get_flagship_evidence_map

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden—and it makes good use of that space. It explicitly discloses that edges only identify the same entry across adjacent axes and 'do not claim causation or form a score', which prevents an agent from misinterpreting the graph semantics. It also states the six receipts are 'independent', a meaningful structural guarantee. It does not describe the response format, but for a zero-parameter read-only tool the disclosed caveats are the most important behaviors.

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 sentences, no filler. The first sentence front-loads the core content and enumerates the six axes compactly; the second delivers the essential interpretive caveat. Every phrase 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?

For a zero-parameter get tool with no output schema, the description covers both what the map contains (six axes) and how the edges should be interpreted (identity mapping, not causation or scoring). A minor gap is the absence of sibling differentiation and the meaning of 'receipt', but the description is largely sufficient for an agent to call the tool and understand the result.

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 takes zero parameters, so the schema fully documents the interface and the description cannot add parameter-level meaning. Per the baseline for 0-param tools, a 4 is appropriate; there is nothing semantically missing that the description would need to compensate for.

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 clearly identifies the resource—a map with six evidence dimensions per flagship example—and enumerates the axes (editorial surface, lifecycle, evidence contract, etc.), so an agent can tell what data this tool exposes. However, it lacks an explicit verb like 'retrieve' or 'returns', relying on the 'get_' prefix to convey the operation, and it never names a sibling to distinguish itself from.

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?

There is no when-to-use guidance, no exclusions, and no mention of alternatives. Given the large sibling set including get_semantic_map, get_evidence_contract_audit, and get_adoption_trends, an agent must guess which tool covers which question. The only usage signal is the implied context of 'flagship examples' and 'evidence', which is thin.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.