company_board_pack

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

No annotations are provided, so the description carries the burden. It discloses that the output is JSON with a `rendered` markdown field, and it lists the data sources (persisted periods, revenue and payables chains, retention cases) and conditional inclusion of plans. However, it does not disclose side effects, whether it reads or writes, required permissions, or failure behavior. For a read-like generation tool, this is partial but not rich.

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 a single dense sentence that front-loads the main content list, but it is overstuffed with a long enumeration and a trailing conditional clause. It is not structured with separate sentences for purpose, inputs, and output, making it harder to parse. It earns its place but could be clearer.

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?

Given 10 parameters, 0% schema coverage, no annotations, and a complex output, the description is incomplete. It does not explain the meaning or format of the JSON inputs (bundle_json, decisions_json, exceptions_json, etc.), nor does it clarify the relationship between the required `bundle_json` and the optional JSON parameters. An agent would struggle to assemble the correct arguments.

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 description coverage is 0%, so the description must compensate for 10 parameters. It mentions `bundle_json` implicitly via 'when the bundle carries their plans' and `month` via 'The month's board pack', but it does not explain `project_id`, `now`, `evals_json`, `forecast_json`, `decisions_json`, `exceptions_json`, `growth_review_json`, or `intelligence_review_json`. The description adds almost no meaning beyond the schema's bare titles.

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 states a specific verb and resource: it generates the month's board pack from persisted periods, revenue and payables chains, and retention cases, listing the contents (revenue, spend, books verified, cash proven, runway, exceptions, decisions, counterfactuals, etc.). It is clear what the tool produces, though it does not explicitly differentiate from sibling tools like finance_board_pack or company_board, which could be ambiguous.

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 when to use it (when you need the month's board pack with the listed contents) but does not explicitly state when not to use it or name alternatives such as finance_board_pack, company_board, or finance_saas_board_pack. The context is clear enough for a general use case, but exclusions and alternative routing are absent.

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