extract_shorts_hooks

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

With no annotations, the description carries the full behavioral burden. It usefully discloses domain logic—the weighted ShortScore formula and hard rejection rules for filler starts, dangling pronouns, and dead zones—which is real behavioral context. However, it omits operational traits: it never states that the tool is read-only, how transcript sources are handled, whether results are deterministic, or what happens on invalid/failed transcript retrieval. This is helpful but incomplete for an unannotated 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?

Two tight sentences: the first sentence front-loads purpose and output, the second adds the key rejection-rule behavior. The formula is expressed compactly and every clause earns its place. There is no filler or redundancy.

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 a nested object input, no output schema, and no annotations, the description is only partially complete. It explains the scoring and rejection logic but does not describe the shape of a returned candidate (e.g., whether it includes timestamps, titles, per-component scores) or the practical input pathways (file vs. URL vs. raw text). An agent can call it, but cannot fully anticipate the result or handle transcript-source variations without consulting the schema.

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 33% (low), so the description should compensate by explaining parameter meaning. Instead, it mentions no parameters at all—not the transcript source options (filePath vs. youtubeUrl vs. rawTranscript), not the context defaults (tone, contentType, spoilerPolicy, targetDurationSec), and not maxResults. The schema's nested leaf descriptions do some work, but the description adds zero parameter semantics beyond that.

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 a specific verb ('Analyze') and resource ('a transcript'), and states the exact output: ranked YouTube Shorts candidates scored by a named ShortScore formula. This is clearly distinguishable from the sibling tools (generate_chapters, generate_seo_metadata, audit_compliance), which serve different output types. An agent can tell exactly what this tool produces without opening the schema.

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 implies when the tool is useful (extracting Shorts hooks from a transcript) but never explicitly says when to use it versus the sibling tools or when not to use it. There is no mention of prerequisite conditions (e.g., the transcript must be public for YouTube URL extraction) or alternative tools for overlapping goals. Usage is inferable but not guided.

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