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fix(prompt_builder): inject tool-use enforcement for GLM models

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GLM-family models (z-ai/glm-4.5-air, z-ai/glm-4.5-flash, etc.) exhibit
the same "describe-instead-of-call" failure mode that gpt/codex/gemini/
gemma/grok already trigger enforcement for. Without the injection,
free-tier GLM workers spawned by the kanban dispatcher routinely exit
cleanly (rc=0) without invoking kanban_complete or kanban_block,
producing the "protocol violation" error and triggering the dispatcher's
gave_up path.

Observed in real workloads: seven consecutive kanban tasks across three
GLM-tier profiles (shipbackend, frontend-engineer, backend-engineer) all
failed with the identical message:

    worker exited cleanly (rc=0) without calling kanban_complete or
    kanban_block — protocol violation

Re-running the same tasks on Claude Haiku immediately resolved them.
Adding "glm" to TOOL_USE_ENFORCEMENT_MODELS closes the gap so future
GLM-routed work receives the explicit "every response must contain a
tool call or final result" steering that already protects the other
enforcement-gated model families.

One-line change; no behavior change for non-GLM models.
This commit is contained in:
ALIYILD 2026-05-12 18:46:22 -07:00 • committed by Teknium
parent e474130c48
commit afa5b81918
1 changed files with 1 additions and 1 deletions
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agent/prompt_builder.py
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@ -268,7 +268,7 @@ TOOL_USE_ENFORCEMENT_GUIDANCE = (
# Model name substrings that trigger tool-use enforcement guidance.
# Add new patterns here when a model family needs explicit steering.
TOOL_USE_ENFORCEMENT_MODELS = ("gpt", "codex", "gemini", "gemma", "grok")
TOOL_USE_ENFORCEMENT_MODELS = ("gpt", "codex", "gemini", "gemma", "grok", "glm")
# OpenAI GPT/Codex-specific execution guidance. Addresses known failure modes
# where GPT models abandon work on partial results, skip prerequisite lookups,