ChiefLab

chieflab_persistence_health

P91 — verify the persistent stores. Probes proof_ledger / publishing_targets / company_profiles tables (Supabase) OR confirms the in-memory fallback. USE WHEN the user just ran the SQL migrations and wants to confirm the API is now using durable storage; OR before a real founder launch to make sure data won't evaporate on cold start; OR when debugging why a previously-stored target / profile disappeared. Returns per-store: { kind: 'supabase'|'in_memory', durable: bool, tableExists?: bool, sampleQueryOk: bool, rowCount?: number, error?, warning? }. The 'tableExists: false' case means the SQL migration has NOT been run.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`workspaceId`	No

TDQS

A4.1/5.0

Behavior5/5

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

No annotations provided, but description fully discloses tool behavior: returns per-store object with fields kind, durable, tableExists, sampleQueryOk, rowCount, error, warning. Explains meaning of tableExists: false. No contradictions.

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?

Description is front-loaded with core purpose and usage scenarios, then return format. Concise for the information provided, though slightly dense.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers core functionality, usage, and return format. However, missing parameter explanation, and output schema is absent. Adequate for a simple health check tool, but incomplete regarding the workspaceId parameter.

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

Parameters2/5

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

Schema coverage is 0%, so description must explain the single parameter 'workspaceId'. Description does not mention it at all, leaving the agent uncertain about its role or necessity. This is a significant gap.

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?

Description clearly states the tool verifies persistent stores (proof_ledger, publishing_targets, company_profiles) or confirms in-memory fallback. This specific verb+resource distinguishes it from sibling tools like chieflab_get_company_profile or chieflab_query_proof_ledger.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly lists three scenarios: after SQL migrations, before launch, or when debugging data disappearance. Provides clear when-to-use guidance, though it does not explicitly state alternatives or when not to use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All ChiefLab tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.7/5.0

Disambiguation4/5

Most tools have distinct purposes, e.g., approve_action vs execute_approved_action vs publish_approved_post. However, alias overloading (e.g., chieflab_launch_product and chieflab_get_users_after_build pointing to the same handler) introduces some ambiguity. The detailed descriptions mostly mitigate confusion, but an agent might still struggle to choose between near-identical aliases.

Naming Consistency4/5

Tools predominantly follow a 'chieflab_verb_noun' pattern (e.g., chieflab_approve_action, chieflab_connect_provider). A few exceptions exist (chieflab_help, chieflab_inbox, chieflab_boot) that are single nouns, but these are clearly distinct and the overall consistency is high.

Tool Count3/5

32 tools is on the high side for an MCP server, but the domain of a growth/marketing launch platform naturally requires many operations (launch, approve, execute, measure, iterate, connect providers, etc.). The count is borderline but still manageable; it doesn't reach the 50+ extreme.

Completeness4/5

The tool set covers the full launch lifecycle: create, approve, execute, measure, and iterate. It includes provider connections, manual fallback, brain summary, and work requests. Minor gaps exist (e.g., no explicit tool for deleting a launch or revoking approval), but core workflows are fully supported.

Resources

Need Help?