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

Annotations already declare readOnlyHint=false and destructiveHint=false, and the description adds genuinely new behavior: content is written as Markdown files and secrets (tokens, keys, passwords) are redacted before writing. That redaction note is important context an agent cannot get from structured fields. It stops short of covering duplicate behavior, which matters given idempotentHint=false.

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?

Two tight sentences, the core action front-loaded and the safety-relevant redaction detail second. Nothing is redundant.

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-shape explanation is not required, and the annotations plus a fully described schema carry most of the load for an 11-parameter mutation. The remaining gap is where memories land (the project parameter's storage semantics) and how duplicates or re-adds are handled given non-idempotency.

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% with per-field descriptions for all 11 parameters, including the 'type' values (lesson/do/dont/history) and link syntax. The description adds nothing about parameters, which is acceptable at full coverage but leaves it at the baseline.

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 verb and resource ('Save a memory as Markdown') plus the observable outcome ('return the file path'). It is clearly a write counterpart to the sibling search/related tools, though it never names them to draw the boundary explicitly.

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 add a memory versus when to search first with memory_search, nor on what qualifies as worth persisting. An agent must infer the whole usage context from the tool name alone.

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

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

Annotations already establish that this is a safe read-only, non-destructive, closed-world operation. Beyond that, the description adds useful behavioral detail by disclosing the relation ranking order and the relationship categories used for matching.

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 description is a single compact sentence that front-loads the core purpose and then lists the relation ordering. Every element earns its place, with no repetition or filler.

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 simple two-parameter read-only traversal tool with full schema documentation and no output schema, the description provides enough context to invoke it correctly. A minor gap is that it does not describe the returned memory fields, though the core behavior is clear.

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 fully documents both the ref and limit parameters. The description adds no parameter-specific syntax or constraints beyond what the schema provides, making the baseline score appropriate.

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 clearly states that this tool returns memories related to a given memory, and it specifies the relation ordering and categories. It does not explicitly distinguish itself from memory_search, but the resource and scope are clear enough for selection.

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 implied: call this when you need memories related to a known memory reference, ordered by relation strength. However, it gives no explicit when-to-use guidance versus memory_search or when-not-to-use conditions.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds genuine behavioral context the annotations don't: a ticket key expands to return everything for that task and its epic. No return format or pagination/ranking behavior is described, but that is a minor gap for a read tool.

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 short sentences, front-loaded with the verb and resource, then the special ticket-key rule, then the filter list. No filler and nothing buried.

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 output schema, the description gives enough on filters and special key handling to call the tool correctly, and annotations cover safety. It stops short of explaining result ordering, tag-search semantics, or how multiple filters combine, which an agent might want.

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. The description adds real semantics beyond the schema: the ticket-key expansion rule and the fact that searching spans tags, which is not a parameter at all – both help an agent reason about results rather than just field names.

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 (Search) and resource (memories) plus the fields searched (title, body, project, task, epic, tags). The ticket-key behavior sentence makes it clearly different from memory_add and memory_related, so an agent can distinguish it 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?

Implies usage ('Search memories by...', 'Filters: project, type, task and epic') but never states when to prefer this over memory_related or when memory_add applies. It also omits that empty text returns most recent results – that detail lives only in the schema.

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