continuum_get_offerA general-tools contract lookup that returns the canonical price, acceptance, delivery, and checkout terms without creating anything.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description adds context beyond this by specifying what the read surfaces (canonical offer terms across price, acceptance, delivery, checkout). The 'without creating anything' wording reinforces rather than contradicts the read-only annotations.
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?
A single sentence with no filler. Each clause earns its place: it states the operation, lists the returned term categories, and flags the absence of side effects. The key 'lookup' framing is front-loaded and everything else is directly informative.
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 zero-parameter, low-complexity read tool with rich annotations, the description covers the essential decision factors: what it does, what it returns, and that it has no side effects. It omits return-format details and there is no output schema, but that gap is minor for a get-style lookup an agent can safely invoke.
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?
The tool has zero parameters and schema coverage is 100% (vacuously), so the baseline of 4 applies. There are no parameters for the description to explain, and it correctly adds no misleading param detail.
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 identifies a specific verb/action ('returns') and a specific resource ('canonical price, acceptance, delivery, and checkout terms'), clearly framing it as a read/lookup operation. The 'without creating anything' clause explicitly differentiates it from the create/register siblings, so an agent can distinguish it 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?
The description establishes clear context: this is for retrieving offer terms as a pure lookup, and 'without creating anything' implies it is not the choice for creation workflows (which map to the continuum_create_* siblings). It does not name the alternatives explicitly or give when-not conditions, so it stops short of full exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool serves a clearly distinct purpose: creating a checkout, creating a sponsor packet, fetching an offer, registering a referral, and running an audit. There is no overlap between their responsibilities, making misselection highly unlikely.
All tool names follow a consistent verb_noun pattern in snake_case: create_checkout, create_sponsor_packet, get_offer, register_referral, run_audit. The naming is uniform, predictable, and easy to parse for an agent.
With 5 tools, the server is well-scoped for its purpose. Each tool covers a distinct workflow step, and there is no bloat or redundancy. The count fits comfortably within the ideal 3-15 range.
The tool set covers the core lifecycle: creation (checkout, sponsor packet, referral), lookup (offer), and validation (audit). Minor gaps exist, such as no update/cancel for created entities, but the essential workflow appears functional without dead ends.