explore_reddit_discussions

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

With no annotations, the description carries the burden of disclosing behavior, and it does so meaningfully: it reveals output fields (upvote_ratio, age_in_days, next_page_token), explains how to interpret them, and signals pagination. It could add limitations (e.g., rate limits, scope of data), but it gives a solid behavioral picture for a read-only exploration 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 three short, front-loaded sentences with no filler. Each sentence earns its place: purpose, output interpretation, and pagination. The use of `code` formatting for field names is clean and scannable.

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 tool with 6 parameters, no annotations, and 0% schema coverage, the description is incomplete: it omits input parameter semantics and tool-selection context. It does cover purpose, key output interpretation, and pagination, and an output schema likely exists, which reduces the need to document return values. Overall, adequate but with clear gaps.

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 must compensate, but it only references next_page_token and output fields, not the actual input parameters. It does not explain keyword, sort, limit, subreddit, page_token, or time_filter. The agent is left to infer meaning from enum names and defaults, which is a significant 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 clearly identifies the tool's purpose: 'gauge public opinion and market acceptance' via Reddit discussions. It adds a step context ('STEP 2: SENTIMENT EXPLORATION') and specific behavioral cues (upvote_ratio, age_in_days), making the resource and intent clear. It does not explicitly differentiate from sibling tools like extract_public_opinion, so it falls short of a 5.

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 a clear use case: 'Use this to gauge public opinion and market acceptance,' and frames it as step 2 in a workflow. It offers practical guidance on interpreting results (upvote_ratio thresholds, age_in_days) and pagination. However, it gives no exclusions or alternatives despite likely overlap with sibling tools, so it lacks full when-not-to-use guidance.

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