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bealmot

sleeper-mcp

by bealmot

auth_status

Diagnose Sleeper API token failures when writes or authenticated reads fail: check length, shape, source, formatting mistakes, and verify acceptance without exposing it.

Instructions

Where each setting came from and whether the token actually works.

Call this first when a write or an authenticated read fails. It reports the token's length, shape and source (environment or config file), names the usual delivery mistakes — an unexpanded ${SLEEPER_TOKEN}, surrounding quotes, a "Bearer " prefix — and then asks Sleeper whether it accepts the token. The token itself is never included in the output.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses what the output contains (token length, shape, source from environment or config file), that a live check is made against Sleeper, and the common delivery failures it detects. The privacy guarantee that the token itself is never emitted is genuinely valuable. It does not state whether the call has any side effects or its cost/rate characteristics, leaving a modest gap.

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?

Four short sentences, with the trigger condition placed immediately after the purpose statement so an agent sees when to call it early. The first sentence is slightly abstract in isolation, but nothing is padded or redundant.

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

Completeness4/5

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

An output schema exists, so return-value documentation is not required, yet the description still characterizes the output, which is a bonus. For a zero-parameter diagnostic with a rich output schema, the only meaningful omission is pointing at setup_token when the diagnosis is that no valid token exists.

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 zero parameters, so there are no argument semantics to explain; per the rubric a 0-parameter tool baselines at 4. Nothing in the description is needed to compensate for schema gaps.

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 opens with a concrete statement of what is reported: the source of each setting and whether the token works. That is a specific diagnostic purpose, not a restatement of the name. It stops short of differentiating from the one obvious sibling, setup_token, which an agent would need to distinguish this read-oriented diagnostic from the token-writing tool.

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

Usage Guidelines4/5

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

"Call this first when a write or an authenticated read fails" gives a clear, actionable trigger condition. There is no explicit when-not or naming of alternatives such as setup_token for the case where the token needs to be set rather than diagnosed, so it falls short of full routing guidance.

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