Klyf

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered; the description adds real context on top: it reads the user's own connected channel directly, requires no input, and must be called immediately without clarifying questions. It also discloses the hard scope boundary ('always the user's own audience, never a competitor's'). It does not describe freshness/lag or rate limits, which keeps it short of a 5.

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?

Front-loaded with purpose, then routing, then the no-input rule, so the important material comes first. It is on the long side: the long run of near-duplicate paraphrase triggers ('who are my viewers or subscribers; who am I reaching or serving') is redundant for a human reader, though defensible as routing keywords.

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 parameters, no output schema and annotations covering safety, the description carries the remaining burden well: it says what data source is used, what dimensions the analysis covers, what it will not do (competitor audiences, clarifying questions), and which siblings handle adjacent questions. Nothing an agent needs in order to call it correctly is missing.

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 tool takes zero parameters and the schema is empty at 100% coverage, so the baseline is 4. The description usefully confirms this ('Needs no input: it reads their real connected YouTube channel directly'), removing any doubt that arguments are expected.

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 and resource ('Analyze WHO the signed-in user's YouTube audience is') and enumerates the exact dimensions covered (age, gender, top countries, implications for content). It explicitly excludes the competitor-audience reading and names three sibling tools it is not, so an agent can route without opening another 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?

Gives explicit when-to-use triggers across many phrasings ('who is my audience', 'who watches my channel', 'my audience demographics') and explicit when-not/alternatives: check_discoverability for HOW people find the channel, read_comments for what the audience says, evaluate_idea for what to make next. It also states the precondition that no input is needed and that the agent must not ask the creator anything first.

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?

Annotations cover the safety profile (readOnlyHint=true), so the bar is lower, and the description still adds useful behavioral context: it lists what is returned (performance vs. usual, drop-off, discovery source, comments) and clarifies no user input or authorization setup is needed. No rate limits or pagination behavior mentioned, keeping it short of a 5.

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?

Front-loaded with purpose, then usage, then parameter semantics. It is long, but the redundant-looking synonyms each serve query matching, and there is no filler prose. Slightly overstuffed at the tail.

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 steps up to describe return contents and the zero-input requirement, which is exactly what the agent needs. The only hole is the unexplained `title` parameter, which keeps this from being fully complete.

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?

It adds real meaning for `video` (title or partial title accepted; empty = most recent upload), but the second parameter, `title`, is never mentioned even though the description says to pass a title via `video`. At 50% schema coverage this leaves the agent to guess the role of `title`, which can create ambiguity.

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 (deep dive/analyze) and resource (ONE specific YouTube video of the signed-in user's own channel) with explicit scope. It names the relevant siblings (audit_channel, diagnose_channel, find_best_videos), so an agent can route to it without opening any 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?

Enumerates rich trigger vocabulary (flopped, tanked, underperformed, blew up, went viral, break down, review), covers the 'my last/latest/newest upload' case, and gives explicit exclusions naming the alternatives for other scopes. It even resolves the ambiguous reference ('that video' = most recent upload) and forbids stopping to ask.

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?

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds value by stating that refresh=true is slower, Klyf Pro only, and requires explicit user request, and that the tool reads a live snapshot of the user's channel. It does not cover error behavior or rate limits, but given the annotations, the added context is substantial.

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 front-loaded with the core purpose and then flows into usage and parameters. It is somewhat verbose, but every sentence contributes to routing or parameter clarification. The structure is logical and easy to parse.

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 tool's complexity (broad-channel audit), the presence of a detailed schema for parameters, and no output schema, the description is complete. It covers purpose, usage, alternatives, parameter guidance, and behavioral caveats (refresh slowness, Pro-only). It leaves no critical gaps for an agent to call it correctly.

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 schema fully documents the two parameters. The description repeats the enum meanings and adds context for refresh ('slower', 'Klyf Pro only'), but does not add significant meaning beyond what is already in the schema descriptions.

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 uses specific verbs (audit, overview, read as a whole) and explicitly distinguishes itself from siblings diagnose_channel and check_growth. An agent can understand exactly what this tool does and how it differs from the alternatives.

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?

It provides explicit when-to-use criteria ('when the user asks to audit, analyze, review, assess, evaluate, or check their channel') and gives clear alternatives for overlapping needs (diagnose_channel for ranked list, check_growth for trends). It also includes example phrases, making the routing unambiguous.

