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Accept a suggested topic

accept_plan_suggestion

Turn one of the plan's suggestions (see get_plan suggestions) into a real scheduled entry. Lands on the suggestion's date if free, else scheduledDate, else the next open slot. Runs the duplicate-intent guard (blocked response; force: true overrides). Counts against posts per week like any entry. Refresh suggestions (source "refresh": a page the site already owns covers the keyword) never become a new entry and never use a posts-per-week slot: when the owner is one of the site's published plan articles this starts a smart-update draft of that article instead (returns refresh with the updateId; the draft shows up in list_update_opportunities as "ready" in a few minutes, then approve_update; Pro+). Where page refreshes are on for the site, that draft always waits for review even with Updates autopilot on, and accepting a refresh of a page Blawgy did not write writes its update brief (returns refresh with briefReady; read it with get_refresh_brief, then mark_refresh_done once the page is updated). Otherwise a page the plan does not manage returns blocked "not-managed". An article that has not published yet returns blocked "refresh-not-ready", and nothing is added in either blocked case. A suggestion accepted or dismissed earlier returns already: true with its current status; nothing is done twice.

Input Schema

NameRequiredDescriptionDefault
siteYesThe site to act on. One of: fencestainingdenver.com.
forceNo
suggestionIdYes
scheduledDateNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the annotations (which only say non-read-only, non-destructive, non-idempotent), the description discloses the date-fallback order, the duplicate-intent guard with `force: true` override, posts-per-week accounting, Pro+ gating, autopilot review exceptions, and the exact `blocked` reasons ('not-managed', 'refresh-not-ready') with the guarantee that nothing is added in those cases.

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 main behavior is front-loaded and every sentence carries a rule an agent needs. It is dense and the refresh paragraph runs long, so a reader has to parse carefully, but given the branching logic there is little wasted text.

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?

With no output schema, the description takes on the return-shape burden and discharges it: it describes the `refresh` variant with `updateId`/`briefReady`, the `already: true` no-op, and the `blocked` strings. For a tool this branch-heavy, nothing an agent needs to invoke it correctly is missing.

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

Parameters5/5

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

Schema coverage is only 25%, so the description must compensate, and it does: `force` is framed as the duplicate-guard override, `scheduledDate` as the middle rung of the date-fallback ladder, and `suggestionId` as an id drawn from get_plan suggestions. This adds real semantics beyond the bare 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?

Opens with a specific verb and resource: 'Turn one of the plan's suggestions ... into a real scheduled entry.' It names the source (get_plan `suggestions`) and is immediately distinguishable from the sibling dismiss_plan_suggestion and from add_to_plan/approve_update.

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?

It says where suggestions come from (get_plan `suggestions`), what happens per branch, and routes to the correct follow-up tools: approve_update, list_update_opportunities, get_refresh_brief, mark_refresh_done. It even distinguishes the refresh case from the ordinary accept case.

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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