memory: disambiguate tool descriptions to reduce agent tool-misuse (measured +34.5 pts)

[sujugithub]

What

Rewrites 6 tool description strings in src/memory/index.ts. No code or behavior changes — only the text agents read when choosing tools.

Why

Agents pick tools from names + descriptions + schemas alone. I measured how a mid-tier agent actually uses this server (11 realistic scenarios × 5 runs each, live server, every tool call recorded) and found two systematic failures:

1. Wrong-tool confusion: create_entities vs add_observations, and search_nodes vs open_nodes — the current descriptions don't say when to prefer the sibling.
2. Ritual extra calls: agents call open_nodes/search_nodes before writes and deletes that don't need a lookup first.

Measured effect of this diff (nothing else changed)

metric	before	after
tool hit rate (right tool chosen)	80.0%	100.0%
argument correctness	100%	100%
strict success (right tool + args + no extra calls)	61.8%	96.4%

Method: agent = gpt-oss-120b (a deliberately mid-tier model — weaker agents are hurt most by ambiguous descriptions), N=5 runs per scenario, descriptions applied via in-memory override so before/after used the identical server build. Happy to share the full per-run data and the scenario suite, or re-run against any revision of this text — treat the exact wording as a starting point.

Notes

• Each rewritten description leads with when to use the tool and names the sibling to prefer otherwise ("Use add_observations instead to add facts to existing entities").
• The measurement harness (scenarios + runner) is being open-sourced; I'll link it here once public.

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