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by io.chieflab.api

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 the full burden. It details the tool's effects: creating launchPack, signed reviewUrl, approval-gated actions, 24h measurement, memory, next move, etc. It explains it's an agent-dependency tool. While it could be more explicit about side effects, the description is quite informative.

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 a single paragraph that is information-dense but well-structured, starting with purpose and usage. It could be broken into bullet points for readability, but the content is efficient and every sentence adds value.

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?

Given the tool's complexity (11 params, nested objects, no output schema), the description covers the overall process, outcomes (launchPack, etc.), and important context like gathering repoContext and response shape. It lacks explicit return value documentation but hints via responseShape parameter. Fairly 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?

Schema description coverage is 100%, so baseline is 3. The description does not add parameter-specific meaning beyond what the schema already provides (e.g., channels and outputMode have detailed schema descriptions). The description focuses on overall behavior rather than individual param details, so a 3 is appropriate.

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 it is an alias for chiefmo_launch_product, specifies the exact scenario (after build/ship/deploy) and user queries that trigger its use, and distinguishes from siblings like chiefmo_diagnose_marketing. It provides a specific verb+resource: turning the product into a money/distribution loop.

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?

Explicit 'USE WHEN' conditions are given (after build, user asks 'get users', etc.). It instructs to gather repoContext first and provides a negative guideline ('do not use chiefmo_diagnose_marketing for a new product'). It also directs to route exactly like chiefmo_launch_product, clarifying sibling differentiation.

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

A3.7/5.0
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