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edge-verifier

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.

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grahama1970/agent-stack-public
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2026년 9월 24일 15:51
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SKILL.md
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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.
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