UGCfy AI

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds real behavioral context beyond that: it enumerates the analysis output and discloses the returned breakdown_id token needed for the follow-up call. Auth requirements and rate limits remain unstated, keeping it out of 5 territory.

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, and the long opening clause is dense but every listed element is a distinct output. The input guidance and handoff token follow in two short sentences. Slightly run-on for a single sentence, but nothing is padding.

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: it names the output fields and the breakdown_id handle. Combined with input options and downstream routing, 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 coverage is 100%, so the baseline is 3. The description adds the either/or semantics the schema does not express: supply a public link OR paste the text, framing them as alternative paths rather than values to combine. The optional 'notes' parameter is left to 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?

Specific verb+resource (reverse-engineer a competitor TikTok/IG Reels ad) with an enumerated scope of what gets extracted: hook type, segment structure, selling points, CTA. It also names the downstream sibling rewrite_ad_for_product, so the agent can place it in the workflow without opening other 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?

The description tells the agent exactly which inputs to supply (public video link, or pasted ad text if already available) and what to do with the result by routing to rewrite_ad_for_product. It stops short of stating when NOT to use it or contrasting with siblings like generate_hooks or write_ugc_script.

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, destructiveHint=false, openWorldHint=true, so the safety profile is covered. The description adds one genuine behavioral trait not in the annotations — "Free and unlimited" (no cost, no quota) — but says nothing about determinism, rounding, or what happens on invalid input combinations.

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 short sentences, zero filler, with the core input/output relationship front-loaded before the ancillary "Free and unlimited" note. Nothing repeats the schema or annotations verbatim.

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 stateless three-number calculator with no output schema, the description covers the input contract and names the returned value, which is essentially all an agent needs. It leaves minor gaps: the response field name/format and behavior when zero or three arguments are supplied. Low tool complexity keeps these gaps minor.

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 each property is documented with units, so the baseline would be 3. The description earns a point by stating the cross-parameter constraint — any two must be provided — which the schema cannot express, since it marks all three properties optional with required: [] (0 required parameters).

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 operation on a specific resource: given any two of budget/impressions/CPM, return the third. The title and description together make the calculation semantics unambiguous, and the siblings (breakdown_ad, generate_hooks, rewrite_ad_for_product, write_ugc_script) are all creative tasks with no overlap, so no differentiation is needed.

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?

"Give any two of ... and get the third" is an explicit invocation rule that tells the agent exactly how many and which inputs to supply. It stops short of naming when-not-to-use cases or error behavior (e.g. all three supplied, or only one), but no alternative tool competes for this task.

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 the safety profile (readOnlyHint=true, destructiveHint=false). With no output schema, the description usefully discloses the return shape: exactly 8 lines, each tagged with one of six named hook types plus the underlying psychology. It omits cost/latency behavior, keeping 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?

A single dense sentence that front-loads the deliverable (8 opening lines) and packs the labelling scheme in a parenthetical. Every clause earns its place; nothing is redundant.

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 generator with no output schema, the definition covers the deliverable, its structure, and the labelled hook taxonomy. Safety is handled by annotations and params by the schema. Only minor gaps (no mention of platform's effect on output, no cost/limits) remain.

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 both the required product input and the platform enum are fully documented in the schema. The description adds no syntax or format detail beyond that, so the 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 (Write) and a precisely quantified resource (8 scroll-stopping opening lines for a UGC-style video ad), including the labelling scheme. This is enough for an agent to distinguish it from write_ugc_script (full script) 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?

The description implies the usage context (creating ad hooks) but never says when to reach for this tool versus siblings like write_ugc_script or rewrite_ad_for_product, and offers no exclusions or prerequisites. Usage is inferred rather than stated.

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 (readOnlyHint, openWorldHint, destructiveHint=false) cover the safety profile, so the description's added value is the generative/behavioral context: it produces 1-3 variants, preserves hook type and structure while avoiding copying the competitor, and returns an open_url that hands off to UGCfy AI for rendering with AI actors. It does not clarify whether script text is also returned alongside the URL.

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, front-loaded with the action and its required input, then the return value. Every clause (sources, variant count, structure preservation, no-copy constraint, open_url handoff) carries information an agent needs; nothing is padding.

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 six-parameter, no-output-schema tool this covers the essential contract: inputs accepted, what is generated, and what is returned. A minor gap remains around whether the scripts themselves are returned in the response or only reachable via the open_url, which matters for an agent deciding how to present 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 description coverage is 100%, so the schema already documents product, platform, variants, breakdown_id, reference_video_url, and reference_transcript. The description usefully frames the three reference inputs as interchangeable alternatives, but adds no format, priority, or precedence rules beyond that. Baseline 3 applies 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 (rewrite/write variants), the resource (a reference ad -> scene-by-scene UGC script variants for a different product), and enumerates the three accepted reference sources. It is clearly distinguishable from siblings like breakdown_ad and write_ugc_script.

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 opening clause establishes the precondition for use (you already have a proven reference ad as a breakdown_id, video link, or text) and names breakdown_ad as the upstream source for breakdown_id. It never explicitly contrasts itself with write_ugc_script or generate_hooks for the no-reference case, so the alternative routing is left implicit.

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 declare readOnlyHint=true/openWorldHint=true, but the description adds genuine context beyond them: it discloses the return artifact (an open_url that loads the scripts into UGCfy AI for rendering), which tells the agent the tool generates content rather than mutating stored data. It does not cover auth, rate limits, or failure behavior, so it is useful but not 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 tight sentences, front-loaded with the action and deliverable, then the usage condition, then the return value. No filler and nothing repeated from the title.

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 itself and does so by naming the open_url and its downstream effect (rendering in UGCfy AI). Purpose, usage condition, scope, and return are all covered for a one-parameter generation tool.

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?

There is a single parameter with 100% schema description coverage, so the schema already documents the URL-or-description input. The description's '(link or description)' wording merely mirrors the schema, adding no new syntax, format, or constraint detail; baseline 3 is appropriate.

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 verb (write) and resource (UGC video ad scripts), and quantifies the output precisely: 4 complete 20-30 second scripts, scene by scene, with different angles, plus the product profile. It also names what the tool produces beyond scripts (benefits, proof points, objections), which lets an agent distinguish it from generate_hooks or breakdown_ad 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?

It gives an explicit selection condition: 'Use this when there is no reference ad to copy,' which implicitly rules out the sibling rewrite_ad_for_product. The context is clear, but the alternative is never named directly, so the agent must infer which sibling the exclusion points to.

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