extract_gov_landscape

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

The description adds valuable behavioral context beyond annotations. While annotations indicate read-only and open-world operations, the description reveals this is a composite tool that queries four sources simultaneously, returns a unified timestamped report, and has specific output format expectations (answers three questions). It doesn't mention rate limits, authentication needs, or data freshness, but provides meaningful operational context.

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 efficiently structured and front-loaded: it immediately states this is a composite tool, lists the four sources, specifies the three questions it answers, and describes the output format. Every sentence adds value without redundancy. The final sentence about uniqueness appropriately emphasizes differentiation without being verbose.

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 the tool's complexity (composite queries across four sources) and lack of output schema, the description does well to specify what questions it answers and the report format. However, it doesn't detail potential limitations (like data availability across sources) or error handling. With annotations covering safety aspects and good schema coverage, the description provides solid context but could be more complete about operational constraints.

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?

With 67% schema description coverage, the description doesn't add significant parameter semantics beyond what the schema provides. The schema already documents the three parameters well, including the optional github_url and default max_length. The description mentions using the query for GitHub/changelog sections when github_url is omitted, but this is already implied in the schema descriptions. Baseline 3 is appropriate given the good schema coverage.

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 explicitly states the tool's purpose: it's a composite intelligence tool that simultaneously queries four specific sources (USASpending.gov, GitHub, Hacker News, product changelog) to answer three specific questions about government contract winners, development activity, and developer community awareness. It clearly distinguishes itself from siblings by being 'Unique — not available in any other MCP server' and by combining these four sources into one unified report.

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 provides clear context about when to use this tool: for analyzing companies/keywords/NAICS codes across government contracts, development activity, and community awareness. It implicitly distinguishes from siblings by being a composite tool, but doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools (like extract_govcontracts, extract_github, extract_hackernews).

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