Summarize represented ACE eligibility and evidence gaps across up to five provider-qualified merchant candidates. This is a bounded readiness sample, not a claimed full-catalog lost-revenue estimate.
| Name | Required | Description | Default |
|---|---|---|---|
| claims | No | ||
| country | No | US | |
| candidate_ids | Yes | ||
| excluded_terms | No | ||
| required_terms | No | ||
| preferred_terms | 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?
No annotations are provided, so the description carries full behavioral disclosure burden. The caveat 'This is a bounded readiness sample, not a claimed full-catalog lost-revenue estimate' is a meaningful limitation disclosure that prevents misuse, and 'Summarize' implies a read-only operation. However, it does not disclose output shape, failure behavior, or how evidence gaps are computed, so transparency is only partial.
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 two sentences with no filler. The main action and scope are front-loaded, and the caveat is placed immediately afterward. Every sentence earns its place.
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 six parameters, zero schema descriptions, no annotations, and no output schema, the description is far too sparse to give an agent enough context to invoke the tool correctly. It does not cover paramater semantics, expected output, or operational constraints beyond the bounded-sample caveat.
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 undocumented parameters. It provides general context about up to five merchant candidates and ACE eligibility, which loosely maps to candidate_ids and possibly claims, but it does not explain the meaning of claims, terms, country, excluded_terams, required_terms, preferred_terms, or operator semantics. This is not enough for reliable parameter construction.
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 ('Summarize') and resource ('ACE eligibility and evidence gaps') across up to five merchant candidates, and adds a clear scope caveat distinguishing it from a full-catalog lost-revenue estimate. It is clear but does not explicitly differentiate from sibling tools such as ace_check or compile_commerce_claims, so it stops short of a 5.
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 the tool is for provider-qualified merchant candidates in a bounded sample, but it provides no explicit when-to-use vs. alternatives guidance. It does not name any sibling tool or state conditions under which another tool would be preferred, leaving the agent to infer usage from the name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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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.