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

Goes well beyond the annotations: it discloses immediate retrievability ('in this session and every future one, from any agent the user has connected'), the provenance-linking expectation, the one-fact-per-memory constraint, and the conditional `choice.choice_required` follow-up flow with required answer options. This is rich behavioral context an annotation-only view would miss.

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 usage, then the edge-case flow in a logical order. Every sentence carries information, though the final enrichment-handling sentence is dense and slightly extends the length.

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?

For a mutation tool with no output schema but full annotation coverage and 100% schema descriptions, the description compensates by documenting cross-session/cross-agent effects, provenance, and the choice_required return behavior. Nothing critical is left implicit.

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 coverage is 100%, so the baseline is 3, but the description adds real meaning: it explains the purpose of source_universal_ids (link the fact to evidence from cortex_ask) and reinforces the 'one self-contained fact' constraint on text. It stops short of clarifying kind/confidence semantics beyond the schema.

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 and resource ('Persist a fact, decision or conclusion into the memory') with scope (attributed to you) and distinguishes itself from cortex_ask/cortex_recall by describing persistence semantics. An agent can tell exactly what this does 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?

Gives explicit when-to-use criteria ('whenever the conversation produces a durable conclusion — a decision, a preference, an outcome, a commitment'), names the alternative path for provenance via a previous cortex_ask, and routes the conditional enrichment case to cortex_choose_enrichment.

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