Where the founder's agent starts its go-to-market work: diagnose which stage of the Recao Roadmap this account is in (S0 pre-launch to S4 scale), the binding constraint, and the playbook to run. Reads your scans and memory. Sharpen it: write a memory_note named 'company-stage' with your MRR band and funnel numbers, and this tool will use it.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds that it 'reads your scans and memory' and can be improved by writing a memory note, which provides moderate additional behavioral context beyond annotations. However, it does not cover potential side effects or limitations.
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?
The description is extremely concise: three sentences that front-load the core purpose, then detail what it reads, and finally provide a tip. Every sentence serves a purpose without redundancy or excess.
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?
The description covers what the tool does, how it works, and how to improve results. It does not specify the output format (since no output schema exists), but the mention of diagnosing stage, constraint, and playbook gives a reasonable expectation. A minor completeness gap exists regarding the return structure, but overall it is adequate.
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?
The input schema has no parameters (0), so schema coverage is 100% by default. The description adds value by explaining that the tool uses existing scans and memory, and suggests a preparatory action (write a memory_note) to sharpen results. This is additive and actionable, fully compensating for the lack of parameters.
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 clearly states the tool's purpose: 'diagnose which stage of the Recao Roadmap this account is in (S0 pre-launch to S4 scale), the binding constraint, and the playbook to run.' It uses a specific verb (diagnose) and resource (roadmap stage), and the context of being the starting point distinguishes it from sibling tools like get_playbook or assemble_status.
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?
The description suggests this is the starting point for go-to-market work, but it does not explicitly mention when to avoid it or compare to alternatives like get_playbook or memory_note. The tip about writing a memory_note provides indirect usage guidance, but it lacks clear when-to-use or when-not-to-use criteria.
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.
