list_my_applicationsEvery application sent for this account: company, title, stage, outcome, when it went out, how many screening questions it still waits on, and the employer's acknowledgement where one was received.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| only_waiting_on_me | No | Only applications stalled on unanswered screening questions. | |
| include_cover_letter | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful context about scope ('every application sent for this account') and the returned status fields. However, it does not disclose pagination behavior or how the filter affects the result set.
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, focused sentence that front-loads the scope and then lists the returned fields. It is concise and contains no filler, though the long field list could be slightly more structured.
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?
There is no output schema and only partial parameter documentation, so the description carries a heavy burden. It explains the returned fields but leaves include_cover_letter undefined, does not explain limit behavior or pagination, and provides no decision support for sibling list tools. It is adequate only as a basic overview.
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 only 33%, so the description needed to compensate for the undocumented limit and include_cover_letter parameters. It does not mention either parameter. The mention of 'how many screening questions it still waits on' describes an output field, not the only_waiting_on_me filter semantics, so the description adds no real 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 clearly states a specific verb and resource: it lists applications sent for the current account, and enumerates the fields returned (company, title, stage, outcome, etc.). It is not a tautology and is easy to understand, but it does not explicitly distinguish itself from sibling tools like list_run_history or get_tracker.
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 about when to use this tool versus alternatives such as list_run_history, get_tracker, or list_blocking_questions. The description says what is returned but not why an agent should choose this tool over its siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tool purposes are generally distinct and well-described, but a few clusters overlap in function: answer_screening_question vs save_answer both write to the answer book, get_my_profile vs get_account both report plan status, and the CV preview/sent-CV/base-CV tools could be confused. The detailed descriptions mitigate most misselection, so this is only a minor issue.
The set almost uniformly uses snake_case verb_noun names like list_, get_, update_, create_, delete_, and start_/stop_. Minor deviations such as login, describe_what_i_want, and the get_my_* vs list_* alternation prevent a perfect score, but the overall pattern is predictable and readable.
49 tools is far above the 25+ threshold and will burden agent tool selection even though many are legitimate single-purpose operations. Several groups could be consolidated—billing links, API-key management, and the CV PDF family—without hurting clarity.
The surface covers the full lifecycle: account creation/auth, profile and CV, targeting, matching, apply runs, screening answers, tracking, billing, export, and deletion. Minor gaps remain, such as no application-level detail/withdrawal endpoint and no direct way to save a parsed CV without re-uploading, but agents can work around them.