Clipping Daily

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

Annotations already cover the read-only, non-destructive, closed-world profile, so the description's job is to add behavior — and it does, disclosing the default rate source ('current median pay rate unless a rate is given'). It stops short of saying how the estimate is returned or whether it rounds/assumes anything else.

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 front-loaded sentence that states the trigger first and the default behavior second. No filler, no restatement of the tool 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?

With zero required parameters and no output schema, the agent gets no guidance on what the tool actually returns (a dollar figure? a view count? both?) or on how to resolve the ambiguity of supplying target and views at once. The description is adequate for triggering but leaves real gaps for correct invocation.

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 baseline is 3; the description earns above that by making the two operating modes explicit — target_usd (+period) versus views — and by stating the default rate behavior for rate_per_1k. It doesn't clarify what happens if both modes' parameters are supplied together.

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 both directions of the calculation: views needed to hit an income goal, and what a given number of views pays. That is a specific verb+resource, but it never names the sibling get_clipping_pay_rates, so the boundary between 'estimate' and 'fetch the rate' is left implicit.

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 opens with an explicit trigger ('Use when someone asks...') and gives concrete example phrasings ($100/day, $500/day, $10K/month). There is no explicit when-not-to-use or named alternative, which keeps it short of a 5.

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, and openWorldHint=false, so the safety profile is covered. The description adds useful behavioral context beyond that: this is a snapshot (not historical/time-series) of *public* campaign rates, and it names the aggregates returned (median, range, by category and platform). It stops short of stating freshness, coverage limits, or what happens when no rate data exists.

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, zero filler, with the invocation trigger front-loaded before the return-content sentence. Every clause earns its place.

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 burden of explaining returns, and it does so adequately (median, range, by category and platform). Minor gaps remain around data freshness and behavior when the optional filter matches nothing, but 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?

Schema description coverage is 100% and the single optional `category` param is documented with examples (Entertainment, Finance, Streamer). The description only echoes that category and platform breakdowns exist, adding little syntax or semantics beyond the schema; 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?

States a specific verb and resource: returns the latest snapshot of public clipping campaign rates, with median, range, and breakdowns by category and platform. It's clear what the tool produces, but it never names the sibling it must be distinguished from — estimate_clipping_earnings — which also answers questions about clipping pay.

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 "Use when someone asks how much clipping pays, what clipping campaigns pay per 1,000 views, or which categories/platforms pay most" gives concrete trigger phrases, which is strong. However, there is no exclusion: a question like "how much would I earn" could plausibly route to estimate_clipping_earnings, and the description gives no rule to break that tie.

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 readOnly=true, destructive=false and openWorld=false, so the safety profile is covered without description help. The description adds the return shape ('most relevant guides with links'), which is useful given no output schema, but says nothing about result count, ranking, or how many guides come back.

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 with the usage trigger front-loaded before the enumeration of covered topics and the return statement. Every listed topic works as a retrieval cue, so none of the enumeration is wasted.

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 one-parameter, annotation-covered search tool with no output schema, this covers what an agent needs: when to call it, what topics it spans, and what comes back. Only the result-set characteristics (count, ranking, links-only vs. summary) remain unspecified.

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?

Single parameter with 100% schema description coverage, so the schema carries the load and baseline 3 applies. 'Any question about clipping' in the description does add a hint that the query is free-form natural language rather than a keyword, but no format or length guidance is given.

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 retrieval action ('search' implied by name, 'returns the most relevant Clipping Daily guides') over an enumerated topic space. The topic list ('how to start clipping, payout caps, clipping agencies...') clearly signals a documentation-search tool, which implicitly separates it from the calculation siblings, but it never names those siblings 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?

'Use for any question about clipping' gives a clear triggering condition, reinforced by a concrete topic list that maps to realistic user questions. It lacks any when-not guidance or explicit hand-off to estimate_clipping_earnings / get_clipping_pay_rates for numeric questions.

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