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ChiefLab

by io.github.bdentech

chieflab_get_users_after_build

Outcome-named alias for chiefmo_launch_product. USE WHEN a coding agent just built, shipped, or deployed something and the user asks 'get users', 'find customers', 'make money from this', 'get paying users', 'get eyes on this', 'what now?', or 'how do I launch this?' This is the agent-dependency tool: after build, call this to turn the product into a repo-grounded money/distribution loop with launchPack, signed reviewUrl, approval-gated publish/send actions, 24h measurement, memory, next move, moneyLoop, and agentDependency. Gather repoContext first. Route exactly like chiefmo_launch_product; do not use chiefmo_diagnose_marketing for a new product.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalNoDesired outcome, e.g. 'Get first 100 users', 'find paying customers', 'get design partners', 'make money from this'.
brandNoOptional inline brand context.
channelsNoOptional launch channels. Default is auto-selected from the detected product playbook — service agencies skip Product Hunt; B2B SaaS / devtools / consumer / AI-agent products include it; internal tools default to email + landing only. Pass an explicit subset to override.
tenantIdNoOptional tenant/end-user id for stored brand context and memory.
outputModeNocontext | draft | full | demo. 'demo' is the first-use / YC-demo concise mode — forces 4 punch-list channels (linkedin / x / product_hunt / email), draft rendering, no image gen, scrubbed inline drafts. Defaults to context/draft behavior from chiefmo_launch_product.
productUrlNoLive product URL. Pass either productUrl or productDescription.
repoContextNoStrongly recommended. Include whatChanged, recentCommits, changedFiles, routes, readme, targetCustomer, launchGoal.
responseShapeNosummary (default, smallest — promotes launchId / launchRoomUrl / publishActionIds / firstResponseScript; per-channel draft bodies live behind the reviewUrl) | compact (per-channel previews + truncated draft bodies inline) | full (everything inline; debug/export only — large).
idempotencyKeyNoOptional dedupe key to prevent duplicate launch preparation.
productDescriptionNoShort product description if no public URL exists yet.
includeFullArtifactsNoAlias for responseShape:"full". Backward-compat with older P29 clients.

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries full burden and does well by revealing the behavioral loop: launchPack, signed reviewUrl, approval-gated publish/send actions, 24h measurement, memory, next move, moneyLoop, and agentDependency. It lacks explicit side-effect or permissions detail, but the behavioral arc is clear.

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 longer than two sentences but each sentence adds value: alias identification, trigger conditions, output artifacts, prerequisite, and routing/exclusion. It is front-loaded and structured, though slightly verbose.

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?

The description covers purpose, usage context, behavioral outputs, and routing, which is substantial given no annotations or output schema. It stops short of detailing return values or explicit side effects, but for an alias tool with 11 parameters, it is reasonably complete.

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?

The input schema has 100% parameter coverage with detailed descriptions, so baseline 3 applies. The tool description adds general guidance about repoContext but doesn't enhance per-parameter semantics beyond what the schema already provides.

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 defines the tool as an outcome-named alias for launching a product to acquire users, with explicit trigger phrases like 'get users' and 'find customers'. It distinguishes from the marketing diagnostic tool via 'do not use chiefmo_diagnose_marketing for a new product', establishing a unique purpose among siblings.

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 scenarios ('after build... user asks get users, find customers...'), a prerequisite ('Gather repoContext first'), and an explicit alternative exclusion ('do not use chiefmo_diagnose_marketing'). This gives strong, actionable 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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TDQS

A3.8/5.0
Disambiguation2/5

Many tools have overlapping purposes (e.g., multiple launch and measurement tools), and the presence of aliases like chiefmo_* can confuse an agent. While descriptions are detailed, the sheer number of tools covering similar workflow steps makes it hard to distinguish the right one without careful reading.

Naming Consistency4/5

All public tools start with 'chieflab_' and mostly follow a verb_noun pattern (e.g., chieflab_approve_action, chieflab_set_company_profile). However, some internal names like 'chiefmo_*' appear as aliases, which slightly breaks consistency from the user's perspective.

Tool Count1/5

45 tools is excessive for a single MCP server. While the domain is broad, this many tools likely overwhelms agents and users. Most well-scoped servers have 3-15 tools; 45 indicates poor scoping and should be split into focused sub-servers.

Completeness5/5

The tool surface is extremely comprehensive, covering the full lifecycle from signup and installation to launch, approval, execution, measurement, next-move suggestions, manual fallback, and specialist delegation. No obvious gaps for the stated purpose of growth and distribution.

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