layout), greater than 0. | |
| shop_increment | No | The shop’s selling increment to round up to, e.g. 0.25 for quarter metres or 0.125 for eighth yards. 0 for no rounding (default 0). | |
| shrinkage_percent | Yes | Measured lengthwise shrinkage in percent, e.g. 5 for 5%. Negative means growth. |
TDQS
A3.9/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower; the description still adds real behaviour: the exact formula, round-up-to-selling-increment behaviour, unit handling, and the edge case that negative shrinkage means growth. Minor gap: it never states plainly that the returned value is the purchase length.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose and immediately followed by the formula that determines the answer. No filler; every clause (unit flexibility, negative shrinkage) carries information the caller needs.
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?
For a pure calculation tool with no output schema and annotations covering the safety profile, the description supplies the formula, rounding rule, unit labelling, and the negative-shrinkage edge case. Only the exact shape of the result is left implicit, which is a small residual gap.
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?
Schema coverage is already 100%, and the description goes beyond it by showing how the parameters compose — usable length plus extra, divided by one minus shrinkage, then rounded to the shop increment, with the unit used only for labelling. It also flags that a negative shrinkage rate is growth, reinforcing the schema's -100..100 range.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb and resource: 'Works out how much fabric to buy before washing so that the usable length needed remains afterwards.' The boundary with the sibling measure_fabric_shrinkage is implicit in the pre-wash purchase-planning framing, but the description never names that sibling to make the split explicit.
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?
Usage is implied rather than stated — 'before washing' and 'how much fabric to buy' signal the scenario, and 'Works in metres or yards (any one unit)' constrains inputs. There is no explicit when-to-use / when-not-to-use rule and no pointer to measure_fabric_shrinkage as the alternative for the measurement step.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
- First observed
measure_fabric_shrinkage - First observed
plan_fabric_length
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