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toolkit-mcp-server: generate id

toolkit_generate_id
Read-only

Mint cryptographically-random identifiers using the platform CSPRNG — the correct source for IDs that must be unpredictable, unlike model-generated values. type selects the format: uuid_v4 (random, the default), uuid_v7 (time-ordered, sortable by creation), or ulid (26-char Crockford-base32, lexicographically sortable). Set count to mint a batch in one call (up to 1000); the returned ids array always contains exactly count values and is never truncated. For uuid_v7 and ulid, a batch is monotonic — strictly increasing even within the same millisecond — so the ids array stays in sorted creation order; ids minted in the same millisecond are separated by random gaps, so no id in a batch can be derived from another. IDs from this tool feed into toolkit_generate_qr (pass ids[0] as data) to create a scannable code.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoIdentifier format: uuid_v4 (random), uuid_v7 (time-ordered), or ulid (sortable Crockford-base32).uuid_v4
countNoHow many identifiers to mint (1–1000). The full batch is always returned.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsNoThe minted identifiers — exactly count of them, in mint order; for uuid_v7 and ulid that order is strictly increasing (sorted by creation), with random gaps between ids minted in the same millisecond.
typeNoThe identifier format that was minted.
countNoThe number of identifiers minted (equals the requested count).
errorNoPresent when the call failed. Absent on success.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / properties / ids / description
      Previous value: -"The minted identifiers — exactly count of them, in mint order; for uuid_v7 and ulid that order is strictly increasing (sorted by creation)."New value: +"The minted identifiers — exactly count of them, in mint order; for uuid_v7 and ulid that order is strictly increasing (sorted by creation), with random gaps between ids minted in the same millisecond."
  2. Changed6 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • addedInput schema / additionalProperties
      Added value: +false
    • changedOutput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • addedOutput schema / anyOf
      Added value: +[
      +  {
      +    "not": {
      +      "required": [
      +        "error"
      +      ]
      +    },
      +    "required": [
      +      "type",
      +      "ids",
      +      "count"
      +    ]
      +  },
      +  {
      +    "required": [
      +      "error"
      +    ]
      +  }
      +]
    • addedOutput schema / properties / error
      Added value: +{
      +  "additionalProperties": {},
      +  "description": "Present when the call failed. Absent on success.",
      +  "properties": {
      +    "code": {
      +      "description": "JSON-RPC error code for this failure.",
      +      "maximum": 9007199254740991,
      +      "minimum": -9007199254740991,
      +      "type": "integer"
      +    },
      +    "data": {
      +      "additionalProperties": {},
      +      "properties": {
      +        "reason": {
      +          "description": "Machine-readable failure mode.",
      +          "type": "string"
      +        },
      +        "recovery": {
      +          "additionalProperties": {},
      +          "description": "Actionable next step for the caller.",
      +          "properties": {
      +            "hint": {
      +              "type": "string"
      +            }
      +          },
      +          "required": [
      +            "hint"
      +          ],
      +          "type": "object"
      +        },
      +        "retryable": {
      +          "description": "Whether retrying may succeed.",
      +          "type": "boolean"
      +        }
      +      },
      +      "type": "object"
      +    },
      +    "message": {
      +      "description": "Human-readable description of what went wrong.",
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "code",
      +    "message"
      +  ],
      +  "type": "object"
      +}
    • removedOutput schema / required
      Removed value: -[
      -  "type",
      -  "ids",
      -  "count"
      -]
  3. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, but the description goes far beyond: it discloses the source (platform CSPRNG), output guarantees ('always contains exactly count values and is never truncated'), monotonic ordering for uuid_v7/ulid, strict increasing within the same millisecond, and the security property that 'no id in a batch can be derived from another'. This rich behavioral disclosure is not present in annotations and is critical for correct use.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Each sentence earns its place: purpose and source are front-loaded, then type semantics, batch behavior, ordering guarantees, and downstream integration. There is no fluff or repetition of schema verbatim; the description is dense but well-structured, guiding the agent from conceptual purpose to invocation details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter tool with an output schema and clear annotations, the description fully covers what an agent needs: when to use, format selection, batching limits, return-count guarantees, ordering behavior, and integration with a sibling. No critical information is missing, and the output schema handles return-shape details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds meaningful semantics beyond the schema: it explains the default (uuid_v4), clarifies each type's ordering properties, specifies 'up to 1000' for count, and introduces the guarantee that the full batch is always returned without truncation. This adds real value over the schema alone, though the schema already covers basic type and count limits.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description opens with 'Mint cryptographically-random identifiers using the platform CSPRNG' — a specific verb ('mint'), resource ('identifiers'), and method (CSPRNG). It distinguishes this tool from siblings by stating it is the correct source for unpredictable IDs and explicitly contrasts with 'model-generated values'. The purpose is unambiguous and differentiates from toolkit_hash_value, toolkit_encode_value, etc.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says to use this tool when IDs 'must be unpredictable' and indicates 'unlike model-generated values' — an explicit when-not. It also provides a concrete downstream workflow: 'feed into toolkit_generate_qr (pass ids[0] as data)', which acts as a usage directive. Combined with format-selection guidance for type and batching with count, the agent knows exactly when and how to invoke it.

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

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