Silent Directive Tools

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

With no annotations provided, the description carries the full burden. It discloses the output behavior ('Returns each hit with severity and the migration path') and the range of inputs, but does not explicitly state it is read-only or discuss potential side effects like network fetch. This is adequate for a scanning/checking tool.

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, well-structured sentence that front-loads the core purpose and then provides concrete examples and output details. It is efficient without being overly brief, but could be tightened slightly by trimming redundant examples.

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 tool has a single parameter, no output schema, and no annotations. The description explains what inputs are accepted and what the output includes (hits with severity and migration path), which is sufficient for an agent to invoke it correctly. It does not detail exact detection logic, but that is not required.

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 the 'input' parameter as 'Source code, a dependency list, or an http(s) URL to fetch and scan'. The description repeats this and adds nothing new about parameter format or constraints, so the baseline of 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?

The description names the specific verb 'Check' with the resource being code, package lists, or URLs, and enumerates concrete deprecated APIs (OpenAI Assistants, Google Content API, etc.). This clearly distinguishes it from sibling tools like flipworth_resale_scan and website_audit.

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 provides clear context on what the tool does and the types of inputs it accepts, making it obvious when to use it. It does not explicitly state when not to use it or name alternatives, but the specificity of the deprecation focus gives strong contextual guidance.

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 provided, the description carries the burden of disclosing behavioral traits. It discloses that free scans are limited per client and that past the limit the response includes an upgrade link, which is valuable. However, it does not mention any error handling (e.g., invalid URL), whether the image must be publicly accessible (though the schema hints at 'public URL'), or that this is a read-only operation (though implied). It is not misleading but could be more explicit about potential failure modes and constraints.

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 two sentences with no redundancy. The first sentence states the core purpose, and the second provides the input instruction and discloses the limit. It is front-loaded with the most critical information and each sentence earns its place. No fluff or irrelevant detail.

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 simple tool with 2 parameters, no output schema, and no annotations, the description covers the essential context: what it does, how to invoke it (image URL), what the response includes (item identity, resale range, sell-through signals), and the free-scan limitation. It does not detail error cases or the exact format of the output, but these are not critical for a basic scan tool. The description is adequately 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?

The schema description coverage is 100%, with both parameters having meaningful descriptions: category lists example hints, and image_url defines its purpose. The tool description adds no extra parameter meaning beyond what the schema already provides. It only restates that an image URL is needed, which is already in the schema. Therefore, the baseline 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 clearly states the tool's purpose: estimating resale value of a secondhand item from an image URL. It names the specific verb 'Estimate' and the resource ('what a secondhand item is worth to resell'), and mentions the FlipWorth vision engine. This is distinct from the sibling tools (deprecation_check, website_audit), so there is no ambiguity.

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 provides clear context on when to use the tool: 'thrift find, garage sale, shelf photo'. It implies the primary use case is for secondhand items with a photo available. It does not explicitly state alternatives or exclusions, but the siblings are unrelated, so this is sufficient. A clear 'use this when you have a photo of a used item' is effectively conveyed.

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 behavioral burden. It discloses the specific checks performed and the output format (verdict + notes). It does not mention network behavior, timeouts, or rate limits, but for a read-only audit tool the described checks are sufficiently transparent.

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 compact and front-loaded with the core action, followed by a focused checklist and return values. The 'door-to-door web designer' analogy adds character but is not strictly necessary; still, it helps set expectations without bloating the text.

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 tool with a single parameter and no output schema, the description covers the input, the checks performed, and the output verdicts and notes. It does not explain edge cases like invalid URLs or protocol handling, but it provides enough for correct invocation in most expected scenarios.

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% for the only parameter ('url'), and the description does not add meaningful format details beyond what the schema already provides. The baseline of 3 applies because the schema handles parameter documentation adequately.

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 ('audit') with a clearly defined resource ('small-business website') and enumerates concrete checks (load, HTTPS, mobile viewport, page weight, dead/parked domain, social-only). It also names the exact verdict values returned, making it easy to distinguish from the unrelated siblings.

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 clearly frames when to use it: when auditing a small-business website's basic health and legitimacy. It does not explicitly exclude other use cases or mention sibling alternatives, but the scope and checklist are specific enough that an agent can infer appropriate usage.

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