Assemble workspace

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

Goes well beyond annotations by disclosing the mutation's consequence — passing workspace_id overwrites that workspace's selected-item list — which explains why destructiveHint=true despite the read-flavored name 'assemble'. It also discloses the ranking factors (format, performance tier, local engagement) and that no model analysis is performed by the tool, setting the agent's expectations for follow-up work.

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 doing distinct work — purpose, alternatives, parameter behavior, and expectation-setting — with the core purpose front-loaded. No filler or restatement of the name.

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?

With no output schema, the description carries the burden of describing returns; it names the slice contents (examples, audience questions, taste/own-channel context) but not the response shape or ordering guarantees. For a 6-parameter, zero-required tool this is close to complete, with only return-format detail missing.

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, but the description adds genuine meaning beyond the schema for workspace_id (overwrite vs read-only slice) and for your_channel (adds a self-analysis snapshot). It doesn't add detail for topic/format/hook_target beyond pointing at get_facet_taxonomy, which the schema already does.

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?

States a specific verb+resource with scope: 'Select and rank saved examples for planning a video,' plus what the selection is conditioned on (audience questions, taste, own-channel context). It explicitly contrasts itself with the two nearest siblings, get_workspace and critique_against_corpus, so an agent can route without opening any schema.

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?

Gives explicit when-to-use and names alternatives: 'Use to assemble a corpus slice; use get_workspace to read a saved workspace or critique_against_corpus to review a draft.' It also gives a when-to-use-which-parameter rule: supplying workspace_id replaces the selected-item list, omitting it only returns the slice.

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