Telemetry Terminology Similarity
from Claude Code Skills — Quality Tools29
Compute multi-layer similarity scores for telemetry/log field names (syntactic, taxonomic, semantic) to surface naming collisions and standardization candidates
What it does
This skill scores telemetry field names across five layers (normalization, syntactic fuzzy matching, taxonomic WordNet checks, semantic embedding similarity, and optional canonical lookup against OTel/OCSF/CloudEvents). It emits raw scores and canonical anchors so an agent can decide rename proposals deterministically.
When to use it
Use this when auditing logging/telemetry schemas, comparing two JSON/JSONL schemas, detecting naming style inconsistencies (trace_id vs traceId), or preparing structured rename proposals for review. Works well as a deterministic scoring phase feeding an LLM-driven proposal phase.
What's included
- Scripts: analysis script in
references/(term_similarity.py). - References:
references/proposer-prompt.mdfor Phase 2 prompt templates and an abbreviation dictionary. - Instructions: usage examples for direct field lists, JSONL extraction, schema comparisons, and parameters controlling output size and canonical lookups.
Compatible agents
Agents that can run Python scripts and manage local model downloads (e.g., Claude Code, local Python-capable LLM integrations).
Tags
Not yet audited
This skill has not been reviewed by our automated audit pipeline yet.
Information
- Repository
