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Python
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Delimit Intel Dataset Freeze

delimit_intel_dataset_freeze

Lock a dataset against any future writes to ensure replay integrity for evidence or signed attestations. This makes the dataset immutable and rejects subsequent write attempts.

Instructions

Freeze a dataset to make it immutable for replay integrity.

When to use: when a dataset is about to be referenced as evidence or signed attestation, and you want to lock its content forever. When NOT to use: to delete a dataset (the registry is append-only) or to inspect what's frozen (use delimit_intel_dataset_list).

Sibling contrast: delimit_intel_dataset_list inventories; delimit_intel_dataset_register writes; this locks against further writes.

Side effects: writes a frozen marker to the registry via backends.tools_data.intel_dataset_freeze. Subsequent writes to this dataset id will be rejected.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataset_idYesDataset identifier from the registry. Required.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv4.7.9
    • changedInput schema / properties / dataset_id / description
      Previous value: -"Dataset identifier."New value: +"Dataset identifier from the registry. Required."
  2. Changed1 schema field changedv4.5.5
    • addedInput schema / properties / dataset_id / description
      Added value: +"Dataset identifier."
  3. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

The description discloses concrete side effects: writing a frozen marker to a specific backend path and causing subsequent writes to the dataset id to be rejected. This adds meaningful behavioral context beyond the annotations, which only indicate readOnlyHint=false and destructiveHint=false.

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?

The description is well-structured with a clear lead sentence followed by concise, purposeful sections for usage, non-usage, sibling contrast, and side effects. Every sentence adds relevant information without fluff.

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 simple single-parameter tool with an output schema, annotations, and clear sibling routing, the description is complete. It captures the action, rationale, exclusions, side effects, and consequences for future writes.

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

Parameters3/5

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

Schema description coverage is 100%, with dataset_id already documented as the registry identifier and required. The description adds minimal new semantic detail about the parameter itself, so the baseline score of 3 is appropriate.

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?

The description opens with a specific verb and resource: 'Freeze a dataset to make it immutable for replay integrity.' It clearly distinguishes this tool from siblings by contrasting list, register, and freeze behaviors.

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 provides explicit 'When to use' and 'When NOT to use' sections, including a specific alternative for inspection (delimit_intel_dataset_list). It also explains that deletion is inappropriate because the registry is append-only, leaving no ambiguity about selection.

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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