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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real context beyond that: it is free, the data comes from a daily archive, and the score is a composite of four named signals. It still omits pagination, response shape, and whether the Agent Demand Index is always returned or only for certain feeds.

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?

One dense but front-loaded sentence that leads with the tool's identity and score definition before listing coverage. Nothing is redundant, though the nested parenthetical makes it heavier than necessary for a two-parameter tool.

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?

With no output schema and no annotation detail on returns, the description must explain what comes back; it does name the leaderboard and Agent Demand Index, but not the item shape, ordering, or whether the Agent Demand Index is coupled to the feed selection. Adequate for invocation, thin for interpreting results.

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?

Schema description coverage is 0%, so the description carries the full burden. It partially compensates by enumerating the four content categories that map to the feed enum (github-ai-repos, mcp-servers, llm-pricing, hf-trending), though the LLM/pricing mapping is loose. The limit parameter (1-100, default 25) is not mentioned at all, leaving a real gap.

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 the resource (ADC Momentum leaderboard) and the exact content it returns: a 0-100 score derived from growth velocity, consistency, recency and agent demand, plus an Agent Demand Index. The coverage list (GitHub AI repos, MCP servers, LLMs, Hugging Face items) overlaps with siblings like get_github_ai_repos and get_mcp_servers, but the momentum-score framing distinguishes it. It stops short of explicitly contrasting itself with those siblings.

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?

Only the 'Free:' prefix hints at a reason to prefer this over paid siblings; there is no statement of when to use a leaderboard versus get_trends, get_github_ai_repos or get_mcp_servers. No prerequisites, exclusions or alternative-routing guidance are given. The agent must infer usage from the description alone.

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