Find AI-agent retry loops, repeated failed tool calls, error streaks, terminal failures, and recovery patterns in execution traces. Generates the smallest replay experiment to test a retry/validation/fallback change without claiming unverified savings.
Audit AI-agent traces for token-heavy context, retries, model switching, repeated tool transformations, and human-interruption pressure. Returns the smallest matched-replay experiments needed to verify whether cognition can be removed safely — without inventing savings claims.
Compare matched baseline and challenger AI-agent runs before accepting an optimization. Terminal success and protected quality come first; lower cost, latency, token use, errors, or human interruptions cannot compensate for a material regression.
Prevent wrong-business Google Maps matches from entering your CRM or database. Verifies the expected name and address and returns MATCHED only with strong evidence; otherwise it refuses the result. Unofficial and not affiliated with Google.
Reduce bloated MCP or AI-agent tool catalogs to a smaller evidence-based allowlist for stated tasks. Detect routing confusion, preserve task coverage, and identify what can stay dormant — without using an LLM or pretending lexical similarity proves behavioral equivalence.
Detect when Facebook, X, LinkedIn, Slack, Discord, and normal crawlers receive inconsistent social-preview state. Returns deterministic PASS, RISK, FAIL, or INCONCLUSIVE verdicts for publishing agents, CI, and CMS workflows.