why_recalled

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

With no annotations, the description carries full burden and delivers: it discloses determinism/no LLM rationalization, the per-channel output dimensions, active-project scoping, and the cross-project not-found behavior. These are behavioral facts beyond the schema and materially shape how an agent should interpret results.

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?

Three sentences, front-loaded with the explainability category and the core question, followed by return contents, determinism, and scope limitation. No filler; each sentence contributes a distinct fact.

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 2-parameter read-style explainer with no output schema or annotations, the description covers purpose, output dimensions, determinism, and scope limits. It is slightly short on response structure details beyond the named channels, but this is a minor gap given the tool's simplicity.

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?

With schema description coverage at 0%, the description compensates partially: `query` is tied to the memory lookup and `id` is described as selecting a specific memory. However, it never defines the id's source/format, and the schema still requires `query` even when `id` is supplied, which the description does not clarify.

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 opens with the category 'EXPLAINABILITY' and immediately poses the question it answers: 'why did (or didn't) a memory surface for `query`?'. It names the returned artifact (per-channel breakdown of relevance/value/provenance) and the deterministic no-LLM nature, which clearly separates it from recall-type and decision_explanation siblings.

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?

It gives clear usage context: explain top hits or a specific id, and scopes the tool to what recall can surface ('Honours the active project scope, like recall'). It also states an exclusion behavior ('an `id` in another project is answered as not found'), but it does not explicitly name alternative tools or say when not to use this tool, so it stops short of a 5.

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