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AgentPlaybooks

by ai.agentplaybooks

Canvas table of contents

get_canvas_toc
Read-onlyIdempotent

Get the table of contents for a canvas document. Returns section IDs, headings, and levels for navigation and patch_canvas_section. Read-only. Use read_canvas for full markdown and list_canvas to discover slugs. Pass playbook_id as the UUID or GUID of the playbook this call should target.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesDocument slug
run_idYesWorkflow run UUID
playbook_idYesUUID or GUID of the target playbook

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tocYes
nameYes
slugYes

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description reinforces read-only status and adds useful context about returning section IDs/headings/levels for navigation and patch_canvas_section, going beyond the structured annotations without contradicting them.

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

Conciseness5/5

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

Three tight sentences deliver purpose, return value, read-only note, alternatives, and parameter hint without any wasted words. Information is front-loaded with the primary action first.

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?

With output schema present and annotations covering safety, the description effectively complements the structured data. It references sibling tools for related operations, covers parameter nuance, and provides sufficient context for a tool of this complexity.

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?

Schema covers 100% of parameter descriptions, including slug, run_id, and playbook_id. The description adds extra clarity by specifying playbook_id as 'the UUID or GUID of the playbook this call should target' and implies slug discovery via list_canvas, enriching the parameter understanding beyond the schema.

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 begins with 'Get the table of contents for a canvas document,' clearly stating the action and resource. It further specifies the returned data (section IDs, headings, levels) and distinguishes itself from read_canvas (full markdown) and list_canvas (slugs), making sibling differentiation explicit.

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?

Explicit guidance is provided: 'Use read_canvas for full markdown and list_canvas to discover slugs.' This tells the agent when not to use this tool and directs to alternatives. It also mentions the purpose for navigation and patch_canvas_section, establishing clear use cases.

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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TDQS

A4.5/5.0
Disambiguation5/5

Each tool targets a distinct entity and action (e.g., delete_memory vs delete_skill vs delete_run), and even similar operations like read_memory vs search_memory vs get_memory_context have clearly differentiated purposes. The descriptions are detailed and explicitly cross-reference other tools to avoid confusion.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (create_*, list_*, update_*, delete_*, read_*, etc.), with plurals used uniformly for list operations (list_playbooks, list_runs, list_secrets). No mixed conventions or ambiguous verbs; the naming is highly predictable and systematic.

Tool Count4/5

With 48 tools, the server covers a broad but coherent set of domains (playbooks, personas, skills, memory, canvas, runs, secrets, MCP servers, and discovery). While this exceeds the typical 3-15 range, each tool serves a distinct and necessary function within the comprehensive playbook management scope, so the count feels justified rather than bloated.

Completeness5/5

The tool surface provides complete CRUD and lifecycle coverage for every entity type: playbooks, personas, skills (including versioning and rollback), memory (including hierarchical tasks and tiering), canvas (with locking and patching), runs, secrets (including rotation and usage), and MCP servers. Additionally, find_tools covers discovery for federated tools, leaving no apparent dead ends.

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