Skip to main content
Glama
Capacities MCP Server

Capacities MCP Server

Get Capacities Object (Markdown)

get_object

Read a Capacities object as Markdown with YAML frontmatter and body, including an authoritative Labels line that resolves status and priority conflicts in rendered data.

Instructions

Read an object rendered as Markdown (YAML frontmatter of its properties + body). A Labels: line before the markdown lists every label property (e.g. Status, Priority) read from the STRUCTURED object, as <propertyId>: <Option>[, <Option>] entries separated by ; ((none) when empty). Where it disagrees with the frontmatter, the Labels line is authoritative: Capacities' markdown render omits some statuses (e.g. Open Question, Backlog, On Hold) and shows Complete as Done.

Input Schema

NameRequiredDescriptionDefault
objectIdYesobjectId of the object to read

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.3.1

TDQS

A3.7/5.0
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 substantial work: it discloses a non-obvious behavioral quirk (the Labels line is parsed from the structured object and overrides frontmatter) and enumerates concrete known discrepancies such as omitted Open Question/Backlog/On Hold and Complete rendered as Done. It stops short of covering error behavior for invalid ids or truncation of large bodies.

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 purpose is front-loaded in the first sentence and the remaining length is spent on parsing-critical detail (separator format, `(none)` sentinel, precedence rule) that genuinely earns its place. It is dense but not padded, though the Labels exposition could be tightened slightly.

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?

For a one-parameter tool with no output schema and no annotations, the description compensates well by describing the exact return shape (frontmatter, body, synthesized Labels line) that an agent would otherwise have to discover empirically. Only failure modes and size limits remain unstated.

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

Parameters3/5

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

Schema description coverage is 100% and there is a single parameter, so the schema already explains objectId. The description adds nothing about id format or provenance, leaving this at the baseline.

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 opening sentence gives a specific verb and resource plus the return format: 'Read an object rendered as Markdown (YAML frontmatter of its properties + body).' It does not, however, distinguish itself from siblings such as find_objects or search_content, nor say how an objectId is obtained.

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?

Usage is only implied by the verb 'Read'; there is no explicit when-to-use guidance, no statement that this is the by-id fetch after find_objects/search_content, and no exclusions. The agent must infer the workflow from the required objectId parameter alone.

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