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Write a lightweight working-memory trace during a task to preserve decisions, assumptions, or observations without promoting them to a full idea.

Instructions

Write a lightweight working-memory trace during a task. Use when: you form a non-trivial synthesis mid-task; you make a decision the session will depend on; you want a durable breadcrumb without promoting it to a full idea yet; you want to leave a visible trace of what changed in your understanding during the task. Do not use for final, standalone ideas that should survive the task — use capture for those. Optional task_ref groups all writes from the same task; it is normalized to lowercase kebab-case at the boundary, so casing and whitespace variants collapse onto the same key. Optional kind_label is a semantic hint (observation | decision | assumption | question | next_step). Returns scored annotate_candidates (existing ideas this trace may update) and related_candidates so the next memory move is obvious. candidates (default 5, max 10, 0 to skip) controls how many annotate/related suggestions are returned — set to 0 for a fire-and-forget trace where you don't intend to act on suggestions, or raise to 10 when actively triaging.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYes
scopeNo
tagsNo
originatorNo
task_refNo
kind_labelNo
candidatesNo
actorNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already declare readOnlyHint=false (write operation) and non-destructive, non-idempotent. The description adds valuable context: the trace is 'lightweight', not final; it returns candidates; task_ref normalization to lowercase kebab-case; kind_label enum; candidates parameter behavior. No contradiction found.

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 two paragraphs, front-loaded with purpose, then usage conditions, then parameter details. It is reasonably concise, though could be slightly tighter. No redundant information.

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?

With 8 params, 1 required, no schema descriptions, and an output schema (not visible), the description covers usage, key parameter behavior, and return values (annotate_candidates, related_candidates). It misses explanation for some optional params but overall is thorough enough for an agent to use correctly.

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 0% (no parameter descriptions in schema). The description explains task_ref (normalization), kind_label (enum values), and candidates (default, max, meaning of 0). However, it does not cover content, scope, tags, originator, actor. Partial but helpful.

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 clearly states the tool's purpose: 'Write a lightweight working-memory trace during a task.' It uses specific verbs and resources, and distinguishes itself from the sibling 'capture' tool by specifying that 'capture' is for final standalone ideas.

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?

The description provides explicit when-to-use scenarios (e.g., 'non-trivial synthesis mid-task', 'decision the session will depend on') and when-not-to-use ('Do not use for final, standalone ideas'). It also names an alternative tool ('capture'). This gives clear guidance for tool selection.

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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