---
name: h-mmer/learn
source: https://app.decimal.ai/s/h-mmer-learn@1/SKILL.md
source_sha256: 6fe458999516
---

Record platform response: $ARGUMENTS

1. Parse arguments and run: `uv run python3 ../../tools/response_tracker.py log $ARGUMENTS`
2. Also update brain: `uv run python3 ../../tools/brain.py log "Report response: $ARGUMENTS"`
3. Sync to global brain: `uv run python3 ../../tools/global_brain.py sync-from-local`
4. Show updated insights: `uv run python3 ../../tools/response_tracker.py insights`

## Top-Tier Learning Loop

Convert every platform response into a future hunting rule.

- If accepted: record the decisive proof artifact, impact framing, asset type, vuln variant, bounty tier, and why triage agreed.
- If duplicate: record the duplicated primitive and which uniqueness signal was missing.
- If N/A: record the exact sentence or policy clause that killed it.
- If informative: record the missing chain or business impact required to make it payable.
- If severity changed: record the evidence that moved it up or down.

End with one concrete update: a brain pattern, a never-submit rule, a report wording change, or a target ranking adjustment.