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?

Annotations already declare readOnlyHint and openWorldHint, so safety is covered. The description adds real behavioral context: it reads the connected channel directly, needs no input, and should be invoked without asking the creator anything. It also previews what the diagnosis returns (view source, arrival door, actual searches, one change to make).

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?

Purpose is front-loaded, but the body is a single dense block that exhaustively lists near-duplicate user phrasings ('why am I not getting discovered or found, how do I get found or rank...' etc.). The routing value is real, yet the enumeration is longer than it needs to be and the trailing imperative adds bulk.

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 carries the return-value burden and does so by naming the diagnosis dimensions. For a zero-required-param read tool it is nearly complete; the undocumented `title` parameter is the only unresolved gap.

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 coverage is 50%, with `video` documented in both schema and description (title/fragment/'latest', omit for whole channel, reach-vs-conversion framing). The description enriches `video` with the reach-vs-conversion purpose and the 'specific video' trigger, but the `title` parameter remains undocumented in either place.

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 (Diagnose how...gets FOUND) and a scoped resource (the signed-in user's own channel), and explicitly distinguishes itself from analyze_audience, analyze_video, and diagnose_channel. An agent can identify the tool's job 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?

Names alternatives and the exact condition that selects each ('For WHO the audience is... use analyze_audience; for a single video's overall performance... use analyze_video; for the ranked list... use diagnose_channel'). It also enumerates the user phrasings that should route here, leaving little to inference.

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?

Annotations only declare readOnlyHint and openWorldHint; the description adds substantial context beyond that: it requires no input, reads the user's real connected channel, discloses what data it does NOT hold (packaging, retention, reach, comments), and warns that the premise behind a why-question is often wrong. That is rich behavioral guidance an agent could not infer from the annotations.

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?

Front-loaded and well organized (purpose, then usage, then the why-question caveat), but the synonym cascades ('growing or dying, going up or down, gaining or losing steam, getting better or worse') are redundant padding that bloats the text without adding routing value.

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 no-param, read-only, no-output-schema tool, the description covers everything an agent needs: what it returns conceptually (direction and rough turning point), its data limitations, how to combine it with audit_channel for why-questions, and the invocation protocol.

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?

Zero-parameter tool, so the baseline is high; the description goes further by stating explicitly that no input is needed and that it reads the connected YouTube channel directly, resolving any ambiguity about whether the caller must supply a channel ID or link.

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+resource (whether the signed-in user's own YouTube channel is growing/sliding/flat, and roughly when it turned) and the inputs it derives that from. It explicitly distinguishes itself from siblings by naming audit_channel for current-state overview and analyze_video for one video.

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?

Explicit when-to-use coverage: growth/momentum/trajectory questions, and also 'why' questions about stalled growth, with the caveat that the direction alone doesn't answer why. It names the complementary tool (audit_channel with ask 'specific') and the alternatives for other intents, plus an explicit 'call it immediately, never ask the creator first' instruction.

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?

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds real operational context beyond that: it reads the user's real connected channel directly, requires no input, and should be invoked immediately without gathering context from the creator. It does not cover latency, rate limits, or failure modes, which keeps it below a 5.

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?

Front-loaded with purpose and output, then routing, then the no-input directive. Most sentences earn their place, but the closing clause ("not for context, not for a link, not for a title you could look up") is emphatic repetition that could be tightened.

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?

There is no output schema, so the description carries the return-value burden and does so: ranked prioritized list, funnel stage (packaging/retention/audience fit), and per-video cost. Combined with the no-input and immediate-call guidance, nothing needed to invoke it correctly is missing.

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?

Zero parameters, so the baseline is 4. The description reinforces this with "Needs no input: it reads their real connected YouTube channel directly," which tells the agent not to fabricate or solicit arguments.

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 (Diagnose) and resource (the signed-in user's YouTube channel), then specifies the output shape: a ranked, prioritized per-video worklist with funnel stage and cost. It explicitly distinguishes itself from the sibling audit_channel (channel-level context vs per-video worklist), so an agent can route correctly without opening either 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?

Gives an explicit trigger ("call it when the user asks what to fix or improve on their channel") and an explicit alternative with its own condition ("for what the channel is about... call audit_channel instead"). It also states the negative case for inputs: never ask the creator anything first.

