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karbassi

slack-mcp

by karbassi

canvases_sections_lookup

Search for specific sections within a Slack canvas by filtering on text content or section types.

Instructions

Find sections matching criteria in a canvas.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
criteriaYesFilter for which sections to return, e.g. a ``contains_text`` substring and/or ``section_types``.
canvas_idYesEncoded ID of the canvas to search within (e.g. ``F0123ABC456``).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv3.0.0
    • addedInput schema / properties / canvas_id / description
      Added value: +"Encoded ID of the canvas to search within (e.g. ``F0123ABC456``)."
    • addedInput schema / properties / criteria / description
      Added value: +"Filter for which sections to return, e.g. a ``contains_text`` substring and/or ``section_types``."
  2. Changed1 schema field changedv2.2.0
    • changedInput schema / properties / criteria / additionalProperties
      Previous value: -{
      -  "type": "string"
      -}New value: +true
  3. First observedv2.0.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, and the description does not disclose any behavioral traits like read-only nature, pagination, error conditions, or what happens if no sections match. The agent lacks insight into side effects or constraints.

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 a single, efficient sentence. It is front-loaded and to the point. However, it could include slightly more context without sacrificing conciseness.

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 presence of an output schema and two simple parameters, the description is minimally adequate. However, it lacks context on usage scenarios, limitations, and distinguishing features from similar tools. Additional behavioral details would improve completeness.

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 coverage is 100% with both parameters described. The description adds no additional meaning beyond the schema; for example, 'criteria' already has a detailed description in the schema. Baseline 3 is appropriate.

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?

The description 'Find sections matching criteria in a canvas' uses a specific verb ('Find') and clearly identifies the resource ('sections in a canvas'). It distinguishes from sibling tools like canvases_create or canvases_delete, which deal with canvas-level operations.

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?

The description provides no guidance on when to use this tool versus alternatives, such as when to use search_all or other search tools. There are no exclusions or context about prerequisites.

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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