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

Annotations already mark the tool as read-only and idempotent, so the description correctly adds behavior beyond that: it replays from an append-only ledger, clamps days, treats backfill as seed-only, and overlays plan lines. Nothing contradicts the annotations; the description enriches the behavioral model without redundancy.

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 information-dense but not bloated; each clause contributes a distinct constraint or behavior. It is front-loaded with the core purpose, then cleanly covers each optional parameter. A couple of phrases could be tightened, but it earns its length given the complexity of the tool.

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?

There is no output schema, so the description must hint at return shape. It mentions a 'summary' and for baseline_id 'exact frozen-task planned/actual JSON with coverage', which gives a reasonable sense of output. Combined with the detailed behavior and parameter semantics, an agent can infer what the tool returns well enough to call it correctly, though a bit more explicit output structure would push it to 5.

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 only 25% (target_date only), yet the description explains every parameter in functional terms: root_id scopes the subtree, days is clamped with default 30, target_date defines the plan-line endpoint, and baseline_id selects the frozen-task variant. This fully compensates for the sparse schema, giving agents the meaning behind each field.

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 precise statement of what the tool computes: a daily burndown series replayed from the append-only ticket ledger, including per-day scope, remaining, done, and added/completed flows, plus a summary. This clearly distinguishes it from any sibling tool—none other mention burndown or ledger replay—so an agent knows exactly what to expect.

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?

It gives explicit usage conditions for the optional parameters: root_id scopes to an epic subtree, days clamps to 7–180, target_date overlays a straight-line plan, and baseline_id provides frozen-task planned/actual JSON. It even contrasts target_date and baseline_id ('Alternatively'), and explains that backfill rows never count as additions—guiding when each parameter is appropriate.

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