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?

Annotations supply readOnlyHint=true and openWorldHint=true, so the safety profile is covered; the description aligns with them by framing the output as a 'draft' rather than a save. It adds real behavioral context beyond annotations: drafts imitate the user's own voice and structure learned from their prior descriptions. It does not state whether the draft is persisted back to YouTube, which is the only notable gap.

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?

Front-loaded with the action, then usage triggers, then parameter routing, then the sibling exclusion — a logical order with no filler. It runs slightly long with 'or the text/notes/blurb under a video,' which is useful disambiguation rather than padding, but the last two clauses could be tightened.

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?

No output schema exists, so the description carries the burden of explaining the return, which it does not do (e.g., whether a draft is saved or just returned, and in what form). With five optional params and no required ones, an agent also lacks guidance on which combinations are valid or what happens with `topic` vs `idea`. Adequate for calling, incomplete for predicting results.

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 coverage is 60% and the description meaningfully explains three of five params (`video`, `idea`, `title`), including when each applies. However, `topic` and `video_title` are undocumented in both the schema and the description, leaving ambiguity about how `topic` differs from `idea` and when `video_title` applies. Helpful but incomplete compensation.

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 ('Draft a YouTube video DESCRIPTION') plus scope ('for the signed-in user, in their own voice'). It explicitly excludes siblings' territory: 'for titles and thumbnails use package_video.' An agent can distinguish it from package_video, draft_script, and suggest_ideas without opening a 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?

Explicit trigger conditions ('when the user asks to write, draft, rewrite, or improve a video description... or the text/notes/blurb under a video') and routing logic: pass `video` for an existing upload, `idea` for a new one, `title` when agreed. It also names the alternative tool for the adjacent job. Nothing is left to inference.

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?

Annotations declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds meaningful behavior beyond that: the shape of the return (hook options, beat-by-beat outline, CTA, suggested title for long-form; word-for-word for Shorts) and a 'Klyf Pro only' gating constraint. It does not contradict the read-only hint since drafting is a generation, not a mutation.

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?

Front-loads the purpose and keeps the routing guidance compact at the end. The middle return-shape sentence is dense but informative; nothing is wasted, though the whole is slightly long.

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?

There is no output schema, so the description carries the burden of describing returns — and it does so reasonably well. With zero required parameters and only the `idea` param left implicit, a caller has enough to invoke it correctly.

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 coverage is 75%, so most parameters are documented in the schema. The description reinforces topic and format (including the short/long values and the default), but it never explains the undocumented `idea` parameter or clarifies the interplay between `topic`, `idea`, and `title`. It adds some value without fully compensating for the 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?

States a specific verb+resource (draft a video script) and scopes it precisely — in the user's voice, built from converting content on their channel. Explicitly distinguishes itself from package_video, evaluate_idea, and suggest_ideas, so an agent can route without opening schemas.

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?

Gives an explicit trigger ('when the user asks to write, draft, or outline a script... or a hook, intro, or outline') and names three alternatives with the conditions that select each. When-to-use and when-to-use-something-else are both covered.

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?

Annotations only mark this as non-read-only/open-world/non-destructive; the description adds substantial behavior beyond that: it branches on plan, returns an upgrade link for non-Pro users, a one-time permission link for Pro users without grants, or a confirmation if already on. This is exactly the liability/flow context an agent needs before calling.

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?

Front-loaded with purpose, then triggers, then mechanics, then the sibling preference — a good ordering. Slightly verbose in the enumerated synonym list ('reply to / respond to / answer'), but those variants earn their place as matching cues rather than filler.

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?

Although no output schema exists, the description itself explains the three possible outcomes (upgrade link, permission link, already-on confirmation), which covers the return-value gap. For a zero-parameter action tool this is complete.

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?

Zero parameters, so schema semantics are trivial and the description has no parameter burden to carry. Baseline 4 applies; nothing here adds or omits parameter meaning.

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+resource (enable auto-reply) and immediately defines the mechanism ('Klyf posting the YouTube comment replies the user approves'). It is clearly distinguishable from reply_to_comment and upgrade_to_pro, which it explicitly references as downstream conditions.

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?

Gives explicit trigger phrasings ('enable or turn on auto-reply', 'reply to / respond to / answer their comments', 'do it for me') and an explicit exclusion: prefer this over posting when auto-reply is not yet enabled. No inference required.

