talk-walter-runtime-intelligence-agents
Provides detailed answers, analysis, verbatim-grounded summaries, framework applications, and workflow audits based on May Walter's talk "From Blind Spots to Merged PRs: Runtime Intelligence for Continuous Agentic Performance Optimization". Use when the user asks about May Walter's talk — including questions about Hud's runtime code sensor, the prod-to-code mapping concept, automating the performance-investigation phase, scoring fixes by impact and risk, why automated pull requests didn't work, the layered architecture (query language → skills → automations), the four takeaways (define what matters, automate investigation, context over cleverness, agentic engineering ≠ coding with an agent), or applying Walter's approach to integrating AI agents into the SDLC.
73
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High
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Security
1 high severity finding. You should review these findings carefully before considering using this skill.
W007: Insecure credential handling detected in skill instructions.
What this means
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
Why it was flagged
The skill explicitly requires verbatim quoting from transcript.md and verification of quoted passages, so if transcript.md contains any credentials or secrets the model would be forced to reproduce them verbatim, creating an exfiltration risk.
- Repository
- AINativeDev/aidevcon-2026-ldn
- Commit
1887349
- Audited
- Security analysis
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