Routing

Route work to the right path up front. 2 optimizations.

i.

Route metric questions through a deterministic semantic layer; fall back to text-to-SQL

Where a semantic layer exists, have the agent answer metric questions by choosing metrics and dimensions that the layer compiles to SQL, and write SQL only when the layer cannot answer.

Better quality

Tier 3 · tuning · changes control flow, knowledge access · data analysis agents · 4 sources, 3 measured
ii.

Prompt chaining with gate checks

Split a task that decomposes cleanly into fixed steps into a chain of model calls, one goal per call, with a gate between steps: a schema check, an assertion, or a run against the real system, and an LLM check only for subjective criteria.

Better qualityMore secureBetter governanceBetter for brandHigher costSlower

Tier 4 · restructuring · changes control flow · any agent · 11 sources, 8 measured

Try it for yourself

Paste this into Claude Code, or any coding agent, in your agent's repo to check it for these optimizations.

Read these agent optimizations (Orchestration: Routing), each with the signs that it applies:
- 7.a.i Route metric questions through a deterministic semantic layer; fall back to text-to-SQL: https://mahalsystems.ai/aot/optimizations/semantic-layer-routing.md
- 7.a.ii Prompt chaining with gate checks: https://mahalsystems.ai/aot/optimizations/prompt-chaining-with-gates.md
- 8.a.i Choose the retriever by corpus size and question type: https://mahalsystems.ai/aot/optimizations/choose-retriever.md
Then check whether any of them applies to the agent in this repository. Look for each one's signs under "When it applies" in its code, prompts and tools, and in any traces or eval results you can find. Tell me which apply, strongest first, with what you found for each. Don't change anything yet.

Routing

Route metric questions through a deterministic semantic layer; fall back to text-to-SQL

Prompt chaining with gate checks

See also

Choose the retriever by corpus size and question type

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