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devpatel25

resumeai-mcp

by devpatel25

auth_status

Verify Big Interview login and daily scan allowance before starting any work. Returns login state, remaining scans, and email; if not logged in, stop and prompt to run scripts/login.py.

Instructions

Check the Big Interview login and the remaining daily scan allowance before starting any work. Returns logged_in (false is data, not an error), scans_remaining (null when not shown — never guessed), account_email (null when not visible), checked_at. If logged_in=false: stop and ask the user to run scripts/login.py. Pacing: the server adds random 2-5 s human-like delays between UI actions and runs one tool at a time; never call tools in parallel. On ok=false follow error.hint (PLAN.md §13): auth_expired, site_changed, unknown_state, internal_error and profile_in_use are never retried blindly; otherwise retry at most twice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.1

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so: it discloses server-side pacing (random 2-5 s delays, one tool at a time, never parallel), null semantics ('never guessed'), that logged_in=false is data not an error, and a bounded retry policy. This is unusually rich behavioral context.

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?

Purpose and the pre-work trigger are front-loaded, then return fields, then failure handling and pacing. Every clause carries information, though the single dense paragraph packs several distinct concerns (returns, auth failure, pacing, retry policy) that would scan better as separated lines.

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

Completeness5/5

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

For an auth/allowance gate with an output schema present, the description covers the return fields, the not-an-error case, the null cases, the prerequisite action on failure, concurrency constraints, and the retry matrix. Nothing an agent needs to call it correctly is missing.

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

Parameters4/5

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

The tool takes no parameters, so there is no schema semantics to add; the baseline for a zero-param tool is 4. The description correctly spends its words on outputs and behavior instead.

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

Purpose5/5

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

States a specific verb and resource ('Check the Big Interview login and the remaining daily scan allowance') and clearly positions itself as a pre-flight check distinct from the scan-oriented siblings. An agent can tell immediately that this is the auth/allowance gate rather than a scan action.

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

Usage Guidelines5/5

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

Explicitly says to run it 'before starting any work' and prescribes the exact action when logged_in=false (stop and ask the user to run scripts/login.py). It also routes error handling via error.hint and names which error states must never be blindly retried.

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