Part of MCPAQL/website#32 (Epic: MCPAQL 2026 product launch). Phase 1a — additive.
What
Add a safety-gating metric to the mcpaql-parity runner that measures how the MCPAQL-adapted path handles operations that can do damage, versus raw MCP.
This reuses the induced-error harness pattern already built in #21 (closed). Instead of injecting a bad-argument response, the harness injects tasks that should trigger a destructive or irreversible operation, and we measure what each configuration does with it.
Metric: induced-danger gating rate — across a set of tasks that would trigger destructive/irreversible operations:
- How often does the MCPAQL path correctly surface the danger up front / require a confirmation step / refuse?
- How often does raw MCP simply execute it unguarded?
Why
This makes the Programmatic Safety & AI Governance pillar measurable instead of asserted. Right now Phase 1a proves token economy (96%) and is set up to prove LLM correctness + recovery (tools#22). The safety/governance pillar has no measured proof point — this is the cheapest way to produce one, because the harness already exists.
The result feeds the case study (MCPAQL/website#34, new "Safety & Governance" section) and the Phase 1b homepage governance band.
How
Scope note
Additive — does not change the scope of #22. That issue's four metrics (tool-list tokens, first-call success, turns, recovery) stay as-is. This adds a fifth, optional metric category that #22 can include if the run is cheap, or that can run separately.
Phase
1a (additive).
Part of MCPAQL/website#32 (Epic: MCPAQL 2026 product launch). Phase 1a — additive.
What
Add a safety-gating metric to the
mcpaql-parityrunner that measures how the MCPAQL-adapted path handles operations that can do damage, versus raw MCP.This reuses the induced-error harness pattern already built in #21 (closed). Instead of injecting a bad-argument response, the harness injects tasks that should trigger a destructive or irreversible operation, and we measure what each configuration does with it.
Metric: induced-danger gating rate — across a set of tasks that would trigger destructive/irreversible operations:
Why
This makes the Programmatic Safety & AI Governance pillar measurable instead of asserted. Right now Phase 1a proves token economy (96%) and is set up to prove LLM correctness + recovery (tools#22). The safety/governance pillar has no measured proof point — this is the cheapest way to produce one, because the harness already exists.
The result feeds the case study (MCPAQL/website#34, new "Safety & Governance" section) and the Phase 1b homepage governance band.
How
Scope note
Additive — does not change the scope of #22. That issue's four metrics (tool-list tokens, first-call success, turns, recovery) stay as-is. This adds a fifth, optional metric category that #22 can include if the run is cheap, or that can run separately.
Phase
1a (additive).