get_reputation_scores
Compute PageRank trust scores from your directed trust graph to rank agents by trustworthiness and prioritize counterparties.
Instructions
Compute PageRank/EigenTrust trust scores over a directed trust graph you supply (LUMEN).
Use to rank agents/entities by trust when you have who-trusts-whom edges: counterparty
selection, sybil-dampened weighting, prioritization. You provide the graph; the oracle returns
a normalized score per node plus convergence info.
Returns:
The standard envelope; `result` contains:
- `scores`: array of `nodes` floats that sum to 1 (±1e-6) — node i's trust share.
- `iterations`, `converged`: power-iteration convergence info.
Cost ~$0.005 USDC (scales with graph size).
Example:
get_reputation_scores(nodes=3, edges=[[0,1,1.0],[1,2,0.5],[2,0,0.5]], damping=0.85)
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| nodes | Yes | Number of nodes in the directed trust graph, 1..100000. Node indices in `edges` must be in [0, nodes). | |
| edges | Yes | Directed, weighted trust edges as `[from_index, to_index, weight]`. An edge i→j with weight w means node i confers w trust on node j. Weights need not be normalized. | |
| damping | No | PageRank damping factor in [0,1] (default 0.85). Lower = more weight on the uniform prior, dampening graph manipulation. |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |