queue_article

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

No annotations are provided, so the description carries the full burden. It explicitly flags 'WRITE ACTION' and the plan-tier requirement, which is critical for an agent to know before invoking. It also discloses the duplicate-notice return behavior. It doesn't describe side effects on existing queue entries or confirm what a successful call returns, but the disclosed mutation nature and plan gating are strong.

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?

Four sentences, each earning its place: purpose/effect, input format, duplicate behavior, and access restriction. Slightly dense but front-loaded with the core action first. No fluff or repeated schema content, though the paragraph is a bit long without breaks.

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?

The tool has 5 params, is a mutating write action with no output schema, and zero annotations. The description covers the write nature, plan gating, duplicate handling, input formatting, and a cross-reference to list_keywords. The main gap is not describing what a successful response looks like, but given no output schema exists, the description compensates reasonably well.

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 100%, so the baseline is 3. The description adds meaningful context beyond the schema: it explains that keyword must match list_keywords exactly, that numbers serve dual roles (provenance and prioritisation), and that volume/position/competition are optional priority signals. This elevates the score above baseline.

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 clearly states the verb 'Queue' and resource 'an article for a keyword', and explains the downstream effect (AutoSEO drafts it on the next run). It distinguishes itself from siblings by being the only queue-writing tool, and even references list_keywords for correct keyword entry. This is specific and unambiguous.

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?

The description explicitly instructs how to format input ('Pass the keyword exactly as it appears in list_keywords'), explains when to include extra numbers ('when you have them... to prioritise the queue'), and describes the duplicate-notice behavior when a topic/article already exists. It also states planning restrictions (Pro+ vs Starter/trial read-only). This is comprehensive guidance.

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