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Nitrozen

by io.nitrozen
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Create a changelog entry

create_entry

Create a new changelog entry for a project.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "project_id": "<project_id>",
      "title": "<title>",
      "content": "<content>",
      "category": "<category>"
    },
    "name": "create_entry"
  }
}

Input Schema

NameRequiredDescriptionDefault
titleYesEntry title
contentYesEntry content (Markdown)
categoryYesEntry category slug. Every project has the built-in categories 'new', 'improvement', 'fix', and 'announcement'; projects with custom categories enabled may also have additional project-specific slugs.
project_idYesProject ID
is_publishedNoPublish immediately (default: false)
published_atNoISO 8601 publish date (defaults to now if is_published is true)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnly=false, destructive=false, idempotent=false, and openWorld=true, so the safety profile is covered. The description adds nothing beyond that: it doesn't say that a created entry defaults to unpublished, that duplicate calls create duplicate entries (non-idempotent), or whether custom category slugs are validated. For a 6-param mutation with an open-world hint, that is thin.

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

Conciseness4/5

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

A single front-loaded sentence with zero waste or filler. It is efficient, though its brevity is under-specification rather than tight editing.

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

Completeness2/5

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

For a write tool with six parameters and an open-world annotation, the description says nothing about the draft/published lifecycle, side effects such as notifications, or what identifying information comes back. The schema covers fields, but the agent is left guessing about the operation's consequences.

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%, including a detailed explanation of category slugs and publish defaults, so the schema carries the semantics. The description repeats none of it and adds no extra meaning, making 3 the correct baseline.

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

Purpose4/5

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

States a specific verb and resource (create + changelog entry) scoped to a project, which is enough to distinguish it from get_entry/update_entry/delete_entry. It offers no explicit differentiation from the create_* siblings or note about what a created entry's initial state is, 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.

Usage Guidelines2/5

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

There is no guidance on when to use this versus update_entry or create_project, no prerequisite that project_id must reference an existing project, and no mention of when to leave the entry as a draft versus publishing. The agent must infer everything from the schema.

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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