count_gtin_coverageGlobal coverage statistics: GTINs, nodes, makers (supply), retailers (demand).
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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 the full burden of disclosing behavior. It only names metric categories and supply/demand framing; it does not state that the operation is read-only, describe how coverage is computed, or mention any data-scope caveats. For a zero-parameter tool the risk is low, but the absence of behavioral detail is still a gap.
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 compact sentence that front-loads the core idea ('Global coverage statistics') and then enumerates the relevant facets. Every phrase earns its place, with no filler or repetition.
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 that the tool has no required parameters and an output schema is present, the description provides sufficient domain context for a caller to understand what the tool reports. It does not explain when to choose this over siblings, but that is a moderate gap rather than a fatal one for such a simple call signature.
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 input schema has zero parameters and 100% schema description coverage by construction, so there is no parameter documentation burden on the description. The baseline for zero parameters is 4, and no additional parameter context is necessary.
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 resource domain ('GTINs, nodes, makers, retailers') and a clear verb concept ('coverage statistics'), and distinguishes itself from sibling resolution/list tools by emphasizing global coverage. It could be slightly more explicit that it returns counts, but it is not vague or tautological.
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?
No guidance is provided on when to use this tool vs. siblings like node_market, list_brands_by_node, or find_retailers. The 'Global' prefix implies a high-level overview, but there are no explicit alternatives, exclusions, or selection conditions.
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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Multiple tools overlap heavily: resolve_gtin, resolve_sparks, and get_signal_chain all resolve GTINs to different but closely related signals, and resolve_node vs node_market both return the same node with makers/retailers counts. Agents will struggle to pick the correct tool without reading deep into descriptions.
Most tools follow a clear verb_noun pattern (check_, count_, find_, get_, list_, resolve_), but node_market breaks the pattern and the get_ vs resolve_ distinction is not obvious. Overall readable with only minor deviations.
14 tools is well-scoped for a CPG knowledge graph covering GTIN resolution, eligibility, supply/demand search, node metadata, taxonomy, and brand coverage. Each tool reasonably earns its place without overwhelming the surface.
The surface covers the apparent domain comprehensively: GTIN resolution, eligibility checks, maker/retailer discovery, node/spine queries, SKU taxonomy, brand listings, signal chains, and registries. For a read-only knowledge graph, there are no obvious dead ends or missing core operations.