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AfterLaunch: the agentic growth marketing engine

by io.afterlaunch

untrack_prompt

Remove one buyer question from the AI visibility (GEO) set, freeing a slot against the cap of 15. Free, spends nothing. Same two honest consequences as track_prompt: the next scheduled scan runs at full depth, and the week-over-week trend re-baselines. Matched on the question text, ignoring case and punctuation, and IDEMPOTENT. Requires the 'config' scope and the Founder plan.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe tracked question to remove, from list_tracked_prompts. Matched ignoring case and punctuation.

TDQS

A4.5/5.0
Behavior5/5

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

The annotations only set readOnlyHint=false and destructiveHint=false, which add little. The description compensates fully by disclosing the side effects (next scan runs at full depth, trend re-baselines), matching semantics (case/punctuation insensitive), idempotency, and access requirements. This is rich behavioral context beyond the annotations.

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 dense but efficient, with four sentences covering purpose, consequences, matching, idempotency, and requirements. Every sentence adds value, and the main action is stated first. No redundancy or fluff.

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?

The tool is simple (one parameter, no output schema), and the description covers all essential aspects: what it does, side effects, matching behavior, idempotency, prerequisites, and cost. It references track_prompt for consequences but also states them inline, so no missing information.

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 schema has 100% coverage: the 'text' parameter is described as 'The tracked question to remove, from list_tracked_prompts. Matched ignoring case and punctuation.' The description repeats the matching logic but does not add new semantic meaning. Since the schema already documents the parameter well, baseline 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 the action ('Remove one buyer question from the AI visibility (GEO) set') and the purpose ('freeing a slot against the cap of 15'). It distinguishes this from the sibling `track_prompt` by implication (removal vs. addition) and specifies the exact resource being modified.

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?

The description provides context (used to remove tracked questions) and prerequisites (requires 'config' scope and Founder plan). It references track_prompt for consequences, which implies the alternative, but does not explicitly state when not to use it. Still, the usage scenario is clear.

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

A3.9/5.0
Disambiguation4/5

Most tools follow a clear action+resource pattern (get_, list_, set_, ship_, etc.) with distinct purposes. A few boundaries could cause confusion, such as get_move vs get_output (both return drafts) and ship_move vs set_output_status (both mark things shipped), though descriptions mitigate this sufficiently.

Naming Consistency4/5

The overwhelming majority use consistent snake_case verb_noun naming (list_feed, ship_move, get_visibility). The only outlier is 'whoami', a common convention but not verb_noun; otherwise the pattern is highly predictable.

Tool Count2/5

At 41 tools, the surface is well over the 25-tool threshold for 'too many'. While the domain is broad, this volume places significant cognitive load on agents and suggests some consolidation or modularization could help.

Completeness3/5

Core workflows for moves and outputs are covered (create/list/get/update/ship/skip/undo). However, the tool descriptions reference 'approve_output' as the publishing action, yet that tool is absent from the list, leaving a dead end for channel distribution. There are also no tools for editing competitors or managing Memory pages beyond recording insights.

Resources