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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden and does so: auto-creation of missing entities, pre-insertion contradiction detection, authority-tier assignment, dependency recording, and the policy of persisting the fact while emitting a warning on contradiction. It also documents the side effect of audit-log recording and the return shape, which is exactly the kind of mutation/return transparency a no-annotation tool needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action, then cleanly sectioned into trigger and behavior blocks. Every line earns its place — the routing lines and the contradiction/return note each carry information an agent needs.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite six parameters and no output schema, the description supplies the return JSON keys (ok, entity, domain, tier, observationIds, contradictionWarnings) and the contradiction warning path. Combined with the usage and behavioral sections, an agent has everything needed to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents entity, facts, tier, type, domain, and derived_from. The description echoes concepts (authority tiers, logical dependencies) but adds no syntax, defaults, or value guidance beyond what the schema provides, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (store) and resource (factual observations under an entity in a knowledge graph) and explicitly distinguishes itself from the forget/recall/context siblings. An agent can identify this as the write path for memory without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The WHEN TO USE block gives explicit positive triggers (new knowledge, preferences, decisions, verified facts) and two explicit exclusions routing to 'forget' (invalidation) and 'recall'/'context' (querying). Nothing about when to pick this over a sibling is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.