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?

Annotations declare readOnlyHint=true and openWorldHint=true, so the agent already knows this is a safe read operation with open-world grounding. The description adds the grounding basis ('what already converts on their own YouTube channel and what their audience asks for') and the output nature ('light title/thumbnail direction'), which is useful behavioral context. However, it doesn't detail rate limits or the format/depth of the returned evaluation. A 3 is appropriate given annotations already carry the safety profile.

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 sentences, front-loaded with purpose, then usage, then the alternative. Efficient with no wasted words, though slightly dense. The routing to package_video is well-placed at the end.

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 read-only evaluation tool with annotations covering safety and no output schema, the description provides the grounding basis and output nature ('light title/thumbnail direction'). It routes to the sibling for deeper needs. The main gap is unclear parameter semantics due to low schema coverage, but the description is otherwise complete for an agent to call it correctly.

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 coverage is only 33% – only 'idea' is described in the schema, while 'title' and 'topic' are undocumented. The description mentions 'idea, topic, or title' but doesn't clarify how they relate (e.g., whether topic and title are alternatives to idea or supplementary). With low coverage, the description should compensate but only partially does so.

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 (judge/evaluate) and resource (a YouTube video idea, topic, or title) and grounds it in concrete data sources (own channel's conversions, audience asks). It also names the sibling it is not (package_video) for deeper packaging, making it distinguishable from other siblings like suggest_ideas.

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?

Explicitly states when to call it ('whenever the user proposes an idea and asks whether it (or a title) is worth making, will work, or is a good idea') and when to use the alternative ('For deeper packaging help... use package_video instead'). This is a clean when/when-not/alternative structure.

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?

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds meaningful behavioral context beyond that: it reads the user's real connected channel directly, requires no input, and instructs the agent not to ask the creator anything first. It does not describe return format or failure modes (e.g., no connected channel), which keeps it from a 5.

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?

Front-loaded with the core action and pattern scope, and the package_video routing follows early. The final sentence ('Never ask the creator anything first, not for context, not for a link, not for a title you could look up; call it immediately') is somewhat repetitive, restating the no-input point three ways, which costs a little efficiency.

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?

No output schema exists, but the description conveys what the tool surfaces (the shared traits across top thumbnails) and what it does not do (per-video scoring). For a zero-parameter read tool, nothing an agent needs to invoke it correctly is missing.

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?

Zero parameters, so the baseline is 4. The description reinforces this with 'Needs no input: it reads their real connected YouTube channel directly,' which usefully prevents the agent from inventing or requesting arguments.

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+resource ('read what the user's best-performing thumbnails have in common') plus the concrete attributes analyzed (text, faces, colors, layout). It explicitly contrasts itself with package_video, the closest sibling, so an agent can route without opening either 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?

Names the exact triggering conditions ('what makes their best thumbnails work', 'what their winning thumbnails share') and gives a clear exclusion with an alternative ('to generate or score packaging for a specific or new video ... use package_video'). Both when-to-use and when-not-to-use are covered.

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?

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered; the description adds genuinely new context by disclosing the data source (reads the real connected YouTube channel directly) and the zero-input behavior. It does not describe output format or pagination, but that is a minor gap given the annotation coverage.

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?

Front-loaded with the core purpose, but the trigger-phrase sentence is bloated with near-duplicate phrasings ('best retention or held viewers longest', 'most clicks or the best click-through rate') that restate the same ranking dimension twice. Several clauses could be cut without losing information.

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?

There is no output schema, so the description carries the burden of conveying returns, and it does name the ranking dimensions and the inclusion of titles. For a zero-parameter read tool, an agent has everything needed to select and call it correctly.

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 tool takes zero parameters, so the baseline of 4 applies. The description correctly reinforces this with 'Needs no input', leaving nothing ambiguous about how to invoke it.

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 and resource (find the user's best-performing YouTube videos) and enumerates the exact ranking dimensions: subscribers, views, retention, watch time, clicks, comments. An agent can tell this apart from sibling tools like analyze_video or find_best_thumbnails without opening any 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?

Gives an unusually explicit when-to-use list keyed to user phrasings ('what is working', 'which video had the best retention', 'what to make more of') and reinforces it with 'call it immediately'. It does not name any alternative sibling or state when NOT to use it, which keeps it out of 5 territory.

