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Glama

triz_trim

Screen removal of one or more boxes against TRIZ trimming rules to find per-function absorbers, orphaned blocking functions, removed harms and costs, and a trimming problem per absorber.

Instructions

Screen a trimming of one or more boxes by the TRIZ trimming rules: A (object trimmed too, function no longer needed), B (the object performs the function itself), C (another remaining box or supersystem resource has an output of the same carrier). Returns per-function absorbers, orphaned functions that block the trim, harms and costs removed, and one trimming problem per absorber. A carrier match is a necessary condition only; every absorber is a hypothesis to solve and substantiate.

Input Schema

NameRequiredDescriptionDefault
trimYesIds of the boxes to remove
modelYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the returned sections (per-function absorbers, orphaned functions blocking the trim, harms and costs removed, one problem per absorber) and warns that a carrier match is only a necessary condition. The main gap is that it never states explicitly that the tool is read-only analysis and does not mutate the model.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three dense sentences, front-loaded with the purpose and then the rules and outputs; no filler. The rule-letter parentheticals are long but earn their place by making the screening criteria self-contained.

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?

Given a huge embedded model schema and no output schema, the description supplies what an agent needs: what the screening does, what comes back, and how to interpret the result. Only the relationship to sibling trim/absorber tools is unaddressed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description's phrase 'trimming of one or more boxes' matches the `trim` array of box ids, which the schema already documents as 'Ids of the boxes to remove'. The `model` parameter is an unlabeled $ref whose semantics come entirely from the nested schema, so the description adds little beyond structured data at 50% coverage.

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?

The description opens with a specific verb and resource ('Screen a trimming of one or more boxes') and enumerates the three TRIZ trim rules A/B/C, so an agent can tell what the tool computes. It does not name the closely related siblings (triz_trim_rewrite, triz_absorber_assignments), which keeps it from a 5.

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: this is the screening/verification step for a candidate trim, and the closing sentence tells the agent to treat every absorber as a hypothesis to substantiate. However, there is no explicit statement of when to prefer this over triz_trim_rewrite or triz_absorber_assignments, so routing among siblings is left to inference.

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