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

No annotations exist, so the description carries the full burden, and it does substantial work: it lists the five detection categories and the shape of the result (overall risk level, per-flag severities, monetization safety, publish-readiness). It stops short of stating that the operation is non-mutating and read-only, or noting constraints such as needing local file access or public YouTube URLs.

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?

Three tight sentences: purpose first, detection categories second, return shape last. Every clause carries information and the front-loading is correct.

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, the description usefully compensates by describing return fields, and it enumerates detection scope. The remaining gap is the nested transcript input union (file vs. URL vs. raw text), which is a meaningful omission for a tool whose only required parameter is that object.

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?

Top-level schema coverage is 0% and the description only says 'a transcript and optional metadata,' which is essentially a restatement of the two parameter names. The critical detail — that transcript accepts three mutually exclusive input modes (local .srt/.vtt/.txt path, public YouTube URL, or min-50-char raw text) — is never surfaced in prose and must be excavated from nested schema properties.

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?

Uses a specific verb and resource ('Scan a transcript and optional metadata') plus an explicit goal ('compliance risks before publishing'), then enumerates the exact risk classes detected. This makes it unmistakably distinct from the sibling content-generation tools (generate_chapters, generate_seo_metadata, extract_shorts_hooks) without needing to name them.

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 phrase 'before publishing' establishes clear usage context as a pre-publish gate, which is the key timing signal an agent needs. It does not state when NOT to use it or name an alternative, but for this tool set there is no obvious competing option.

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

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.

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

With no annotations, the description carries the full burden, and it does disclose useful behavior: the [Searchable Subject] + [Non-Spoiling Outcome Category] formula, the guaranteed 00:00 first chapter, and the spoiler guard driven by spoilerPolicy. It omits whether the tool is read-only, how transcript sources are prioritized, and what the response contains, so the disclosure is partial rather than complete.

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?

Three front-loaded sentences with no filler: purpose first, then the title formula, then the timestamp and spoiler rules. Some jargon ("reveal-type titles", "curiosity categories") is unexplained but does not bloat the text.

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 nested-config generation tool with no output schema and no annotations, the description gives a partial picture of the output (formula, first chapter at 00:00) but never states the return shape (e.g., list of titled timestamps) or failure modes for missing/invalid transcripts.

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 only 33% and the parameters are nested. The description only reinforces spoilerPolicy (already documented in the schema) and does not clarify how filePath, youtubeUrl, and rawTranscript are selected or prioritized, nor what minChapterDurationSec and targetDurationSec do to the output.

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?

States a specific verb (generate) and resource (YouTube chapters) with a clear qualifier (non-spoiling, from a transcript). It is distinctly different from siblings like extract_shorts_hooks and generate_seo_metadata, though it never names them explicitly.

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 output formula but gives no guidance on when to prefer this tool over siblings such as extract_shorts_hooks, nor any prerequisites (e.g., transcript must have timestamps). Usage is only inferable from the name.

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

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

With no annotations, the description carries the full burden, and it does disclose meaningful output behavior: five named archetypes, a hard '<60 characters' constraint, two image-prompt dialects, and the returned fields (description, tags). It says nothing about prerequisites (which transcript source is accepted, whether one is required), cost/latency of the generation, or whether existingTitle changes output shape.

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 dense sentences with zero filler, and the primary deliverable is front-loaded before the secondary return values. Nothing is repeated from the schema or restated from the name.

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?

A nested-object, three-parameter generation tool with an undocumented context block and no output schema needs the description to explain how to feed a transcript and what context knobs exist. Those gaps are significant even though the return-value summary is good for a tool with no output 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 only 33% and the description does not compensate: the entire `context` object (tone, contentType, spoilerPolicy, targetDurationSec) and `existingTitle` are never mentioned, and the three alternative transcript sources (filePath / youtubeUrl / rawTranscript) are not explained. The one constraint it states (60-char titles) is an output rule, not a parameter rule.

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?

Specific verb+resource with concrete deliverables: a five-archetype title matrix (named archetypes), a thumbnail brief in Midjourney and Flux formats, plus description and tags. An agent immediately knows what it gets back. It does not explicitly contrast itself with siblings like generate_chapters or extract_shorts_hooks, so it stops 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?

There is no when-to-use guidance, no exclusions, and no mention of the sibling tools that also operate on transcripts. The agent must infer from the name alone whether this or extract_shorts_hooks is the right call for title/hook work.

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