How DroneLedger assesses evidence
get_methodologyEvidence states, attribution rules, source families and how to cite.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
get_methodologyEvidence states, attribution rules, source families and how to cite.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful content scope (evidence states, attribution rules, source families, citation) but says nothing about whether the content is static or versioned, nor how large the response is.
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 fragment with no filler, and the topic area is front-loaded. It is terse to the point of being a content list rather than a sentence, but nothing is wasted.
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-param, no-output-schema reference tool, listing the sections the document covers is close to sufficient. Only the absence of any usage framing keeps it from being fully self-sufficient.
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?
Zero parameters, so per the rubric the baseline is 4. There is no parameter semantics for the description to add or omit.
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 title plus description make it clear this returns DroneLedger's assessment methodology rather than a data record, distinguishing it from the lookup siblings like get_incident and get_trends. It enumerates the covered sections (evidence states, attribution rules, source families, citation guidance), though it uses a noun phrase rather than a verb and never explicitly says 'returns the reference documentation'.
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 on when to call this versus the data-retrieval siblings. An agent must infer that this is a reference lookup to consult when interpreting evidence states or attribution, but nothing in the text states that condition or any prerequisite.
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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