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canonical_memory

Read-onlyIdempotent

Read the machine-wide canonical memory of what the user has told any agent, organized into sections like about, preferences, and active projects. Call it before asking the user something they may already have answered elsewhere.

Instructions

READ-ONLY: read the machine-wide canonical memory, which is what docmancer has reconciled about this user across every agent and project. Local disk read, machine-wide, so it takes no project_path. Call it before asking the user something they may already have told another agent. Not a search tool: it returns whole prepared sections rather than matches, so use search_memory or ask_memory to look something up. To change what it returns, use pin_memory rather than edit_memory. Parameters: section selects one of about (who the user is), preferences (how they want to work), working-principles (cross-project rules), active-projects (what they are working on), or canonical-memory (a description of the store itself); omit section entirely for a status summary of every section. Returns, with a section, that section split into its pinned zone (durable, survives reconciliation) and its generated zone (rewritten automatically), plus content_hash and revision id. Without a section, returns per-section presence and pinned-line counts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sectionNoCanonical section to read. Omit for a status summary of every section.
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description adds materially: local disk read, machine-wide scope, no project_path, the pinned vs generated zone split, content_hash/revision id, and the status summary behavior. No contradiction with annotations.

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?

Although longer than average, every sentence earns its place: it front-loads READ-ONLY, then explains what/why/when, alternative tools, parameter semantics, and return behavior in a logical flow. There is no filler or redundancy.

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?

The description covers purpose, usage timing, return values (with and without a section), alternatives, and limitations (not a search tool). Given the simplicity of the input schema and lack of output schema, the description fully compensates and leaves no relevant question unanswered.

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

Parameters5/5

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

Schema coverage is 100% for the single parameter, but the description goes beyond by explaining each enum value (about, preferences, working-principles, active-projects, canonical-memory) and the behavior when omitted. This adds clarity beyond the bare 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 uses a specific verb ('read') and a clearly defined resource ('machine-wide canonical memory'), and explicitly distinguishes itself from sibling tools by stating 'Not a search tool' and pointing to search_memory/ask_memory. It also contrasts with mutation tools (pin_memory vs edit_memory), so the agent knows exactly what this tool does.

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?

Provides explicit when-to-use guidance: 'Call it before asking the user something they may already have told another agent.' It also gives clear exclusions and alternatives: 'use search_memory or ask_memory to look something up' and 'To change what it returns, use pin_memory rather than edit_memory.'

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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