plan_podcast_session

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

With no annotations, the description carries the behavioral disclosure burden. It does transparently describe the selection algorithm: episodes count their remaining time, fully played episodes are skipped, and scanning stops at the first unplayed episode that doesn't fit. However, it does not explicitly state whether this is a read-only planning operation or whether it starts playback or mutates state.

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 dense sentences with no filler. It front-loads the primary action, then gives the key behavioral rules in compact, precise language.

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?

The core algorithm and source scope are well covered, and the schema documents parameters thoroughly. However, with no output schema and no explicit statement about whether the tool returns a plan or executes a session, an agent may need additional context to know the exact return shape and the relationship to start_podcast_session.

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 100%, so the baseline is 3. The description adds meaning to `minutes` by clarifying that session length is measured against remaining episode time, and it frames the source as saved episodes. It does not add significant semantics beyond the schema for `kind`, `saved_only`, `max_results`, or `response_format`.

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 states a specific action and resource: greedy-pack saved podcast episodes into a listening session of a given length. It adds precise selection rules (remaining time, skipping fully played episodes, stopping at the first non-fitting episode), which makes the purpose clear. However, it does not explicitly distinguish itself from sibling tools like start_podcast_session.

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?

No explicit guidance on when to use this tool versus alternatives such as start_podcast_session, queue_next_episode, or episode_resume. The use case is implied by the verb 'plan' and the algorithm, but the description never states when a session plan is preferable to starting playback directly.

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