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

No annotations are provided, so the description carries the full behavioral burden. 'Estimate' implies a non-mutating calculation, but the description does not state whether the tool is read-only, requires authentication, has side effects, or returns deterministic results. It lacks meaningful behavioral detail beyond the purpose.

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 a single front-loaded sentence with no wasted words. It is concise, though for a six-parameter calculator with no other documentation, it may be too sparse to be fully appropriately sized.

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 six parameters, zero schema descriptions, no annotations, and no output schema, the one-sentence description is not complete enough. It does not explain parameter meanings, defaults, return values, or calculation behavior, leaving significant gaps 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?

Schema description coverage is 0%, so the description must compensate. It mentions output metrics like reach, engagements, and conversions, which loosely correspond to some parameters (avg_reach, engagement_rate_pct, conversion_rate_pct), but it does not explain the required inputs, defaults, units, or the role of click_rate_pct. Compensation is minimal.

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 ('Estimate') and lists the calculated outputs (reach, engagements, conversions, unit costs) for a creator campaign plan. It is clear what the tool does, though it does not differentiate itself from siblings like engagement_check or draft_brief.

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 a domain context ('for a creator campaign plan') but provides no explicit guidance on when to use this tool versus alternatives, nor any prerequisites or exclusions. Usage must be inferred.

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

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

With no annotations, the description carries the full burden. It discloses the country list and the compliance-label concept, indicating a read-only validation, but it doesn't say whether it returns pass/fail, a reason, a severity, or whether it errors on unknown captions. Adequate but incomplete.

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?

Single sentence, front-loaded with the action and the resource, with the country list as a compact parenthetical. Efficient and readable, though it could use a clarifying sentence about the return.

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-param compliance checker with no annotations, no output schema, and no enum on country, the description is too thin. It conveys the purpose but leaves the return shape, country-code format, and error behavior undefined, requiring the caller to probe.

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 0% and there are two required parameters (caption, country). The description mentions 'caption' and lists expected countries, which slightly informs the country param, but doesn't specify format (e.g., ISO code vs. name), caption length, or what happens with unsupported countries. This fails to compensate for the 0% schema coverage.

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 (check/disclosure) and resource (sponsored caption) with the exact regulatory concept being verified (paid-partnership label). It's clear what the tool does, though the sibling tools (campaign_math, engagement_check) are in different domains, so cross-sibling differentiation is less critical.

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?

No guidance on when to use this versus alternatives, nor what conditions trigger the check. It implies a compliance-checking use case but doesn't state prerequisites or what a caller should do with the result. This falls short of 'clear context'.

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

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

With no annotations, the description carries the full burden. It discloses output format (one-page Markdown) and that a market-appropriate disclosure label is embedded, which is useful, but says nothing about whether anything is persisted, permissions required, or how errors are surfaced.

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 with no filler; output format and key content are stated up front. It is efficient, though extremely sparse for a tool with 11 parameters.

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?

An output schema exists so return values need not be described, but with no annotations, no parameter documentation, and a terse one-sentence description, an agent lacks enough context to fill the 7 required fields 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 0% across 11 parameters, and the description only hints at one of them ('market', mapping loosely to country). Brand, product, goal, audience, platform, deliverables, key_messages, dos, donts, and deadline are left entirely unexplained.

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 ('Write a one-page creator brief in Markdown') plus an additional deliverable ('the right disclosure label for the market'). This distinguishes it functionally from check_disclosure, but it never names siblings to make the boundary explicit.

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?

No when-to-use or when-not-to-use guidance. It is unclear whether this should be called before or instead of check_disclosure, and no prerequisites are stated despite the presence of that sibling 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?

With no annotations, the description carries the full behavioral burden. It usefully discloses the output categories ('healthy, weak or suspicious') and the tier classification behavior, implying a pure read-only computation, but says nothing about thresholds, determinism, or how inputs are bounded.

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 tightly written sentence that front-loads the core action and packs in both the classification and the verdict. No wasted words or 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, no annotations, and 0% schema coverage mean the description should explain return values and input semantics more fully. It covers the output categories at a high level but leaves thresholds, input formats, and error behavior 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 description coverage is 0%, so the description must compensate. It ties 'followers' to a follower tier and 'engagement_rate_pct' to engagement health, giving domain meaning to both required params, but provides no units, ranges, or format details for either.

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 gives a concrete verb+resource pair: classify a creator's follower tier and judge engagement health. It clearly states what the tool does, though it does not explicitly distinguish itself from siblings like campaign_math or check_disclosure.

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?

No guidance on when to use this versus the siblings (campaign_math, check_disclosure, draft_brief), no prerequisites, and no exclusions. Usage is only implied by the description's scope.

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