List this account's company memory, one line per entry (name + description), newest first. Traverse index-first: scan this, then memory_recall(name) for full bodies. Memory accrues automatically from your competitor scans (exhaust) and from your own memory_note writes.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds value by detailing output format, ordering, and automatic memory accumulation from competitor scans and memory_note writes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with front-loaded purpose and efficient explanation of usage and data sources. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only index tool with no output schema, the description fully covers what the tool returns (one line per entry, name+description, newest first) and how memory is populated, meeting completeness needs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters; schema coverage is 100% trivially. Baseline 4 applies, and description adds no parameter-specific detail but explains the tool's behavior adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List'), resource ('company memory'), and details format ('one line per entry (name + description), newest first'). It clearly distinguishes from siblings like memory_recall and memory_note.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to 'Traverse index-first: scan this, then memory_recall(name) for full bodies,' providing a clear workflow. Also explains how memory accrues, informing when the index is relevant.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clear, distinct purpose. The status checkers (assemble_status, clips_status) are differentiated by the job type they monitor. Memory tools (index, note, recall) are distinct operations. Competitor ad tools (search, get ads, get details) and video generation pipeline (avatar, clips, assembly) are well-separated.
All tools use consistent snake_case with a verb_noun or noun_verb pattern (e.g., assemble_video, get_competitor_ads, memory_index). No mixing of conventions, making the tool names predictable and easy to understand.
With 17 tools, the server covers account management, memory, competitor research, and video generation without being overwhelming. The count is well-scoped for its functionality, neither too sparse nor too heavy.
The toolset covers the core workflows: account setup (sign_up, upgrade, whoami), memory (CRUD), competitor analysis (search, get ads, details), and video ad creation (avatar, clips, assembly). Minor gaps like lacking a delete memory tool are acceptable given the domain focus.
