get_digest

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

Despite no annotations being provided, the description covers key behaviors: deduplication by link, sorting by newest first, handling of undated items, truncation of summaries, and the structure of the returned dict. It also explains default values and edge cases (e.g., pass 0 to disable time filter). The description provides sufficient transparency for a read-only aggregation tool.

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 well-structured with a clear opening line, a labeled 'Args' section, and a final sentence describing the return value. It uses a consistent format and avoids unnecessary words. However, it could be slightly more concise by consolidating some parameter details (e.g., default values are already in the schema).

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 complexity (5 parameters, no output schema, no annotations), the description is fairly complete. It explains return value structure ('items', 'count', success count, 'errors') and covers key edge cases (undated items, dedup, sorting). It does not provide example output or error handling beyond per-feed errors, but it is sufficient for most use cases.

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 input schema has 0% description coverage, so the description carries the full burden. It explains each parameter's purpose and behavior: 'feeds' (RSS/Atom URLs with examples), 'keywords' (case-insensitive filtering, behavior when omitted), 'hours' (time filter with undated items handling), 'max_items' (cap after dedup+sort), and 'summary_max_chars' (truncation with ellipsis). This adds substantial meaning beyond the schema's basic titles and types.

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 builds a competitive-intelligence digest from multiple RSS/Atom feeds, specifying the action (build a digest) and the resource (feeds). It implicitly distinguishes from siblings 'fetch_feed' (single feed) and 'load_opml' (import OPML) by focusing on aggregation and filtering.

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 explains the parameters and their defaults, which implies usage scenarios (e.g., filtering by keywords, time range). However, it does not explicitly state when to use this tool versus alternatives like 'fetch_feed' or 'load_opml', nor does it provide when-not-to-use guidance. The usage context is implied but not explicit.

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