Skip to main content
Glama
gchen19

AnkusDrive

by gchen19
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Tolerance Cost Check

tolerance_cost_check
Read-only

Price tolerance schemes against manufacturing processes to flag cost-driving tolerances and secondary operations before quoting.

Instructions

Price a tolerance scheme against the process that has to hold it — the missing link between tolerance_stackup ("what tolerance works") and cost_estimate ("what does it cost").

Per toleranced dimension: its ISO 286 IT grade as a FLOAT (a band between IT6 and IT7 reports 6.4, not 7), the cheapest machining operation that holds that grade naturally (drilling ~IT11, milling ~IT10, turning ~IT9, reaming ~IT7, grinding ~IT6), a relative cost index normalised to 1.0 at process's natural capability, and a verdict: 'ok', 'in_process_tightening' (tighter but reachable in the same operation), or 'needs_secondary_operation' — the flag, meaning the part silently acquired an operation nobody costed. pass is false when any link flags. Cost roughly doubles every 1.5 IT grades tightened below natural capability; above it only inspection/scrap falls. total_cost_index is the sum, so two tolerance SCHEMES over the same chain compare directly.

chain is the same [{name, nominal, plus, minus | tol}] tolerance_stackup takes; instead pass a live handle (+ axis, default_tol, general) and the chain is derived off the solid the same way. process: cnc | injection | casting | sheet | fdm | drilling | milling | turning | boring | reaming | grinding | honing | lapping.

fidelity='correlation', band_pct=50 — the RATIOS are defensible, the absolute index is dimensionless and is not money. Returns {process, links:[{name, nominal_mm, band_mm, it_grade, cost_index, verdict, cheapest_operation, natural_it, note}], n_links, total_cost_index, mean_cost_index, flagged, pass, fidelity, band_pct, basis, escalate_to}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
axisNo+z
chainNo
handleNo
generalNom
processNocnc
default_tolNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

The annotations only state readOnlyHint=true, so the description must carry behavioral weight—and it does. It discloses the verdict semantics, the cost-index scaling rule ('Cost roughly doubles every 1.5 IT grades tightened below natural capability'), the flag behavior ('part silently acquired an operation nobody costed'), and the pass/fail aggregation across links. This is far beyond what annotations provide.

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 dense but front-loaded: the one-sentence purpose comes first, followed by behavioral rules, parameter semantics, and the return shape. Every sentence contributes meaningful information, including caveats like 'the absolute index is dimensionless and is not money.' Despite its length, it avoids padding.

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 tool with no output schema and no parameter descriptions, the description covers a great deal: purpose, process enum, defaults, verdict semantics, and the return object. The only gaps are that output fields like basis and escalate_to are listed without explanation, and default_tol/general semantics are not fully spelled out. Overall, still highly complete for the tool's complexity.

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 description coverage is 0%, so the description must compensate. It explains chain, handle, the handle-related parameters (axis, default_tol, general), and the full process enum. However, axis, default_tol, and general are only listed, not individually defined, leaving some reliance on the reader's familiarity with tolerance_stackup.

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 opens with a specific verb and resource: 'Price a tolerance scheme against the process that has to hold it.' It explicitly positions itself relative to tolerance_stackup and cost_estimate, making it immediately clear what this tool adds and how it differs from those siblings.

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?

The description provides clear context by naming tolerance_stackup ('what tolerance works') and cost_estimate ('what does it cost') and calling this tool the 'missing link' between them. It also explains the chain-as-alternative-to-handle input modes. It does not give explicit when-not-to-use conditions, but the positioning is strong enough for an agent to route correctly.

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

Deploy Server

Other Tools