maxcv — CV tailoring

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses key behavior: returns original match score, score after tailoring, and requirement counts, plus performance traits ('Fast and cheap'). It does not explicitly state it is read-only, but the nature of scoring and the described return values imply no side effects. Given the lack of annotations, this is adequate transparency.

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 remarkably concise: two sentences, front-loaded with the primary purpose, then adding value with return details, performance characteristics, and usage directive. Every sentence serves a distinct purpose with no filler or redundancy.

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 no output schema, the description adequately communicates the return values (original score, after-tailoring score, requirement counts). It also provides context for when to use it relative to tailoring. For a two-parameter tool with no annotations, this is complete enough for an agent to select and invoke 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 input schema has 100% coverage with clear descriptions for both parameters ('The full CV/resume as plain text.' and 'The job posting text.'). The description adds no extra meaning beyond the schema, which is acceptable because the schema already defines the parameters well. This meets the baseline for high 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?

The description clearly states the tool's purpose with a specific verb ('Score') and resource ('CV/resume matches a specific job posting'). It also distinguishes itself from the sibling tool tailor_cv by explicitly positioning it as a pre-tailoring step: 'Use this first to show the user the gap before a full tailor.'

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 explicit usage guidance: 'Use this first to show the user the gap before a full tailor.' This clearly indicates when to use this tool (before tailoring) and implies the alternative (tailor_cv) for subsequent tailoring. It also notes the tool is 'Fast and cheap,' helping the agent decide to invoke it.

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 fully carries the burden of behavioral disclosure. It explicitly states a key guarantee ('never fabricating skills not already present'), lists all return elements, and reveals a rate limit for trial use plus a signup path for unlimited use. This is rich, honest behavioral context beyond the input schema.

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: the first sentence states the purpose and core behavior, and the second provides rate-limit and signup context. Every clause contributes useful information, and no words are 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 tool with only two plain-text parameters and no output schema, the description is complete: it explains what the tool does, the constraints on skills, the exact return value components, and trial limitations. An agent has enough context to select and invoke the tool appropriately.

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?

Input schema descriptions cover both parameters fully (cvText and jobDescription as plain text), so schema coverage is 100%. The description adds conceptual meaning by relating the parameters to ATS keywords and existing skills, but does not add syntax, formatting, or additional parameter-specific details beyond 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?

The description clearly identifies the tool's action ('Tailor a CV/resume'), the target resource ('a specific job posting'), and the core transformation (rewriting with ATS keywords). It also names specific outputs, distinguishing it from the sibling 'score_cv' tool by focusing on tailoring rather than mere scoring.

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 communicates clear use context: it is for tailoring a CV to a job posting and includes the post-tailoring outputs. It does not explicitly exclude alternatives or name 'score_cv' as an alternative, but the verb 'tailor' and the output list imply when this tool is appropriate.

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