jobhound_apply_tailored

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 fallback attempt order and that the outcome is recorded in the database, which is useful. However, it does not mention potential side effects like sending emails, irreversibility, or failure behavior beyond the fallback chain, leaving gaps in 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 compact and front-loaded: a clear purpose sentence, a fallback chain sentence, a database side-effect sentence, and a structured Args block. Each sentence earns its place; no fluff. The Args block is a bit redundant with the schema but justifiable given the lack of schema descriptions.

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. The description covers the tool's action, fallback strategy, and database recording. However, it omits prerequisites (e.g., job_id must reference a valid job, tailored_cv should come from get_for_tailoring), error handling if all attempts fail, and potential duplicate-application guards. These gaps make it adequate but not complete for a side-effectful action.

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 has no parameter descriptions (0% coverage), so the Arg list in the description is necessary. It names all three parameters and adds 'markdown' for tailored_cv, but otherwise just restates the schema's names and types. It provides no constraints, examples, or relationships to other tools, so it adds minimal meaning 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 opens with a specific verb-resource pair: 'Submit an application using the tailored CV and cover letter.' It clearly identifies the tool's sole purpose and differentiates it from sibling tools like status, get, update, and get_for_tailoring, which serve different actions.

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 the tool is used when you have a tailored CV and cover letter ready, and the fallback chain (LinkedIn MCP → direct POST → Blackreach) gives context on how it attempts to submit. It doesn't explicitly exclude alternatives, but no sibling tool overlaps with applying, so the usage is clear.

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