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reference_efforts

Retrieve past efforts' summaries and estimates to compare against current work, enabling calibration of estimation accuracy without exposing actual durations.

Instructions

Prior efforts with their summaries and estimates, for comparison. No actuals.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

C2.1/5.0
Behavior2/5

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

No annotations are provided, so the description must carry behavioral details. It discloses that actuals are not included, which is a key restriction, but it doesn't state whether the operation is read-only, whether it has pagination, or what the output structure looks like. The lack of annotation coverage makes this a significant gap.

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

Conciseness2/5

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

The description is extremely short, which is good for conciseness, but it sacrifices necessary detail. It says nothing about parameters or usage context, making it under-specified rather than effectively concise. It does not front-load any actionable details beyond the core purpose.

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

Completeness2/5

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

Given the tool has two parameters, an output schema, and no annotations, the description is insufficient. It does not explain what the 'kind' filter does, what 'limit' controls, or what 'reference efforts' means in practice. The output schema exists, so return values are covered, but the tool's semantics and usage are not adequately described.

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

Parameters1/5

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

The input schema has zero description coverage, and the description does not mention the 'kind' or 'limit' parameters at all. It only elaborates on the general purpose, leaving the agent without any semantic guidance for how to populate the parameters. This is a critical omission given the 0% coverage.

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

Purpose3/5

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

The description states it provides prior efforts with summaries and estimates for comparison, and explicitly excludes actuals. This distinguishes it from tools that report actual data, but it doesn't specify the verb (e.g., 'list', 'retrieve') or fully clarify its scope relative to sibling tools like effort_table or effort_detail. It's clear enough but not highly specific.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus siblings like effort_table or summary. The phrase 'for comparison' implies a use case, but it doesn't state when not to use it or what alternatives exist. This leaves the agent to infer usage.

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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