Plan execution routes for a short-lived server-issued ACE decision_ref. Routing is strictly post-truth: it cannot change product ranking or ACE Verdict and only exposes protocol paths that are actually verified as executable.
| Name | Required | Description | Default |
|---|---|---|---|
| decision_ref | Yes | ||
| preferred_protocols | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses meaningful traits: the routing is immutable with respect to ranking/verdict and only surfaces verified executable paths. Yet it leaves side effects, authentication/permissions, expiry behavior, and failure modes unstated, and the term 'post-truth' could confuse an agent.
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?
Two dense sentences, front-loaded with the verb and resource, and no filler. The second sentence is slightly convoluted and 'post-truth' is jargon, but overall the description is appropriately compact.
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 two-parameter tool with no output schema and no annotations, it gives core behavioral context but does not describe the return shape of 'execution routes', how the decision_ref expiry is surfaced, or how this tool relates to the many commerce siblings. An agent could invoke it, but would be guessing at output details.
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, but it only references decision_ref by name and hints at 'protocol paths' without explaining preferred_protocols, its optionality, the enum values, or how it affects routing.
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 names a specific verb ('Plan') and resource ('execution routes' for a server-issued ACE decision_ref), and clarifies that it returns only verified executable protocol paths. It does not explicitly distinguish itself from sibling tools such as commerce_preflight or create_commerce_referral, and the phrase 'post-truth' is ambiguous jargon rather than a clear domain term.
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 implies the tool should be used after an ACE decision exists ('short-lived server-issued ACE decision_ref') and that routing cannot alter ranking or verdict, which signals a post-decision use case. However, it never names alternatives or states explicit when-to-use/when-not-to-use conditions relative to the sibling tools.
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.
Most tools target distinct workflow stages (discovery, identity, claims, decision, referral), and the detailed descriptions help separate them. However, ace_check and commerce_preflight both expose ACE Verdict decisions, and verify_global_offer is an explicitly legacy alternative to commerce_preflight, so an agent can still misselect among the verification/decision tools.
All names are readable snake_case, and action tools use a verb_object pattern while query/metadata tools use noun phrases. The split is not chaotic, but it is inconsistent (e.g., product_discovery vs resolve_product_identity), and the commerce_/commercial_ prefix variation adds a minor wrinkle.
Fifteen tools is at the upper end of a well-scoped service and is reasonable for a broad commerce intelligence domain. The count feels slightly heavy because there are several descriptive/policy tools and at least one legacy overlap (verify_global_offer) that could be consolidated.
The set covers the core pre-purchase workflow: discovery, identity resolution, claim compilation, verification, recalls, merchant readiness, trust, referrals, and routing. Minor gaps exist, such as no explicit claim-management or decision-status retrieval separate from the decision products, but these do not create dead ends.