YourSUUID

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and locality are covered without the description's help. The description adds only the "URL-safe" output trait; it says nothing about randomness source, collision properties, or what happens when count exceeds 1, which are the traits that actually matter here.

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 front-loaded sentence with no filler; the verb and the two knobs come first. It is perhaps over-compressed for the information the agent actually needs, but nothing is wasted.

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, side-effect-free generator with annotations covering the safety profile, the description is close to sufficient. The gap is the undocumented count parameter and the absence of an output schema, leaving unclear whether a count>1 call returns an array or a single string.

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 carry the parameter burden, and it only partially does: it mentions size and alphabet but omits count entirely. It also omits the size bounds (2-255) and default 21, and gives no guidance on what a valid custom alphabet looks like.

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 and resource ("Generate URL-safe NanoIDs") and names the two configurable dimensions, so the tool's identity is unmistakable. It implicitly separates itself from the UUID/ULID siblings by naming the NanoID format, though it never explicitly contrasts them.

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: "URL-safe" hints at the scenario where this format is preferable to the UUID/ULID siblings, but there is no explicit when-to-use, when-not-to-use, or named alternative. An agent must infer the routing decision from the format 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 declare readOnlyHint and openWorldHint=false, so the safety profile is covered. The description adds genuinely behavioral detail beyond them: output length (26 chars), monotonicity, and time-based sortability, which affects how an agent can use the resulting IDs. It does not mention uniqueness/collision guarantees, so not a 5.

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 front-loaded sentence with no filler; every clause (monotonic, length, sortability) carries information.

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 one-parameter generator with annotations covering safety, the description covers what is produced and its format. The unexplained count parameter and the unspecified return shape (single string vs list) leave a real gap for correct invocation.

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% and the single count parameter (default 1, max 1000) is never mentioned in the description, so an agent gets no explanation that it can request multiple IDs at once or what the return shape is in that case.

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?

Specific verb (generate) plus a specific resource (ULIDs) with defining characteristics — 26 characters, lexicographically sortable by time — that distinguish it from the UUID and NanoID siblings. It doesn't explicitly contrast with those siblings, but the format detail makes the identity unmistakable.

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: 'sortable by time' and 'monotonic' hint that this tool suits ordered identifiers versus random nanos/uuid v4, but there is no explicit when-to-use statement or reference to the sibling tools.

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 openWorldHint=false, so the safety profile is covered by structured data. The description adds that generation can be batched ("one or more"), but does not mention the 1000-item cap, the return shape, or anything about determinism — all of which matter for a generator.

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 short sentences, zero filler, with the purpose front-loaded and the practical version advice immediately after. Every clause carries information.

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 generator with no output schema, this is nearly sufficient: purpose, variant semantics and selection advice are all present. The remaining gap is the output shape when count > 1 (single string vs array) and the batch limit.

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 carry the load. It explains the meaning of both enum values well (v4 = fully random, v7 = time-ordered) and implies the count parameter via "one or more", but never states the 1–1000 range or the default of 1.

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?

Specific verb plus resource ("Generate one or more UUIDs") with the two supported variants called out. It does not distinguish itself from siblings like generate_ulid, generate_nanoid or generate_uuid_v5, which would require an extra clause.

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?

Gives explicit selection guidance between the two version values (v7 for database keys, v4 for randomness), which is genuinely useful. It offers no guidance on when to pick this tool over generate_ulid, generate_nanoid or generate_uuid_v5, so tool-level choice is left to inference.

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?

The annotations already cover safety (readOnly, idempotent, closed-world), so the description's job is to add behavior, which it does by disclosing the determinism guarantee and the SHA-1 algorithm. It does not cover error behavior for invalid namespaces, which is a minor gap.

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 front-loaded sentence carries the determinism guarantee, the algorithm, and the namespace vocabulary with no wasted words.

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 two-parameter pure function with annotations that make the safety profile clear and no output schema, this covers nearly everything an agent needs. The one omission is that the default namespace of dns is visible only in the schema, not the description.

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 0% schema description coverage, the description must carry the parameter meaning, and it does enumerate the accepted namespace values (dns, url, oid, x500 or a raw UUID) that the schema leaves undocumented. The name parameter is only loosely characterized as "a name," so the compensation is good but not complete.

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 gives a specific verb+resource: it generates a deterministic name-based UUID v5 using SHA-1. The adjective "name-based" and "deterministic" implicitly separate it from the sibling generate_uuid (random) and inspect_uuid, but it never names those siblings 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?

"Deterministic name-based" implies when to prefer this over a random UUID generator, but the choice is left to inference rather than stated outright. There is no explicit "use this when you need reproducible IDs, otherwise use generate_uuid" 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 declare readOnly, idempotent, closed-world, so the safety profile is covered. The description adds real value: it discloses what is reported and, importantly, that embedded timestamps only exist for v1, v6, v7, which prevents false expectations for v4 UUIDs.

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 with zero waste, front-loaded with the verb and followed by the concrete output payload.

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?

No output schema exists, so the description must explain return values and does so adequately (version, variant, timestamp). It stops short of stating what happens for an invalid or nil UUID, which is the one missing piece for a validation tool.

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 0%, but there is only one parameter with the self-explanatory name 'uuid' and a string type. The description references 'a UUID' implicitly but adds no format, case, or variant constraints beyond that.

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 pair ('validate' and 'report') and resource (UUID) with the exact output fields (version, variant, embedded timestamp). It is trivially distinguishable from all siblings, which are generate_* tools.

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 by contrast with the generator siblings—this is the inspection counterpart—but the description never explicitly says when to use it or when not to. No mention of behavior on invalid input or alternatives.

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