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SKILL.md
Edge Verifier
ASecurityVerifies relationships between a source text (e.g. Episode, Task) and existing Knowledge Graph lessons. Runs KNN/Hybrid search to find candidates, then uses LLM (scillm) to verify "verifies", "contradicts", or "related" stances with strict rationales.
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- Added September 11, 2026
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[](https://www.skillsdirectory.com/skills/grahama1970-edge-verifier)---
name: edge-verifier
description: >
Verifies relationships between a source text (e.g. Episode, Task) and existing Knowledge Graph lessons.
Runs KNN/Hybrid search to find candidates, then uses LLM (scillm) to verify "verifies", "contradicts",
or "related" stances with strict rationales.
internal: true
allowed-tools: Bash
triggers:
- verify edges
- link content
- generate relationships
- schedule verification
metadata:
short-description: KNN + LLM verification for KG edges
provides:
- edge-verification
composes:
- scillm
- task-monitor
- agentic-evals
taxonomy:
- validation
- knowledge
- precision
disciplines:
- memory-knowledge
- evaluation-quality
---
# Edge Verifier
This skill links new content to the existing Knowledge Graph by:
1. **Recall**: Running a KNN/Hybrid search (`graph_memory.search`) to find potential related lessons.
2. **Verify**: Using `scillm` (LLM) to audit the relationship, classifying it as `verifies`, `contradicts`, or `neutral`.
3. **Link**: Creating verified `lesson_edges` in ArangoDB.
## Usage
### Manual Execution
```bash
# Verify edges for a specific source text
.pi/skills/edge-verifier/run.sh --source_id <ID> --text "Content to verify..."
# With explicit options
.pi/skills/edge-verifier/run.sh --source_id <ID> --text "..." --type "episode_turn"
```
## Scheduling (Scheduler Integration)
This skill is designed to be scheduled via the `/scheduler` skill for continuous verification of new memory artifacts.
### Register with Scheduler
```bash
.pi/skills/scheduler/run.sh register \
--name "edge-verify-nightly" \
--cron "0 2 * * *" \
--command ".pi/skills/edge-verifier/run.sh --batch" \
--description "Nightly edge verification"
```
Jobs and logs are stored under `~/.pi/scheduler/`. See `.pi/skills/scheduler/SKILL.md` for full options.
## Common Mistakes
### WRONG: Running verification without ArangoDB credentials
```bash
./run.sh --source_id <ID> --text "content" # fails silently without .env
```
### RIGHT: Ensure .env has ArangoDB and Chutes credentials
```bash
# Verify .env exists with ARANGO_URL, ARANGO_DB, CHUTES_API_KEY
cat .env | grep -E "ARANGO|CHUTES"
./run.sh --source_id <ID> --text "content"
```
### WRONG: Verifying edges without specifying content type
```bash
./run.sh --source_id <ID> --text "content" # default type may not match
```
### RIGHT: Specify the source type for accurate classification
```bash
./run.sh --source_id <ID> --text "content" --type "episode_turn"
```
### WRONG: Running batch verification during peak hours
```bash
./run.sh --batch # competes with interactive queries for LLM slots
```
### RIGHT: Schedule batch verification for off-peak (nightly)
```bash
.pi/skills/scheduler/run.sh register --name "edge-verify-nightly" \
--cron "0 2 * * *" --command ".pi/skills/edge-verifier/run.sh --batch"
```
## Prerequisites
- `.env` must expose ArangoDB credentials.
- `CHUTES_API_KEY` for LLM calls.
Files in this skill
- SKILL.md
- fixtures/agentic_eval.json
- hint_sweep.py
- policy.yaml
- pyproject.toml
- run.sh
- sanity.sh
- verify_edges.py
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