FERS — structural FEM

Generate EN 1990 combinations

generate_load_combinations_ec0

Read-only

Generate a complete EN 1990 (Eurocode 0) combination set from the model's load cases in one call, instead of adding them one at a time. Classify each load case as an action type — G permanent, Q imposed, S snow, W wind — and this emits ULS expression 6.10 (each variable action taken as leading in turn, with psi_0 on the accompanying ones) and the SLS characteristic combinations, including the favourable-permanent (gamma_G = 1.0) variants that govern wind uplift. Every generated combination carries a limit_state, so unity checks actually evaluate against them. Any load case you do not classify is guessed from its name. Free.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "actions": "<actions>"
    },
    "name": "generate_load_combinations_ec0"
  }
}

Input Schema

Name	Required	Description
`model`	No	Stringified FERS model JSON
`actions`	Yes	Action type per load case: {"1":"G","2":"S","3":"W"} or [{"load_case_id":1,"action":"G"}]. G = permanent, Q = imposed, S = snow, W = wind. Unclassified cases are guessed from their name.
`model_ref`	No	Handle from stash_model, used INSTEAD of `model`. Avoids sending the whole document on every step; the tool returns the same handle back.
`include_sls`	No	Emit SLS characteristic combinations (default true).
`include_uls`	No	Emit ULS 6.10 combinations (default true).
`replace_existing`	No	Replace analysis.load_combinations entirely instead of appending (default false).
`include_favorable`	No	Emit the gamma_G = 1.0 favourable-permanent ULS variants, which govern uplift (default true).

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 21, 2026

TDQS

A4.3/5.0

Behavior5/5

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

Goes well beyond the annotations: explains that ULS 6.10 treats each variable action as leading in turn with psi_0 on accompaniments, emits SLS characteristic and favourable gamma_G=1.0 uplift variants, attaches limit_state so unity checks evaluate, and guesses unclassified cases by name. The readOnlyHint is not directly contradicted since the writes apply to the supplied/stashed model document rather than external state.

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?

Front-loads the core action and the sibling contrast, then layers in the technically important details. Slightly dense and run-on in the middle sentence, but each clause carries substantive information.

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 7-parameter tool with no output schema, the description explains what gets emitted, the defaults, and the uplift/favourable behavior an agent needs. It does not describe the return shape or handle semantics in detail, but the model_ref schema covers that adequately.

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?

Schema description coverage is 100%, so the schema already documents all 7 parameters, setting the baseline at 3. The description adds the action-letter taxonomy (G/Q/S/W) and the name-guessing fallback, but most parameter meaning is already in the schema.

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?

States a specific verb+resource: generate a complete EN 1990 combination set from model load cases, and explicitly contrasts with the one-at-a-time alternative in add_load_combination. An agent can identify exactly what this produces and how it differs from the sibling add tools.

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?

Says to use it 'in one call, instead of adding them one at a time,' effectively pointing at the sibling add_load_combination and the condition that favors bulk generation. It implies the context of building a full combination set but does not spell out explicit exclusions or when-not cases.

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

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