netcafe-memory

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

Annotations already provide destructiveHint=true and readOnlyHint=false, so the bar is lower. The description adds 'you own' as an authorization constraint and reinforces permanence with 'permanently delete,' but does not elaborate on idempotency (despite idempotentHint) or error behavior. This is moderate additional context.

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, front-loaded sentence with an inline example, containing zero wasted words. It is concise and structured for quick scanning.

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 single-parameter destructive tool, the description covers what, when, ownership, and provides an example. With an output schema present, no gap is evident; it is contextually complete for its complexity.

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 a full description of 'id'. The description restates 'id from recall' and gives a call example, but does not add new semantic meaning beyond the schema, so baseline 3 is 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 states 'Permanently delete one memory you own' with a clear verb (delete) and resource (memory). It distinguishes from siblings like recall and remember by specifying the destructive action and the source of the id.

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 provides a clear condition: 'Use when a memory is wrong or sensitive.' It also implies the prerequisite of obtaining the id from recall, but does not explicitly name alternatives or exclusions beyond that, so it's clear context without exhaustive guidance.

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 cover read-only and non-destructive behavior. The description adds a prerequisite (needs a workspace/key for durable memory) and explains the type of context it retrieves (decisions, fixes, preferences). The example GET request also illustrates the call style. No contradiction with annotations.

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 concise and front-loaded with the core purpose. It includes an example and a key prerequisite in two sentences, with no redundant information. Every sentence serves a purpose.

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?

The description covers the tool's purpose, when to use it, a usage example, and an authentication prerequisite. With full parameter documentation, an output schema, and annotations, the description is sufficiently complete. It also positions the tool well relative to its siblings.

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 schema provides detailed descriptions for all three parameters (limit, query, project), so the description adds little beyond restating that filtering is optional and showing an example that uses 'query.' With 100% schema coverage, the baseline is 3, and the description does not significantly enrich parameter meaning.

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 'Retrieve previously stored memories,' a specific verb and resource. It also specifies optional filtering by search query and project, and gives a concrete use case (restoring context at the start of work). This clearly distinguishes it from sibling tools 'remember' and 'forget.'

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?

The description explicitly says to call it 'at the start of work on a known project' to restore context, which is clear when-to-use guidance. It does not explicitly name alternatives, but the phrasing and sibling names imply that 'remember' is for storing and 'forget' for deleting. The example and note about needing a workspace/key add practical context.

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 confirm this is a non-read-only, non-idempotent, non-destructive write, and the description adds context annotations can't carry: a bounded per-caller/workspace memory pool and no API key requirement. It also warns against secrets/raw logs, which is genuine behavioral guidance. It doesn't cover what happens on pool exhaustion or whether repeats duplicate, keeping it at 4.

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 purpose and constraints are front-loaded, followed by a concrete call example. Three sentences and an example is slightly generous but each element (guidance, exclusion, example) earns its place.

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 an output schema present, the description need not explain returns, and it covers auth, capacity, exclusions, and an invocation example. It omits update/duplicate/idempotency behavior for a non-idempotent write, which is the remaining gap.

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 value by mapping its four example categories onto the enum values (decision/preference/bugfix/discovery) and by tying the project param to later recall scoping, giving semantics beyond the raw schema text.

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 names a specific verb ("Persist") and resource ("durable memory") and enumerates what qualifies as a memory (architecture decision, preference, bug fix, discovery). It gestures at the sibling recall tool ("scope recall later") but never explicitly states how this differs from it, so it stops short of a 5.

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 positive context (durable items worth persisting) and a negative rule ("Do not store secrets or raw logs"), which is real when-not guidance. It stops short of explicitly naming the recall counterpart as the retrieval alternative, so it's a strong 4 rather than a 5.

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, idempotentHint, and destructiveHint. The description adds valuable behavioral traits not visible in annotations: deterministic, calls no model, costs nothing, and never runs out of quota. No contradiction with annotations.

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?

Four dense sentences, front-loaded with the core purpose in the first sentence and supported by recipes, cost/quota guarantees, and when-to-use guidance. Every sentence earns its place; no filler or repetition.

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?

Given the simple context (single required string parameter, rich annotations, and an output schema), the description is complete. It covers the tool's behavior, return value highlights, performance/cost characteristics, and usage context without leaving important gaps.

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 input schema already describes the 'task' parameter with examples, and schema coverage is 100%. The description adds the nuance 'plain language (any language)' and emphasizes that example calls are generated, providing modest additional meaning 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?

The description clearly states the tool's purpose with a specific verb+resource: describe a task and get back exactly which tools on the server do it, with ready-to-run example calls. It explicitly distinguishes itself from sibling tools by positioning itself as the meta-guide that prevents 'reading the whole catalogue and guessing.'

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?

Provides explicit when-to-use guidance: 'Call this FIRST when you are not sure what this server offers.' It also clarifies the intended use case (plain-language task discovery) and contrasts with the alternative of scanning the catalogue manually, which is sufficient for a meta-tool.

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