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?

Annotations already declare readOnlyHint and openWorldHint, so safety is covered. The description adds real behavioral value beyond that: it reads the real connected channel directly, requires no input, and explicitly forbids asking the creator for context or links before calling. It does not describe output shape in detail, but it enumerates the digest's contents.

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?

Front-loaded with the resource and contents before routing rules and the call-immediately directive. The final sentence is somewhat repetitive ("not for context, not for a link, not for a title"), but that redundancy is deliberate guardrail emphasis rather than filler.

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?

No output schema exists, yet the description enumerates what comes back (week-over-week views/subscribers, standout video, one fix, a comment to answer, one action), which is exactly what the agent needs to set expectations. Combined with the no-input guarantee and sibling routing, nothing material is missing.

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?

Zero parameters, so the baseline is 4. The description reinforces this with "Needs no input: it reads their real connected YouTube channel directly," which confirms an agent should supply nothing.

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?

Names a specific resource (the creator's YouTube channel) and a specific scope (this week vs last: views, subscribers, standout video, fix, comment, action). It also distinguishes itself from two named siblings, audit_channel and check_growth, so an agent can route without opening schemas.

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?

Provides explicit trigger phrasing ("weekly digest", "what changed this week", "week in review", "catch them up") plus an explicit exclusion rule, routing point-in-time asks to audit_channel and multi-month trends to check_growth. No inference required.

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 readOnlyHint=true and openWorldHint=true already present, the description adds useful behavioral context: output is always a title+thumbnail unit kept complementary, and generation is grounded in the user's own converting packaging. It does not contradict the annotations and goes beyond them by describing the tool's functional behavior.

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 front-loaded with the core action and unit constraint, then moves through trigger conditions, parameter combinations, and sibling routing. It is dense and written as long run-on sentences, but for a five-param multi-mode tool the length is justified and each sentence contributes.

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?

All major call modes are covered: new idea, existing video, follow-up, scoring, plus routing to sibling tools. The only notable omissions are the meaning of the 'topic' parameter and the exact return/output format, which matter more because there is no output schema; still this is detailed enough to select and invoke the tool safely.

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 already documents 4 of 5 params (80% coverage), so baseline is 3. The description adds combination semantics, e.g. passing both video and idea for follow-ups and using title/thumbnail_text for scoring, but it never explains the 'topic' parameter, leaving that mode ambiguous.

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 opening sentence names a specific verb+resource ('PACKAGE a YouTube video') and enumerates its two functional modes: generating title options/thumbnail text ideas or scoring existing ones. It also explicitly differentiates from siblings by naming evaluate_idea, suggest_ideas, and find_best_thumbnails as alternative tools.

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?

It states exact triggers ('Call this whenever the user wants help with a title or a thumbnail...') and gives explicit exclusions: use evaluate_idea for idea-worthiness, suggest_ideas for brainstorming, and find_best_thumbnails for channel patterns. It also specifies when to pass video, idea, or both.

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?

Annotations already cover safety (readOnlyHint) and scope (openWorldHint), so the bar is lower. The description adds real behavioral context beyond them: it reads the real connected channel directly, needs no input, and explicitly forbids asking the creator for context/links/titles first. It does not disclose output shape or pagination/limits, keeping it below a 5.

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?

Front-loaded with purpose, then usage triggers, then the parameter rule, then routing to siblings — a logical order. It is on the long side and mildly repetitive in the closing 'never ask... not for context, not for a link, not for a title' triplet, but every sentence carries routing or behavioral weight.

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 must convey return content, and it does: themes, audience wants/needs/struggles, unanswered count. Combined with the annotation-provided safety and scope, an agent has what it needs to call this correctly; only the unexplained `title` parameter and any result-size limits are unaddressed.

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 coverage is 50%: the `video` param is documented in the schema, and the description adds meaning there (title or partial title, one upload vs whole channel). However `title` is undocumented in both schema and description, leaving the agent to guess its role from a sibling name. Baseline 3 applies given the partial coverage 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?

States a specific verb (read/summarize) and resource (audience YouTube comments for the user's channel) and enumerates the exact outputs: recurring themes, what the audience wants/struggles with, and count of unanswered comments. It explicitly distinguishes itself from analyze_audience and suggest_ideas, so an agent can route correctly without opening either 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?

