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

No annotations are provided, so the description carries the full behavioral burden and does real work: it discloses partial-patch semantics, the clear-to-NULL mechanism, that renaming the code keeps existing patron redemption rows because they key on coupon id, and an authorization requirement. Remaining unstated behaviors, such as date-validity checks or conflict handling, are minor gaps in an otherwise disclosure-rich text.

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 short blocks, front-loaded with the core purpose, then usage semantics, then the restriction — no filler sentences. The parenthetical '(NULL in the schema)' is a slight internal reference but earns its place by disambiguating the clear flags.

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?

For a 10-parameter mutation with no annotations and 0% schema coverage, the description covers the non-obvious behaviors but leaves several parameters and edge conditions unexplained. The presence of an output schema relieves the return-value burden, keeping this at an acceptable minimum rather than failing.

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. It adds meaning for clear_uses_per_patron and clear_total_uses (unlimited/NULL semantics) and implies that `name` is the coupon code via the rename note. However, several parameters — dpop_token, valid_from/valid_until formats, discount_percent semantics, and coupon_id — receive no explanatory value beyond their type names.

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?

Opens with a specific verb-resource pair — 'Patch a coupon's editable fields' — that names the operation, target, and scope in one sentence. This cleanly separates it from siblings like goodearth_delete_coupon, goodearth_mint_coupon, goodearth_list_coupons, and the credential-update tools, without needing to inspect 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 concrete operational guidance: pass only the fields you want to change, use the clear_* flags to null out caps, and notes the tool is restricted to operators with proof. It does not explicitly name alternatives or exclusion conditions, but the update-vs-create/delete/read split among siblings is easily inferable from the tool names.

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