Mode Classification
SkillFiles & storageUse before routing a /meta-agent request to choose single-agent-creator, team-builder, or agentlas-packager from the user's wording and available files.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Mode Classification skill
What this skill tells your AI
The instructions your AI receives, as published by agentlas-ai/agentlas-os in skills/mode-classification/SKILL.md and read by ahel’s review.
Pick one Agentlas meta-agent mode before generating or repairing files.
Procedure
- Inspect the user request and any provided path, repo, ZIP, prompt, or agent files.
- Step 0 - existing material wins: if existing material is being converted,
repaired, cleaned, imported, or released, choose
agentlas-packager. - Step 1 - count independent ownership boundaries. Ask how many roles must
independently own all three of:
- their own memory/context;
- their own tools/permissions;
- their own success criteria.
One boundary means
single-agent-creator. Two or more boundaries means ateam-buildercandidate. If the boundary count is unclear, run the clarify question loop before generating; do not infer from the word "team" alone.
- Step 2 - check synthesis need for multi-boundary candidates. If those role
outputs must be routed, reviewed, synthesized, or chained through
produces/consumes dependencies, choose
team-builderand require an orchestrator/HQ plus memory, policy, eval, and QA. If the roles are unrelated, create separate single-agent packages instead of one team. - Step 3 - shape guard.
single-agent-creatormay have many skills/tools but must not emit multiple loose workeragent.mdfiles.team-buildermay be small, but it must not omit the orchestrator/HQ. - Use keyword signals only as hints after the ownership-boundary check:
- MULTI hints: separate memory partitions, tools or permissions that must not be merged, role-to-role review/policy separation, and produces/consumes pipelines.
- SINGLE hints: one coherent job, many tools/skills owned by one worker, no routing or final synthesis requirement.
- Overlay check: if the request depends on knowledge search over user
documents, evidence-based or citation-attached generation, or a document
corpus (HWPX/docx/pdf/제안서/계약서/견적서), additionally apply the
ontology-backed-agentoverlay (modes/ontology-backed-agent.md) withontology_backed: trueon the chosen base mode. - Loop policy: derive
loop_policyfrom task purpose and risk using.agentlas/contract-injection-map.jsonrisk tiers —nonefor simple one-shot tasks,self-correctfor complex or long-running work,verified(separate-context verifier + side-effect gate) when the agent performs external writes or sends. Do not force loops onto simple tasks. - If the choice changes the output and the request is ambiguous, run the clarify question loop instead of guessing.
Return
Return the selected mode, whether the ontology-backed-agent overlay applies,
the derived loop_policy, and one short reason. Then route to the matching
builder.
Reference
See docs/mode-classifier.md.
Signals
- GitHub stars
- 1k
- Forks
- 103
- Last commit
- Sep 2026
Advanced
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mode-classification- Source
- github.com/agentlas-ai/agentlas-os