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AffiliateSpy

by io.affiliatespy
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Configure autopilot

set_autopilot
Idempotent

Turn the Discovery Autopilot on or off for one project, and/or set that project's commission offer drafts may promise. Autopilot runs for one project at a time: turning it on binds it to app_id (required until autopilot is bound to a project; default after that: the project it runs for). Turning it on starts the hourly proposal loop; new proposals wait for an approval unless the owner has set an auto mode on the Autopilot page. After the bounce breaker stopped the project's mailbox (get_autopilot's paused_reason for that project), turning it on for that project also clears that stop, restarts that mailbox's bounce count and resumes the campaigns the breaker paused for that mailbox, whose queued emails then send on the engine's schedule. Other mailboxes keep their stops, counts and paused campaigns. A stop whose mailbox was not recorded holds every project: turning autopilot on for any project clears it and restarts no count. Guarded: without approval_token it returns {error:"approval_required", approval_token, summary} for the user to confirm; call again with the token. Every dashboard guardrail still applies: this is exactly what a user clicking the dashboard could do, no more.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
offerNoThe commission offer drafts may promise, e.g. "30% recurring". Omit to leave unchanged.
app_idNoProject id from list_apps. Omit for the project autopilot runs for; required while it is bound to none.
statusNoOmit to leave unchanged.
approval_tokenNoApproval token from a previous approval_required response, after the user said yes.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / app_id
      Added value: +{
+  "description": "Project id from list_apps. Omit for the project autopilot runs for; required while it is bound to none.",
+  "format": "uuid",
+  "pattern": "^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$",
+  "type": "string"
+}
    • changedInput schema / properties / offer / maxLength
      Previous value: -120New value: +200
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Goes well beyond the annotations (readOnly false, idempotent true, destructive false) by disclosing side effects: starting the hourly proposal loop, pending approvals, bounce-count resets, resumed campaigns, and the exact {error:'approval_required', approval_token, summary} guard response. The only gap is it never clarifies what awaits-approval means for idempotency of repeated on-calls, but the coverage is still rich, warranting a 4 rather than 5.

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?

Front-loads the core purpose then layers side-effect details; every sentence carries non-redundant information. It is dense to the point of being a long single paragraph, which slightly hurts scannability, but nothing is wasteful.

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?

For a mutation tool with no output schema, the description covers side effects, per-mailbox vs global stop behavior, the guarded approval contract, and the dashboard-parity guarantee. An agent has everything needed to call it correctly and understand the consequences.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds real semantics: app_id is required until autopilot is bound and defaults to the running project afterward, approval_token comes from a prior approval_required response, and offer is what drafts may promise. This is meaningful context beyond the schema text.

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?

States a specific action (turn Discovery Autopilot on/off and/or set the commission offer) on a specific resource (one project). It is clearly distinguishable from the read-only sibling get_autopilot, which it explicitly references for paused_reason.

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?

Explicitly describes when to use it: turning on starts the hourly proposal loop, requires app_id until bound, and clears a bounce-breaker stop per mailbox or globally if the mailbox was unrecorded. It also explains the approval-required first call and the retry-with-token flow, leaving little to inference.

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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