harris_civil_coverageWhat this Harris County docket corpus actually covers — case and party row counts, the filing-date range present, and the clerk files it was last built from. Call this before concluding anything from an empty search result: the corpus is a rolling activity window, and this tool is how you tell "no such case" from "not in the window covered".
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Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only and non-destructive, and the description adds meaningful behavioral context: the corpus is a rolling activity window and this tool distinguishes 'no such case' from 'not in the window covered.' It also discloses what output to expect (counts, date range, clerk files). This is genuinely valuable beyond annotation metadata.
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 front-load the factual scope and then provide a practical usage warning. Every sentence earns its place, and there is no filler or repetition. The structure is compact and easy to parse.
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 metadata tool with read-only annotations, the description is complete: it explains what the tool reports, why it matters, and when an agent should call it. The absence of an output schema is mitigated by naming the output contents. An agent should be able to use this tool correctly without further information.
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 the description has no parameter semantics to explain. The baseline for a no-parameter tool is 4, and the description appropriately focuses on output and usage rather than inputs. No additional parameter-level detail is needed.
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 states the tool's purpose: it reports what the Harris County docket corpus covers, including row counts, filing-date range, and source clerk files. It is specific about the resource, but it does not explicitly differentiate this tool from sibling tools like harris_civil_case or harris_civil_search_party. The 'coverage' framing makes the distinction reasonably inferable, though not explicit.
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 gives a concrete trigger: call this before concluding anything from an empty search result because the corpus is a rolling activity window. This is strong situational guidance, but it does not mention when not to use the tool or name alternatives. The guidance is clear enough for the main use case even though exclusions are absent.
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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