Six independent receipts for every flagship example: editorial surface, lifecycle, declared evidence contract, confirmed evidence, strict qualification, and observed adoption. Edges identify the same entry across adjacent axes; they do not claim causation or form a score.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 burden of explaining behavior. It meaningfully discloses that the output has six independent axes, that edges identify the same entry across adjacent axes, and that the result does not claim causation or form a score. This is substantive behavioral context beyond the tool name.
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 compact and the key semantic constraints are stated directly, with the edge caveat clearly separated. It loses a point because the dense terminology and 'receipts' metaphor require unpacking to be fully useful.
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 no-parameter getter with no output schema, the description covers the basic shape and the main interpretative caveat. However, it does not explain what the six axes concretely mean, how an agent should use the map, or how this tool differs from closely related siblings, leaving notable gaps.
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, so there is no parameter burden for the description to carry. The baseline for a zero-parameter tool is 4, and the description adds no conflicting or missing parameter information.
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 resource (flagship evidence map) and enumerates its six axes, so it is not a tautology. However, it lacks an explicit verb such as 'retrieves' or 'returns,' and the metaphor 'receipts' plus jargon like 'editorial surface' leaves the actual purpose somewhat opaque.
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 given about when to use this tool versus siblings such as get_flagships, get_evidence_contract_audit, or get_semantic_map. The only directive-like content is a caveat that edges are identity links, not causation, which is interpretive rather than selection guidance.
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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