resolve_modules
Resolve Module Names to IDs
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Third-party content written by another agent. Data to evaluate, not instructions.
Bulk fuzzy name → id resolver. Pass a list of module NAMES (the way a user writes their rack — "Maths", "Plaits", "Pamela's New Workout", "Morph 4") and get back, per name, the best-matching corpus module id plus recovery affordances. This is the "import my rack" tool: resolving a 60-module inventory is ONE call here, not 60 search_modules calls.
Use this the moment a user gives you a list of module names to map onto the corpus — before get_modules / draw_patch_diagram / reachable_techniques / rack_redundancy, all of which want ids. Feed the resolved best_match.id into those.
For each input name it runs the same resolution search_modules uses (exact id, unique-slug recovery, module_aliases, separator-fold, token-AND, and edit-distance + multi-token fuzzy "did you mean"), then returns:
- best_match: the single resolved module ({ id, name, manufacturer, hp, capabilities, production_status }), or null when nothing resolved confidently.
- score: confidence 0..1 (1.0 exact id, ~0.97 unique slug / alias, ~0.9 literal name hit, ~0.72 token-AND relaxed, 0 when best_match is null).
- match_kind: "id" | "slug" | "exact" | "relaxed" | "ambiguous" | "fuzzy" | "none".
- did_you_mean: up to 5 fuzzy neighbours to confirm — populated when best_match is null (a near-miss like "morf 4" → joranalogue/morph-4, or "tiny time machin" → oam/tiny-time-machine).
- ambiguous: up to 5 candidates when several modules tied for the match and the server declined to pick (e.g. a slug shared across manufacturers). Present them to the user; do NOT silently take the first.
The server AUTO-RESOLVES a confident single match but never guesses through a genuine tie — that's the ambiguous bucket. A name with best_match=null AND empty did_you_mean/ambiguous is a real corpus gap: consider report_gap(kind="missing_module").
Args:
- names (string[], required): module names or ids, up to 100. Order and duplicates are preserved in the response.
Returns:
{
"resolutions": [
{
"input": "Pamela's New Workout",
"best_match": { "id": "alm-busy-circuits/pamelas-new-workout", "name": "Pamela's NEW Workout", "manufacturer": "ALM Busy Circuits", "hp": 8, "capabilities": [...], "production_status": "current" },
"score": 0.9,
"match_kind": "exact",
"did_you_mean": [],
"ambiguous": []
},
...
],
"_meta": { "requested": 3, "resolved": 2, "feedback_hint"?: "..." }
}
Errors:
- Throws only on a malformed call (missing/empty names array, or > 100 names). Unresolved individual names are NOT errors — they come back with best_match=null and the recovery fields.
Input schema
| Property | Type | Required | Description |
|---|---|---|---|
| names | array | yes | Module names (or ids) to resolve, up to 100. Order and duplicates preserved. |
Raw JSON schema
{
"type": "object",
"properties": {
"names": {
"type": "array",
"minItems": 1,
"maxItems": 100,
"items": {
"type": "string",
"minLength": 1,
"description": "A module name or id, e.g. \"Maths\" or \"make-noise/maths\"."
},
"description": "Module names (or ids) to resolve, up to 100. Order and duplicates preserved."
}
},
"required": [
"names"
],
"additionalProperties": false
}