memory_lessons

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

With no annotations provided, the description carries the full behavioral burden. It does disclose one genuinely important trait: results are limited to outcomes known by as_of, i.e. point-in-time filtering with no lookahead. It says nothing about read-only semantics, result volume, ranking of 'other tickers' lessons, or pagination.

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?

A single sentence, front-loaded with the core resource and then itemizing its contents via a colon. Every clause carries information; the only weakness is the slightly awkward 'to give the Portfolio Manager' embedding.

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?

An output schema exists, so return-value explanation is not required. However, for a memory/aggregation tool with zero annotation coverage and zero schema documentation, the description leaves open how 'lessons from other tickers' are selected and how many results come back, which an agent would want to know before calling.

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 0%, so the description must compensate for both parameters. It does explain the intent of each ('as_of' as an outcome-known cutoff, 'ticker' as the subject of recent decisions), but gives no format for as_of (date string? ISO timestamp?) and no hint at how the ticker scopes the cross-ticker lessons.

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?

The description states a specific resource (lessons distilled from past decisions) and enumerates its two components: recent decisions on this ticker and lessons from other tickers. That composition distinguishes it from siblings like past_decisions and unsettled_decisions, though it uses a noun phrase rather than an explicit retrieval verb.

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?

Usage is only implied by the phrase 'to give the Portfolio Manager', which suggests pre-decision context, but there is no explicit when-to-use guidance and no mention of how it differs from past_decisions or unsettled_decisions. An agent must infer the selection rule from the sibling names alone.

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