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Delx Seeded Candidate Subset
x402
Delx Seeded Candidate Subset is a paid API for AI agents from api.delx.ai, paid per call via x402, $0.001/call, status unknown (last checked 2026-09-15).
Deterministically selects a reproducible subset of candidate items from a list using a seed string and a count, returning the selected items and their original indices.
Price / call$0.001
Success—
StatusUnknown
How this service works
Seeded Candidate Subset: Seeded Candidate Subset selects a reproducible candidate subset while preserving original order from bounded caller-supplied values without an external provider. Call Seeded Candidate Subset when an agent needs a reproducible decision that another run can independently replay. Returns the deterministic selection plus seed provenance, population bounds, and the operation-specific outcome for Seeded Candidate Subset as versioned deterministic JSON. Price: $0.001 USDC via…
Output
Returns a JSON object containing the selected subset items as an array, their original indices in the input list, an operation identifier, a status field ('pass'), and an evidence block confirming no data was retained and providing an input hash and external call count — enabling auditability of the deterministic selection.
Example use cases
Reproducible A/B test variant assignment
“I have a list of 50 feature flag candidates and I need to consistently select 10 of them for a test group — use the seed 'experiment-7' so the same 10 are always chosen when I re-run this.”
Deterministic task queue sampling
“From this list of 200 job IDs, pick exactly 20 to process in this batch using the seed 'batch-run-2024-06-01' so the selection is stable if I replay the workflow.”
Stable candidate shortlisting for agent review
“I have a pool of 30 candidate strings and I want to consistently shortlist 5 of them for review — seed it with 'agent-review-round3' so the shortlist doesn't change between runs.”
Technical details
Endpoint
POSThttps://api.delx.ai/api/v1/x402/seeded-candidate-subsetWhen to prefer
Choose this endpoint when you need reproducible, auditable, deterministic subset selection from a list — especially in agent workflows where re-running with the same inputs must yield identical results. Prefer it over random sampling when consistency across runs matters, or when you need a lightweight, no-retention computation with an evidence trail (input hash, zero external calls). It is ideal for stable A/B assignments, batch sampling, shortlisting, and any scenario where seeded determinism is required rather than true randomness.
Side effects
- Count exceeds the length of the candidates array — returns an error or empty result
- Candidates array exceeds the 256-item maximum — request rejected
- Seed string exceeds 8192 character limit — request rejected
- Missing required fields (seed, count, or candidates) — validation error
- Non-integer count value — schema validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| seed | string | Seed supplied to Seeded Candidate Subset; used only for this bounded calculation and processed in memory without retention. |
| count | integer | Count supplied to Seeded Candidate Subset; used only for this bounded calculation and processed in memory without retention. |
| candidates | array | Candidates supplied to Seeded Candidate Subset; used only for this bounded calculation and processed in memory without retention. |
Output
Schema · Response
{
"type": "json",
"example": {
"result": {
"items": [
"b",
"c"
],
"indices": [
1,
2
]
},
"schema": "delx/util-seeded-candidate-subset/v1",
"status": "pass",
"evidence": {
"retained": false,
"input_sha256": "a4bf32161649486846b6869f79571ff2228cc007235b36c78983971fe74db115",
"external_calls": 0
},
"operation": "seeded_decision:seeded_candidate_subset"
}
}Tags
x402
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