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chieflab_suggest_next_move

P75 — Next Move Engine. USE WHEN measurement just came in (chiefmo_post_launch_review fired automatically at 24h, OR the user manually called it) and you want to know what the operator should do next. Reads metrics + the original launch's brief and emits a deterministic suggestion: {kind: 'follow_up_email' | 'founder_dm' | 'thread_reframe' | 'landing_iteration' | 'lessons_learned_post' | 'seo_title_test' | 'wait' | 'noop', priority, reasoning, draftBrief: {channel, headline, body, cta?, recipients?}, measurementGroundingFacts}. Pure-function; same input → same output, no LLM. Pair with chieflab_create_next_move_action to turn the suggestion into an approval-gated draft.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
runIdNoOptional. Source run whose brief grounds the suggestion (so the draft references the actual product / market / audience instead of templates).
channelYesChannel the measurement is for (linkedin, x, email, landing_hero, product_hunt, hacker_news).
metricsYesMeasurement metrics — engagements, clicks, opens, replies, traffic, conversions, upvotes, rank, etc. Synonyms (engagement / openRate / clickRate / visits) are accepted.
workspaceIdNoOptional workspace id.

TDQS

A4.5/5.0
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 discloses that the tool is a pure-function with no LLM, deterministic (same input → same output), and lists the emitted suggestion structure. This is strong behavioral transparency, though it doesn't cover potential edge-case behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the trigger condition, then output shape, purity, and companion tool reference. Every sentence provides necessary information for an agent; no redundant or filler content.

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

Completeness5/5

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

In the absence of an output schema, the description provides a detailed output structure including kind enum, priority, reasoning, draftBrief fields, and measurementGroundingFacts. It also covers when to use it, inputs, and purity, making it comprehensive for a 4-param nested-object tool.

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 already documents all four parameters with descriptive text (runId's purpose, channel enum, metrics synonyms, workspaceId optional). The description only adds a high-level note about reading 'metrics + the original launch's brief', so it doesn't meaningfully expand beyond the schema.

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 uses a specific verb+resource ('Next Move Engine') and explicitly states it reads metrics and the launch brief to emit a deterministic suggestion. It distinguishes from the sibling chieflab_create_next_move_action by noting the pairing for turning suggestions into approval-gated drafts.

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?

The description includes a clear 'USE WHEN' condition: measurement just came in, either automatically via chieflab_post_launch_review at 24h or manual call. It also explicitly says to pair with chieflab_create_next_move_action, giving an alternative/next step.

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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