read_assessment_workspace

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

The description goes well beyond the annotations. It discloses that economics requires a costing JSON structure (as_of, requested_by_ref, tax_basis, costs) and is internal operator data, that lists are paged and require passing the returned revision to reject mixed revisions, that the proposal defaults to the saved selected offer, and that output is draft Markdown and never published. These are non-obvious behavioral traits that materially affect invocation and interpretation.

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?

The description is compact and front-loaded: the main purpose is stated in the first sentence, followed by a terse list of views and then a few high-value behavioral caveats. Every sentence adds distinct information, with no filler or repetition of schema/annotation data.

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 description covers the non-obvious gotchas: the costing requirement, the revision-based pagination, the proposal default, and the non-publishing guarantee. It does not enumerate what each view contains, but the presence of an output schema likely covers return formats. For an 8-parameter read tool with zero schema descriptions, this is a thorough enough description for an agent to call it correctly.

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?

With schema description coverage at 0%, the description takes on the burden of explaining parameters. It explicitly documents the costing JSON subfields, explains the meaning of expected_revision in pagination, enumerates valid view values, and clarifies offer_ref via the proposal default. It does not explain limit/offset or project_id, but those are self-evident from their names and schema types.

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 opens with a specific verb and resource: 'Resume a saved assessment by reference or render its client report/proposal.' It lists concrete views (summary, dossier, report, etc.), making the scope clear. It does not explicitly contrast with sibling tools like save_assessment_workspace or recover_assessment_workspace, so it falls short of the highest bar for sibling differentiation.

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 implies usage context: this is the tool to use when you have a saved assessment reference and want to view or render it. It states that economics is 'internal operator data' and that this call 'never publishes,' giving some situational cues. However, it never explicitly says when NOT to use this tool or mentions alternatives (e.g., save vs. read), so the guidance is only implied.

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