Gives explicit trigger conditions ('what their audience wants or struggles with', 'what people are saying'), names the sibling alternatives for adjacent intents, and specifies the video-vs-channel decision rule with concrete example utterances. Near-complete when-to-use coverage.

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?

Annotations already declare readOnlyHint, openWorldHint, and destructiveHint, so the safety profile is covered. The description adds genuine behavioral value beyond that: the return scope (original plus whole back-and-forth), the workflow position ('part of Klyf Pro's reply flow'), and the sequencing requirement to call before drafting. It does not cover rate limits or pagination, so it falls just short of a 5.

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?

Front-loads the core purpose in the first sentence, then layers routing and ID guidance. Slightly longer than strictly necessary with some overlap between the 'reply in context' rationale and the selection rules, but nearly every sentence carries routing weight.

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 single-parameter read tool with no output schema, the description supplies everything an agent needs: what is returned, when to invoke it, when not to, and how to source the comment id. Nothing material is missing.

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 coverage is 100% and the single parameter is already documented. The description restates the same 'lc=' value from the reply link, adding no syntax or format detail beyond the schema, so baseline 3 applies.

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 and resource: reading the full reply thread under one YouTube comment, including the original plus the entire back-and-forth. It distinguishes itself from the sibling read_comments explicitly, so an agent can choose correctly without opening a 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?

Gives explicit when ('BEFORE drafting a reply to ONE specific comment that has replies', marked [THREAD] in read_comments), when-not ('Do NOT call this for a general question about what people are saying... that is read_comments only'), and a reinforcing constraint ('Only open a thread when you are actually about to reply'). Routing is unambiguous.

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?

Annotations already declare readOnlyHint=false, destructiveHint=false and openWorldHint=true, so the write/open-world profile is covered. The description adds real value beyond that: it discloses the Klyf Pro gating, the one-time write-permission requirement, and the concrete failure behavior ("it returns the link they need"). It stops short of describing the success response or any rate limiting, so it is not fully exhaustive.

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 sentences, each carrying distinct information: action, approval precondition, and permission/failure behavior plus id sourcing. The most important constraint (approval) is placed first, and there is no filler.

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 two-parameter mutation with no output schema, the description covers the risky parts an agent needs: human approval before posting, permission gating, and the fallback when gating fails. It could say more about what a successful call returns, but given the annotations and schema it is largely complete.

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 coverage is 100%, so both parameters are already documented in the schema, including the 'lc=' derivation for comment_id. The description adds the sourcing context ("from read_comments") that the schema does not give, but otherwise repeats the schema's own wording. Baseline 3 is appropriate when the schema does the heavy lifting.

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 and resource ("Post a reply to one specific YouTube comment") with the scope narrowed to the signed-in user's channel and their behalf. An agent can distinguish it from read_comments, read_comment_thread, and enable_auto_reply without opening any 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?

Gives an explicit precondition ("ONLY call this after you have shown the user the exact reply text and they have explicitly approved posting it") and names the upstream source of the required input (the id from read_comments). It also states the fallback path when the Pro feature or write permission is missing, so the agent knows what to expect when it cannot proceed.

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?

Annotations declare readOnlyHint=true and openWorldHint=true, and the description adds meaningful context beyond that: it reads the user's real connected channel, requires no input, and should be called immediately without asking questions. It does not detail rate limits or timeouts, but for a read-only review tool the remaining behavioral context is minor.

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 core purpose is front-loaded, but the description is long, includes many repeated trigger phrases and several admonitions ('never ask the creator anything first', 'call it immediately') that could be trimmed. It is informative but not concise.

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 zero-required-parameter, read-only tool with no output schema, the description covers what the tool does, when to use it, how to pick a video, and its relationship to siblings. It omits only a few behavioral details (e.g., latency, failure modes), which are minor for this tool type.

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 coverage is 50%—the `video` parameter is documented in the schema, but the `title` parameter has no schema description. The description adds semantics for `video` (partial title, omit for most imminent) but says nothing about `title`, which is unexplained in both places. Baseline 3 is appropriate, with a small residual 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 states a precise verb and resource—reviewing an upcoming (scheduled, unlisted, private/draft) YouTube upload and producing a prioritized fix list—and explicitly contrasts the target with analyze_video (already public) and package_video (titles/thumbnails alone). An agent can distinguish this tool from all siblings without opening a 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?

