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Glama

draft_create

Create or re-version a canonical draft with title, body, tags, audience, canonical URL, and per-platform variants; returns a content hash that approval binds to.

Instructions

Create (or re-version) the canonical draft: title, body, subtitle, canonical_url (home), tags, audience, per-platform variants. Hash-bound: the returned content_hash is what approval binds to. Re-creating an existing draft_id makes a NEW version and resets approval to none.

Input Schema

NameRequiredDescriptionDefault
bodyYes
tagsNo
titleYes
audienceNo
draft_idNo
subtitleNo
variantsNo
canonical_urlNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does real work: it discloses hash-binding semantics, that content_hash is the value approval binds to, and that re-creating an existing draft_id creates a new version and resets approval to none. It omits auth/permission requirements and failure modes (e.g. what happens on invalid variants), which keeps it short of 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.

Conciseness4/5

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

Three dense sentences, front-loaded with what is created and followed by the behavior that matters most (hash binding, versioning side effect). No filler, though the telegraphic '(home)' parenthetical is slightly cryptic rather than explanatory.

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

Completeness3/5

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

There is no output schema, and the description does say a content_hash is returned, which covers the key return value. However, for a mutation tool with 8 parameters, a nested variants object, and zero annotation coverage, it leaves the variants payload shape, validation behavior, and permission requirements unexplained.

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

Parameters2/5

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

Schema description coverage is 0% across 8 parameters, so the description must supply the missing semantics. It mostly just re-lists the parameter names (title, body, subtitle, tags, audience) with only two hints of meaning — 'canonical_url (home)' and 'per-platform variants' — and gives no structure for the nested variants object or the draft_id format.

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 (create/re-version) and resource (the canonical draft) and enumerates the content it covers. The '(or re-version)' clause and the draft_id note separate it from a pure create, though it never names draft_preview, draft_approve, or syndicate_drafts to draw the workflow boundary explicitly.

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

Usage Guidelines3/5

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

The note that re-creating an existing draft_id makes a new version and resets approval implies the intended entry point of the draft→approve→syndicate flow, but it never says to use this instead of draft_preview or draft_approve, nor when not to call it. Usage must be inferred from the sibling names.

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