Reports how much stored browser-agent experience exists, grouped by outcome, so you can gauge coverage before relying on per-site route memory.
How much experience is stored, by outcome.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden. Read-only aggregation is only implied, and nothing is said about what 'outcome' values exist, what the counts represent, whether the result is a fixed or dynamic set of buckets, or cost/scope of the query.
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?
The single fragment has no filler, but at roughly eight words it is under-specified for a tool with no annotations and no output schema. Conciseness is achieved at the expense of information rather than through efficient framing of necessary detail.
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?
With no annotations, no output schema, and no parameters, the description is the only source of behavioral information, yet it omits what the return shape is (counts per outcome?), what the outcome categories are, and how it relates to the sibling memory tools. It is insufficient for an agent to call it confidently.
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?
The tool takes zero parameters (100% schema coverage), so per the baseline there is nothing for the description to clarify about input semantics.
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 fragment "How much experience is stored, by outcome" indicates an aggregate/statistics read over stored memory entries grouped by outcome, which is a real distinction from retrieval siblings like memory_recall. But it never states a verb or the noun being counted (memory entries? records? lessons?), so the purpose is inferred rather than stated.
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?
There is no guidance on when to call this versus memory_recall, memory_record, or memory_rate. An agent must guess that this is a summary/metrics view and that memory_recall returns the actual content.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.