Start broad, then specialize. Default to universal routing, and switch into OpenClaw-aware mode when the environment supports it.
references/scoring-rubric.md before scoring candidates.references/ambiguity-and-fallbacks.md when confidence is weak or constraints are missing.references/environment-detection.md before deciding whether to stay in universal mode or enter OpenClaw mode.references/chain-patterns.md when the request obviously spans several phases.references/research-notes-2026-03.md when you need the design rationale.Normalize the request into a task card:
Detect the environment using references/environment-detection.md:
Scan visible skill roots conservatively:
SKILL.md frontmatter firstagents/openai.yaml only for shortlisted candidatesApply hard filters before ranking:
Score viable candidates with references/scoring-rubric.md.
If one skill can finish the task, recommend that skill.
If the task spans phases, recommend a short chain using references/chain-patterns.md.
If confidence is low, ask compact clarification questions instead of forcing a route.
Output:
description over name similarity.md
[Routing Decision]
Mode: universal | openclaw-aware
Request: ...
Recommended skill: ...
Confidence: high | medium | low
Why it fits: ...
Missing checks or prerequisites: ...
Fallbacks: ...
Suggested chain: ...
Clarifying question(s): ...
SKILL.md before shortlisting.Finish with one recommended skill or skill chain, an explicit mode, a confidence level, key reasons, fallbacks, and any blocking unknowns.
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