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rajeshaipython-stack

ResumePilot MCP

Search application emails

search_application_emails

Search connected email for application-related messages, classify each into statuses (e.g., INTERVIEW, REJECTED), and update tracking automatically.

Instructions

Search the connected email provider for messages related to an application (by company, role, recruiter email, or domain), classify each into a status (APPLICATION_RECEIVED, SCREENING, INTERVIEW, OFFER, REJECTED, ...), and update the application's tracking. Phase 1 uses an offline mock provider (seed it in tests/demos); Phase 5 connects Gmail via OAuth (read-only, no passwords stored).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinceNoISO date; only newer messages.
domainNo
applicationYes
recruiterEmailNo
Behavior4/5

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

With no annotations provided, the description bears the full burden. It clearly discloses the side effect of updating application tracking, the read-only nature of the Gmail connection via OAuth, and that no passwords are stored. It also explains the status classification. This is strong transparency, though it stops short of describing error behaviors or edge cases.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the core action, then lists the classification and side effect, and finally provider details. It is efficiently written without excess, though the phase info could be separated more clearly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (search, classify, update), 4 parameters, no output schema, and no annotations, the description provides enough to invoke it (application ID is required, optional filters are listed) but omits the return value format and any error handling expectations. It is adequate but not fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 25% (only 'since' has a description). The description mentions search by company, role, recruiter email, or domain, but the schema only includes 'domain' and 'recruiterEmail'—company and role are absent. It does not clarify the meaning of 'application' (required) or 'domain' beyond the name. The description fails to compensate for the low schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Search') and resource ('connected email provider'), and details the actions: classify into statuses and update tracking. It is distinguishable from siblings like get_application_status (read-only) and update_application_tracking (direct update) because it explicitly includes search and classification, but it does not name any sibling as an alternative.

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

Usage Guidelines3/5

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

The description provides useful context about provider phases (mock vs. Gmail) but does not explicitly state when to use this tool versus alternatives like search_jobs or get_application_status. It implies usage for searching and classifying application-related emails, but lacks explicit when-not or alternative routing.

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

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