Content Ops PL

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

With no annotations, the description carries the full behavioral burden. It discloses the core transformation and that the tool returns cleaned text plus flags, but it does not explain what the flags mean, whether the input is mutated, or any side effects. This is adequate for a simple text-processing tool but leaves important behavioral details unspecified.

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 filler. Every clause adds information: the action, the target, the method, and the return 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?

Without an output schema or annotations, the description must explain enough for an agent to invoke the tool and interpret results. It mentions 'flags' but does not define them, and it references 'SOP anti-slop rules' without elaboration. For a tool with only two simple parameters, this is workable but not 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 description coverage is 100%, so the schema already documents both parameters ('Draft text to clean' and 'Optional voice / tone notes for the edit'). The description adds no additional parameter-level meaning, so the baseline score of 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 specifies a clear action ('Tighten'), a resource ('Polish copy'), and a concrete operation ('strip AI/corp fillers using SOP anti-slop rules'). It also states the return value, making the tool's purpose easy to grasp. However, it does not explicitly differentiate from siblings like draft_linkedin_pl, and 'Polish' could be misread as the verb 'polish' without context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool: when copy contains AI or corporate fillers that need tightening. It does not provide explicit when-not-to-use guidance or name alternatives, so an agent must infer the appropriate context from the phrase 'SOP anti-slop rules'.

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 are empty, so the description carries the behavioral burden. It does disclose a key trait: 'Deterministic template engine (MVP)', which signals predictable, template-limited output. However, it does not describe output format, handling of the optional audience field, or limitations of the MVP beyond the label.

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 with no filler. The core action and inputs are front-loaded, and the 'Deterministic template engine (MVP)' caveat adds useful context without bloat.

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 low-complexity generation tool with three simple parameters and no nested objects, the description is largely sufficient: inputs are clear and the output is inferable as a LinkedIn post draft. The main gap is not describing the output format or how the optional audience parameter affects generation, but the schema covers the parameter itself.

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 structured schema already documents all three parameters. The description adds only the connection between brand_voice, brief, and the generated post, which is useful but does not meaningfully extend the schema's own parameter 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 names a specific verb ('Generate'), a concrete resource ('Polish LinkedIn post'), and the inputs it acts on ('brand_voice + brief'). It is clearly distinct from sibling tools like anti_slop_edit and week_content_plan, though it does not explicitly call out those 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?

There is no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. The 'MVP' note implies a limited, template-based use case, but the description leaves the selection criteria entirely to the agent's 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?

With no annotations, the description carries the full burden. It communicates an information-only catalog with no apparent side effects and lists the returned content, but it does not describe output format, static vs dynamic data, or any operational constraints. This is adequate but minimal.

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?

One short, front-loaded phrase contains the essential information without filler. Every word adds value: free, catalog, tool names, USD prices, and input schema summaries.

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-parameter read-only catalog tool with no output schema, the description covers the necessary content: availability, pricing, and schema summaries. It could be slightly more explicit about the returned list structure or that it covers all tools, but it is essentially complete for this simple 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?

The tool has zero parameters and schema coverage is 100%, so the baseline of 4 applies. The description's mention of 'input schema summaries' refers to output content, not to parameters of this tool; no additional parameter semantics are needed.

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 specifies the resource (a catalog) and its exact contents: tool names, USD prices, and input schema summaries. It is clearly distinct from the sibling content tools, though it lacks an explicit verb and reads as a noun phrase rather than a statement of action.

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 catalog nature implies it should be used to discover available tools and prices, but there is no explicit when-to-use guidance or contrast with alternatives. Sibling names make the difference obvious, but the description itself does not state the selection condition.

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, but it only states the intended output. It does not disclose whether the tool is a read-only generator, what format the plan takes, or any side effects or prerequisites.

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 filler. It efficiently communicates the action, deliverable, and inputs.

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 is adequate for basic invocation, but because there is no output schema it does not explain what the 7-day plan looks like or clarify whether 'Polish' means language or audience. This leaves some ambiguity for an agent choosing and calling the 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?

Schema description coverage is 100%, so the schema already documents all three parameters. The description adds minimal extra meaning, mainly clarifying channels are optional, which the schema also states.

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 ('Build') and a concrete deliverable ('7-day Polish content plan'), with inputs clearly stated. It is readily distinguishable from siblings like draft_linkedin_pl or list_catalog, though it does not explicitly name 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?

There is no guidance on when to use this tool versus alternatives such as draft_linkedin_pl, nor any exclusions. The usage context is only implied by the purpose statement, not articulated.

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