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## Why Evaluating buzz agent memory retrieval by seeding a memory then asking the buzz agent a question it needs that memory. **Bug Found**: System prompt had no inclusion of retrieving cold memories and suggested looking in a mem/*.md directory that does not exist. Updated `system-prompt.md` to include memory CLI tools and usage. Eval Before System Prompt Change: 0/3 Eval After System Prompt Change: 3/3 ## What - Add a `memory-retrieval` benchmark that seeds agent memory with `buzz mem set` before asking a direct question. - Grade the observable threaded answer without inspecting tool calls or exposing the answer in channel history. - Teach agents to use `buzz mem set`, `buzz mem ls`, and `buzz mem get` for cold memory. - Add a wire-debug endpoint configuration for diagnosing ACP tool calls in local runs. - Add fixture, seeding, verifier, and prompt coverage. ## Risk Assessment Low. The runtime changes are limited to the benchmark harness. The production-facing change clarifies existing memory commands in the base prompt; it does not change memory storage, relay behavior, or authorization. ## References - Before the system-prompt changes, 0/3 attempts passed because agents never invoked the `buzz mem` CLI and instead searched a non existent filesystem - After the changes, 3/3 attempts passed. ACP wire logs confirmed that every agent ran `buzz mem ls` followed by `buzz mem get` and returned `net_gpv`. --------- Signed-off-by: Philip Azar <pazar@squareup.com>
26 lines
509 B
TOML
26 lines
509 B
TOML
schema_version = "1.3"
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[task]
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name = "buzz-native/memory-retrieval"
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description = "Answer a question using a harness-seeded cold-memory rule."
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authors = [{ name = "Buzz" }]
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keywords = ["buzz-native", "agents", "memory", "retrieval"]
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[metadata]
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evaluation_layer = "regression"
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difficulty = "hard"
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category = "collaboration"
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tags = ["agents", "memory", "retrieval"]
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[agent]
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timeout_sec = 300.0
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[verifier]
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timeout_sec = 30.0
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[environment]
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network_mode = "public"
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cpus = 1
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memory_mb = 1024
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storage_mb = 1024
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