It gives explicit when-to-use triggers ('is my next video ready', 'review my video for tomorrow'), when-not-to-use alternatives (already public → analyze_video; titles/thumbnails only → package_video), and even when never to ask questions first. Routing is fully specified.

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?

Annotations already declare readOnlyHint=false (a write) while destructiveHint=false and openWorldHint=false, so safety is covered. The description adds genuine behavioral value: it's a fire-and-forget logging action ('send it right away this turn, you can ask a follow-up after') and routes reports away from tool execution. It omits auth/rate-limit details, hence not a 5.

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?

Front-loads the purpose, then the when-to-use rules. Four sentences are justified by genuinely useful routing detail, though the phrasing around the follow-up and the final tool-vs-feedback clarification is slightly repetitive.

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 two-parameter, no-output-schema feedback tool, the description covers purpose, timing, categorization, and the tricky boundary with actionable tool requests. An agent has everything needed to call it correctly.

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%, including an inline description for the kind enum, so the schema already carries the parameter semantics. The description reinforces the categorization with concrete examples ('audit crashed'=bug, 'export my winners'=feature), which is mild added value but stays at the baseline.

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 (Send) and resource (feedback/bug report/feature request) directed at a named recipient (the Klyf team). It also distinguishes itself from sibling action tools by clarifying that a bug report about a Klyf tool is feedback to log here, not a request to run that tool.

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?

Explicitly defines when to send immediately (any specific problem or request, even one line) versus when to ask a follow-up first (only when the complaint is too vague to categorize). It gives concrete examples for both branches and clears up the boundary with tool-running siblings.

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?

The annotations already indicate readOnlyHint=true and openWorldHint=true, and the description adds deeper behavioral context: it reads the connected channel directly, needs no input, derives ideas from winners and comments, and must not prompt the user. It also clarifies that the tool generates from scratch, which is valuable beyond the annotation hints.

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 front-loaded with the core purpose and includes useful trigger phrases and exclusions. It is somewhat repetitive near the end ('Needs no input' and 'Never ask...call it immediately' restate the same point), but each section still earns its place by addressing usage, alternatives, and parameter handling.

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 description covers how to invoke the tool, when to use it, what it reads, and what to avoid. Since there is no output schema, a brief note about the shape or format of the returned ideas would improve completeness, but the current description is sufficient for an agent to call the tool correctly.

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?

Although schema coverage is 100%, the description adds crucial operational guidance for the optional 'subjects' parameter: only pass what the user explicitly said, never guess, and Klyf derives these from the search report otherwise. This tells the agent exactly when and how to populate the parameter, beyond the schema's basic definition.

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 uses a specific verb ('Generate') and resource ('specific video ideas for the signed-in user's own YouTube channel'), and clearly differentiates from evaluate_idea by noting this tool generates from scratch rather than judging an existing idea. This makes the tool's purpose unambiguous.

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 gives explicit trigger conditions ('asks what to make, film, or post next...'), explicitly names the alternative for a different scenario ('use evaluate_idea instead'), and instructs the agent to call it immediately without asking the user questions. This fully routes the agent to the correct tool.

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?

Annotations declare readOnlyHint=false and openWorldHint=true, implying a side-effecting, external-facing call (likely a checkout/session URL), but the description never explains what the returned link is, whether anything is created, or any auth/limits. It adds routing context but no behavioral disclosure beyond the annotations.

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 sentences, purpose front-loaded, the long trigger list is justified because it is the routing logic, and the parameter instruction is placed last where it is needed.

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 one optional param, 100% schema coverage and no output schema, the definition is nearly complete; the only gap is that the return value ('a link') is only implied rather than described in any detail.

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 coverage is 100% with an enum, setting the baseline at 3, but the description goes further by mapping user intent to value: 'year when the user asks for the annual, yearly, or discounted plan; otherwise leave it monthly.' That is genuine semantic value beyond the schema.

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 and resource: 'Give the signed-in user a link to upgrade to Klyf Pro.' No sibling occupies this space (all siblings are analytics/content/reply tools), so the agent can identify it instantly.

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?

Explicitly enumerates the trigger utterances (upgrade, subscribe, go Pro, pay, unlock, remove limits, ask about auto-reply) and even routes the interval choice by user phrasing. This is textbook when-to-use guidance.

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